Digital Twin: A new Technology for Future Building Sector

Digital Twin: A new Technology for Future Building Sector | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Digital Twin: A new Technology for Future Building Sector Pragya Vaishnav, Chandrashekhar Patel, Linesh Raja, Ningthoujam Avichandra Singh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9039690/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract The building sector's historically sluggish adoption of digital technologies, due to these results are ineffective workflows, frequent cost overruns, and delays. Moreover, these challenges are exacerbated by the fact that it is a disjointed organization due to market forces. Through the promotion of innovation and enhanced collaboration, the digitalization and shift towards Industry 4.0 can potentially increase the productivity and efficiency of construction significantly and reduce the number of the information gaps and inconsistencies in data. The motivation behind the study is the fact that the digital twin-technology may be applied at different stages of the building, starting with a simple design, all the way to project delivery. Existing studies indicate the innovative impact of digital twin technology on ensuring environmental sustainability and innovative building approaches. These virtual replicas are important in simplifying the manufacturing processes in industries through synchronization of social interactions and production. The analysis in depth, the applications of the digital twin technology to the construction industry demonstrate how the technology can be used to accelerate the coordination process and can be used to facilitate the process of sharing the data between the interested parties. Landlords are driving the digitization of collaborative innovation processes in construction as they become more aware of the value of digital twin technologies in local environment. Enhancing asset quality, optimizing project delivery, and promoting social sustainability are all achieved by including digital twin technology from the beginning of a project and maintaining its use throughout the design phase. With the growing connection between sustainability objectives and technology, the construction sector is poised for a profound shift. Digital twin Construction Smart City computer-aided design (CAD) and Building Information Modelling (BIM) Figures Figure 1 Figure 2 Figure 3 1. Introduction The rise of Industry 4.0 and related initiatives across different sectors, such as Smart Cities. Engineering, and manufacture, serve as excellent illustrations of the swift progress in technology that has occurred recently [ 2 ]. These include Manufacturing 4.0 [ 10 ], Education 4.0 [ 8 ], Mass personalization [ 9 ], Mining 4.0 [ 10 ], Real Estate 4.0 [ 6 , 7 ], Building 4.0 [ 3 ], and Construction 4.0 [ 4 , 5 ]. Integrating digital and physical worlds is essential to the Industry 4.0 idea. Notwithstanding these developments, the building sector faced various issues, the most pressing of which was the urgent need for improved environmental sustainability as well as higher levels of output and operational effectiveness. Digitalization and information technology have been major forces behind the growth of several industries in recent decades. To fully reap the future benefits of Industry 4.0, the building sector must find creative solutions to a specific set of challenges. In this instance, For the building sector to continue growing and being eco- friendly, it becomes necessary to address environmental issues and enhance overall operational effectiveness [ 11 ]. It is a part of the latest phase of the Industrial Revolution, which builds upon technological advancements on par with the revolutionary advances in automation, electrification, and mechanization that preceded it [ 12 ]. 2. Literature Review A very fragmented manufacturing process is a characteristic feature of the building sector which leads to a slow uptake of technology. Both of these characteristics are the reason why the sector lacks competitiveness as a whole [ 13 ]. Although the emerging digital technologies will have huge long term payoffs, the industry is not yet ready to adopt the new technologies as suggested by Columbus [ 14 ]. Blending styles and fields of construction. Digitization and information technology can be used to improve performers, participants and Concerned parties at all the levels of project execution. Love & Matthews [ 15 ] argue that to achieve the value and benefit of technology, behaviour, practice, expectation, relationships and change in strategy of the company need to be adjusted. Gunderson [ 16 ] believes that technology plays an important role in ensuring the existence of a symbiotic relationship between the society and the firms, more so in their ability to impact the environment. Technology should be assessed accordingly with regard to such intricate relations [ 17 , 18 ]. Building Information Modelling (BIM) is an important device to the building industry amid the digital transformation. The vast majority of the recent studies have focused on a number of methods to enhance this technology. The 3D models developed nowadays, as described by Boje et al. [ 19 ], are not simply models since they also hold digital tools that enable data mining, communication among a large number of Concerned parties, and specific information at the component level. Lim et al. [ 20 ] define the term digital twin to refer to an approach that has been extensively adopted in business world to conduct mathematical modelling, simulation and optimization. It helps in exchanging information between the internal and external Concerned parties as far as smart manufacturing is concerned [ 21 ]. The concept of digital twin technology that connects the parts, devices and mechanisms to the specific architecture is becoming more popular in the global debate of urban planning [ 22 ]. In the case of national and urban sceneries being represented with the help of digital twin, the growing consensus is that construction industry may be revolutionized. This will involve virtual testing of complicated systems before actual implementation into the physical life and real time data analysis [ 23 ]. The main goal of the provided research is to participate in a profound investigation of the suitability and viability of the implementation of the digital twin technology into the building surroundings and functioning may make the sustainability more complete, the operational effectiveness more intensive, and the productivity higher. Our study was motivated by the background issue of the development of the sphere of building sector and the implementation of digitalization [ 13 ]. The use of digital twin technology that will be applied in the whole process of constructing a building is still subject to research. This study seeks to generalize its review with the literature on urban planning, construction sites, and site logistics in their review of digital twin technologies in the context of built environments, intelligent buildings, and smart cities. 3. Methodology The current work is carried out in accordance with the principles of systematic reviews, outlined by Saieg et al. [ 24 ]. The systematic review methodology allows the research team to locate, filter and review all the literature available which is relevant to a predetermined standard of quality, a process which Booth and Papaioannou, (2012) emphasize. Among the principal advantages of adopting this procedural framework, there is the fact that it imposes a strict and standardized investigative protocol to the area of interest as emphasized by S. Li et al. [ 25 ]. Subsequently, one can make the results transparently free of subjective bias, which is the quality this approach has guaranteed, according to Jesson et al [ 26 ]. The method has a number of problems. Significant studies with non-significant results and articles that are not written in the English language will be overlooked because most journals tend to publish papers that contain significant impacts [ 25 ]. The Fig. 1 is the outline of this extensive systematic review. 3.1.1. Research approach and the choice of studies. 3.1.1. Data Source Selection The current review follows the principles of conducting a systematic review [ 24 , 25 ] by utilizing a systematic approach to the analysis of a certain amount and quality of studies related to the digital twin technology and construction 4.0 (2) to provide readers with a clear, objective, and standardised technical roadmap that includes information about the database selection, retrieval of studies, and the criteria of target studies selection; and (3) is reproducible and scalable. The key elements of this systematic strategy include; (1) development of a question; (2) identification of relevant studies; (3) selection and assessment of the relevant studies; (4) content-analysis of the relevant studies; and (5) summary of the findings and conclusions [ 25 ]. The researcher used Scopus databases to search relevant literature and some excellent works that explain the state of digital twin technology and building 4.0 in New Zealand were found in foreign publications. Thus, the objective of our study is to explain the flaws of the digital twin technology. Particularly, authi would be concerned with establishing their contributions and potential outcomes. The datasets of S. Li et al. [ 25 ] were therefore deemed particularly useful to our study owing to their massive scope and academic bearing. We did not decide to select Scopus as our primary source randomly. It has an amazing coverage of 15,000 journals published by 4000 publishers, including academic giants in terms of abstract and citation collections. The choice of literature was made to include the publications published between July 2023 and July 2018, which will ensure the corpus of data will be substantial and exemplified by the academic rigor to ensure a thorough picture of the applications of digital twin technology in the building industry. 3.1.2. Peer Retrieval From January 2023 through July 2023, a monthly search of the databases was conducted using the same search methodology. The Scopus criteria consisted of the phrases "title," "abstract," and "keywords" along with the keyboard combination "Digital Twin" AND "Building sector" OR "BIM". It was essential in any academic research to thoroughly review the body of existing literature to collect as much information as possible about pertinent studies. The first step of our data retrieval process was a thorough gathering from three different databases, with a focus on studies that explained how digital twin technology was implemented in the construction sector. Author carefully applied filters to obtain the most pertinent outputs. This article highlighted what appears to be a vacuum in our sophisticated retrieval process: there is a noticeable lack of literature on lean construction in the New Zealand setting, indicating a topic that need more in-depth investigation. After the dual-phase data retrieval, two independent researchers carefully evaluated the remaining papers to guarantee rigor and reduce bias. This required a detailed examination of the publications' principal text, abstracts, titles, and keywords. Author used both inclusion and exclusion criteria to reduce the total number of papers taken into consideration [ 25 ]. The requirements stated that any literature that was redundant should be removed, as should any that had nothing to do with applying digital twin technology to the construction sector. Lastly, any material that merely alluded to the concept of digital twin technology but not delved deeply into it had to be eliminated. The evaluation results were classified into 3 categories based on the following standards: not relevant, somewhat relevant, and relevant. First, two researchers talked about the literature that had variable evaluation results and was categorized as either pertinent or not pertinent, as well as the material that was categorized as somewhat relevant. Next, they tried to come to a consensus over what ought to be included and omitted from the study. The members of the lean construction team spoke and ultimately came to an understanding over the literature on which they could not agree. Table 1 is a represent the initial search in the Scopus database. The first search yields a set of papers, book chapters, and conference papers. The aforementioned things were subsequently removed, with the exception of the articles. Thus, the search was restricted to articles only. As a result, after the first purification process, 246 publications were retained as articles, as shown in Fig. 2 . Table 1 Initially received publications for Insight based on the quantity of search results Search engine and Database Keyword Research (No of articles) Limit to Document Type Initial Search Results Scopus “Digital twin and Building sector” Or BIM 246 Title, abstract and keywords Conference Papers, Books, Book chapter, and article Removing Duplicates Scopus “Digital twin and Building sector” Or BIM 133 Title, abstract and keywords Conference Papers, Books, Book chapter, and article 3.2. Content Analysis The clusters of the topic examined by the research team were aimed at assessing the contribution of the articles to the formation and possible further content direction in New Zealand. Having reviewed the 130 selected publications, the team found out that the research covered a broad array of topics, such as the following: Although some of them discuss the concepts, principles, technologies, and methodologies involved in lean construction, others examine how the digital twin technology is applied to provide supply chain management, construction 4.0, and other scholarly topics [ 25 , 27 ]. The factors that affect the use of digital twin technology in the building business are analysed by some and the effectiveness of digital twin [ 13 , 28 ] is investigated by others. The 130 selected papers were then encoded upon reading their titles, abstracts and keywords lists. In case, the necessary data that could not be located through the title, or abstract of the article, or the keywords, the whole text had to be read and coded. These articles were handled using Microsoft Word [ 29 , 30 ]. The articles were organized into one page with all the articles that had a similar subtopic and each article had a subtopic color-coded according to the category it belonged to. Four distinct subject matter groupings were identified during the in-depth analysis of all the 130 articles. The main aspect of the coding was the critical elements of the material and information in the literature. There were four important parts of information that were coded: (1) paper title; (2) the name of the author; (3) publication date; and (4) the title of the journal the article was published in. The issues that were discussed in the literature about studying the digital twins technology were grouped into four groups that included: (1) theory and application of digital twin technology (2) application of digital twin technology in the research areas in the building sector (3) factors that influence the digital twin technology, and (4) evaluation of the impact of the digital twin. Each cluster of subjects was divided into several subtopics. The coding and classification should also be consistent in order to make sure that the content analysis can be accurate [ 30 , 31 ]. It was due to this that a researcher with a lot of experience in using digital twin technology in building sector facilitated a training session in this study that involved two coders engaged in coding activities and a systematic training aspect. 4. Findings 4.1. Industry 4.0 and Construction 4.0 Industry 4.0 or the first phases of the fourth industrial revolution are already underway in the world in various business realms, as Popkova and Zmiyak [ 32 ] note. According to Khan et al. [ 33 ], the fourth industrial revolution, also known as Industry 4.0, is characterized by the high level of digitization and the utilization of big data and process automation. This is contrary to other three past industrial revolutions which have introduced new technologies. According to Popkova and Zmiyak [ 32 ], the fourth industrial revolution, or Industry 4.0 is different as compared to other industrial revolutions in a myriad of previously unseen aspects, including that there are no people or manual decision-making processes involved in the systems. According to Popkova & Zmiyak [ 32 ], Bonnet and Westerman [ 34 ], Khan et al. [ 33 ], and others, the automation of processes is a key to the success of Industry 4.0. Digitalization development has reached the phase of digital enablement and support already and it is finally at the phase of digital control that unites and binds the digital and physical world, as defined by Qi et al. [ 35 ]. The Industry 4.0 is founded on strongly defined siX design notions by Khan et al. [ 33 ]. Widened communication across technology and human, or interoperability, is the capability to operate with the recently developed technologies such as Cyber-Physical Systems (CPS) and the IoT. Virtualization is the visualization and replication of activities in the real world in the digital world (2). (3) Decentralization refers to the procedure that involves the replacement of CPS systems that can make decisions independently with those that previously had to be given approval by a centralized authority. (4) Real-time capability is the capability to utilize real-time data acquisition to examine and find problems in systems and processes. (5). Service orientation is used in decision making by the operators and managers as well as customers using CPS-connected services. (6). This is termed modularity [ 33 ] when it is possible to quickly add new machines, processes, and modules. Sawhney et al. [ 36 ] gave an outline in support of Construction 4.0. It applies Industry 4.0 design models to the construction industry. The next construction 4.0 definition provided by the authors is as follows: Construction 4.0 is a model that connects the digital layer, comprised of BIM and Common Data Environments (CDE), and the physical layer, comprised of the asset throughout its entire life, through CPS, the IOT, data, and services. This establishes a networked environment, where organizations, processes, and data are incorporated in an efficient manner to design, build and run assets [ 36 ]. In order to understand the numerous layers which comprise Construction 4.0, one should possess a deep knowledge of the technology which facilitates such transition [ 37 ]. Although the other papers in the corpus look at diverse technologies of Construction 4.0, in this article the researchers look at nine technologies commonly cited in the current research corpus [ 38 ]. All these technologies are outlined in the short paragraphs that follow, in a manner in which the technology enables the user to passively view the information presented to them; augmented reality (AR) is an information aggregator, as well as, a publishing platform of data. Virtual reality (VR) involves the use of headgear with 360-degree vision that provides users with an intensive virtual experience and introduces a distinct degree of expertise to the users [ 39 , 40 ]. Compared to standard Building Information Modelling (BIM), Integrated Building Information Modelling (iBIM) is seen as being at a higher level. Robots that can perform or mimic human behaviours are used in robotics. Additive manufacturing, refer as 3D printing, is the process of turning a computer-aided design (CAD) model into a complex, real 3D object [ 41 ]. The term artificial intelligence (AI) describes the capacity of a computer program to mimic human cognitive function [ 37 ]. Drones, also known as unmanned aerial vehicles (UAVs), are small, unmanned aircraft that may be operated from a distance. Based on common and compatible communication protocols, the Internet of Things (IoT) is a dynamic, worldwide network infrastructure with self-configuring capabilities [ 37 ]. The phrase "Internet of Things," which is frequently shortened to "IoT," is a combination of the terms "Internet" and "things." The Internet is a massive, worldwide network of linked computer networks that serves billions of people worldwide by using the standard Internet protocol suite (TCP/IP) [ 42 ]. With millions of private, public, academic, corporate, and government networks of all sizes connected by a variety of optical, wireless, and electronic networking technologies, it functions as a network of networks. The term "things" refers to a wide range of recognizable items or entities in the physical world. These can be commonplace objects like electronics and high-tech products, or they can be more unusual objects that aren't always thought of as electronic, like food, clothes, furniture, materials, parts, equipment, merchandise, specialized items, monuments, works of art, and the various aspects of commerce, culture, and sophistication that are all around us [ 43 ]. One definition of big data, according to Bilal et al. [ 44 ], is the capacity to handle vast volumes of data and extract insightful knowledge from it. Large datasets with a variety of complex structures and large sizes are referred to as "big data," which poses storage, processing, and visualization problems for later steps or results [ 45 ]. At the initial stage of Construction 4.0 integration activities, a life-cycle view on technology utilization is taken into consideration. A project moved on to the design, construction, and facility management phases after the initial planning stage. Eadie et al. [ 46 ] state that integrating technology at the right point in a building project's lifespan allows for the full use of that technology. Teisserenc & Sepasgozar [ 18 ] state that improved communication and interaction amongst the Construction 4.0 technologies are necessary for the second phase of integration efforts. As per the findings of Aleksandrova et al. [ 47 ], the all-encompassing integration of digital technology signifies a noteworthy model change in the building process, establishing a cohesive digital ecosystem. The shift to Construction 4.0 calls for modifications to both methodology and thought processes. The development of digital technologies and their adaptation to the needs of the building sector are extremely dynamic, expensive, and highly customizable [ 37 ]. Furthermore, educating employees and workers to adjust to their new roles is necessary when deploying new technologies. As a result, integrating the new technologies into daily operations and making them usable for a variety of projects is the only method for construction companies to generate excess value [ 48 ]. Rather of taking the more traditional project-oriented approach, one must embrace a process-oriented perspective in order to successfully shift to Construction 4.0 [ 49 ]. On the other hand, this change in perspective forces construction companies to digitize the processes they currently employ, which creates an additional obstacle for two reasons: 1) Not all procedures can be instantly digitalized, and 2) Most current procedures were developed pas years the currently available digital technologies were even imagined. Because of this, all of the current procedures must be redesigned to accommodate the mentality change and enable the construction organizations' transition to Industry 4.0. A comprehensive framework for Construction 4.0 is also presented by Sawhney et al. [ 36 ] and is built on the concepts that drive Industry 4.0. Using digital technologies, the digital layer serves as an interface to connect several physical layers. As a result, a strong connection is made between the real and digital worlds. The authors stress the value of Common Data Environments (CDE) and Building Information Modelling (BIM) in creating a DT [ 50 ]. While Building Information Modelling (BIM) allows for a model-centric approach and visible 3D connectivity, CDE offers a continuous stream of data and data management [ 51 – 53 ]. Throughout the complete life cycle of an asset, from its conception to its demolition, these digital layers support downstream activities in addition to aiding in the design and construction of the asset itself. This remains valid even after they have given their approval for the planning and execution of an investment [ 2 ]. 4.2. Technology in Construction Conducting an effective examination into corporate management requires taking into account and critically analyzing the role that technology plays [ 16 , 17 ]. Depending on the many technological theories, this role of technology may change. According to Orlikowski & Scott (2008), organizational activity is typically constructively interwoven under certain conditions. Because of this, technology cannot be understood in isolation from its context, significance, and effects. Ideas should be flexible and frequently evolve to keep up with the advancement of technology and the application industry [ 54 , 55 ]. This will guarantee that technical innovations are not associated with any intentions or attributes. As the relationship between technology and work in organizations has not yet been conceived, a more advanced theoretical lens will eventually need to be created. Understanding the integrated, diverse, and always changing role of technology probably requires drawing from a variety of technological perspectives and conceptual frameworks. According to Gunderson [ 16 ], technology's overt presence may eventually fade as it gets increasingly integrated into society. This gently alludes to the intricate relationship between technology and the social consequences that follow. Similarly, Lee et al. [ 56 ] contend that even in cases where the technical component is not directly linked to organizational functions, theoretical frameworks that study the effects and dynamics of technology provide insightful glasses through which to see the world. According to this model, technology transcends its physical form to take on the roles and purposes intended for it. Therefore, the idea of digital twin technology should not be understood in terms of its technological architecture alone, but rather in terms of its potential for interaction with organizational processes and its applicability to current and future construction methodologies. Orlikowski & Scott [ 57 ] state that the focus on technology in organizational study is often motivated by the ways in which technology interacts and influences the field. Gunderson [ 16 ] asserts that technology affects how societies engage with their constructed and natural surroundings, as well as how organizations interact with one another. Although digital twin technologies are becoming more and more incorporated into different situational practices, they have not yet become widely accepted as a crucial component of organizational operations in the building sector. According to Peine [ 58 ], a technological model can explain some aspects of how technology develops in response to particular circumstances, but it is unable to explain how innovation occurs overall. Peine (2008) characterizes it as a technological model with a prevailing design, mutual obligation, and mentality. Scientific models, which are expected solutions to a problem that are widely accepted by all Concerned parties, are the source of this concept. If the dominating design has been correctly developed throughout an industry, the technological model can represent the cumulative technical advancement within that industry quite well. However, it is more difficult to coordinate around a shared commitment and mindset. Peine's [ 58 ] description of the technological model is similar to that of Cantwell & Hayashi [ 59 ]. They characterize it as the similarities among a collection of innovations and discoveries that take place throughout time and at a period when organizational procedures and scientific concepts are similar. The model shifts and the integration of key technological aspects and novel forms of information, institutions, and production variables serve as the best illustrations of process of invention and societal evolution. These technological, socioeconomic, and political models may be applied in the manufacturing industry, in technological domains, or in society, claim Cantwell & Hayashi [ 59 ]. 4.3 Digitalisation in the Building sector In the building sector, there is currently a clear differentiation between companies that have adopted digital technologies and procedures. Building Information Modelling (BIM), Tekla, and other CAD-related apps are a few examples, along with others that still depend on more traditional methods. This "digital divide" can be attributed, according to Ayinla & Adamu [ 60 ], to a number of distinct limitations and constraints that companies face while seeking to apply digitalization. Ayinla & Adamu [ 60 ] looked into the idea that an organization's adoption of digitalization is heavily influenced by financial reasons. The government, project owners, or customers may place external demands or obligations on this procedure. Governments are increasingly requiring the use of BIM, especially for larger contractors, and as a delivery format, according to Bosch-Sijtsema et al. [ 61 ]. This has increased the quantity of digitalization in projects [ 54 ]. For SMEs, however, the adoption of BIM has happened more gradually. This purported value states that the main determinant of whether BIM is deployed or not is BIM [ 61 ]. While non-users do not appreciate the value in technology to the same extent as actual users, the latter strongly believe in its benefits and support its use. Additionally, despite the creation of regulations that strengthen the need for BIM, small and medium-sized firms (SMEs) are impacted by the implementation of BIM since they lack the resources to invest in BIM technology to the same extent as larger players. Two of these barriers include, according to Dainty et al. [ 62 ], the cost of software and training. The ability of companies, especially those built with "innovation thinking" as a guiding principle, is crucial in evaluating the influence of these factors, claim Ayinla & Adamu [ 60 ]. The digital gap is more prevalent in larger firms, as specific employees are impacted by the skill and motivational barriers associated with BIM, according to Dainty et al. [ 62 ]. According to Davies & Harty [ 63 ], a person's willingness to adopt BIM is correlated with how they see the technology's potential to help them in their field of work. Workers' decisions on whether or not to adopt BIM will be influenced by their newly developed understanding of what constitutes performance in their current role and how implementing BIM will either enhance or diminish that performance [ 64 , 65 ]. There is still variation in the level of true digitalization, even among those using digital tools. For example, some organizations think that their digitalization criteria may be satisfied by only moving from paper to digital documents. But the industry's digital transformation involves a much more complex set of conditions, and in order for companies to evolve and achieve saturation, they must yield to pressure from both the inside and the outside [ 66 , 67 ]. Bosch-Rekveldt et al. [ 68 ] state that the construction sector is unique in a number of ways. Its organization, for instance, is project-based; large construction projects might take decades to complete, while smaller construction projects operate almost exactly like separate businesses. In hierarchical organizations, project managers perform a role similar to that of the chief executive officer. Compared to other industries like manufacturing, the building sector is said to have a vertical structure, which limits the exchange of knowledge and data between projects [ 55 , 69 ]. 4.4 The idea of Digital twin Digital twins are a very recent notion that is constantly changing. However, since the 1960s, the idea which came about as a result of NASA's space missions has been used in a number of sectors[ 70 ]. The DT model phrase was credited to Dr. Michael Grieves in 2002. Nonetheless, since the 1960s, the idea has been used in a variety of businesses. Despite the traditional definition of DTs, one approach to conceptualize it is as the integration of a physical thing, its digital representation, and the ways in which both are interconnected. When there is a bidirectional relationship between the two, a true DT is completed, providing a legitimate and accurate representation of the physical asset [ 71 ]. Depending on the use, the physical and digital products' connectivity may change. However, when there is a link between the two in both directions, a true DT is produced. Because of its enormous potential benefits, the notion of DTs is especially relevant to the building sector. The idea of digital twin technology is seen in Fig. 3. However, there are a variety of definitions of DTs in this industry because there isn't one that is widely acknowledged. It is necessary to look into these often used definitions. A DT technique is defined as an integrated multi-physics, multi-scale, probabilistic simulation of a complex product by Glaessgen & Stargel [ 72 ]. To simulate the life of its corresponding twin, this simulation makes use of the greatest physical models currently available, sensor updates, and other similar features. A cyber-physical system product lifecycle model, according to Schroeder et al. [ 73 ], is a virtual representation of an actual product that includes data about the product from the beginning of its lifecycle to its disposal. Leng et al. [ 74 ] describe the linked representation as a digital twin technology of the machine that runs on the cloud platform and simulates the state of health by combining other physically accessible knowledge with data-driven analytical algorithms. The Centre for Digital Built Britain (CDBB) proposed two distinct definitions of a DT in its Gemini Principles: the first highlighted the model's dynamism, while the second highlighted the model's strategic significance. A dynamic model of an asset is one that gives real-time control to its physical twin in the form of live data flows from sensors, receiving current performance data from the physical twin and feeding it back [ 75 ]. By employing corporate plans to a system model for the system's static strategic planning reacts to the physical twin through the capital investment, using imputed long-term data from the physical twin. Fig: 3 Digital twin Technology Adopting Digital Twin Technology solutions is becoming increasingly common as the demand for increased efficiency and competitiveness in construction develops [ 13 ]. This entails the integration of several Industry 4.0 technologies specifically designed for building environments [ 76 ]. The application of Industry 4.0 technologies to the four fundamental components of DT is covered in detail in the following sections. These characteristics include data collection, data processing, modelling and simulation, and enablers for decision support [ 13 ]. Modelling and Simulation The core elements of DT technologies are modelling and simulation. Both make use of high-fidelity 3D models and simulations to offer intricate visual aids for assessing specific scenarios and verifying automatically generated solutions. These features work in concert with the other construction-related technologies shown in Table 2 . Data processing It is essential to managing the enormous volumes of heterogeneous, real-time data that are gathered. In order to obtain useful information for modelling and analysis, raw data must be converted and treated. A review of the facilitating technology tools used in different academic works to address issues unique to the construction sector is given in Table 3 . Enablers for decision support An essential component of construction systems, decision support gives them the ability to manage disruptions and guarantee seamless lifecycle transitions. The key to this capability is the implementation of diverse tools and methodologies for semantic solution generation, as shown in Table 4 . The importance of AI in decision support is emphasized, and particular AI domains are crucial in this regard. Data acquisition The data acquisition procedure starts the process of extracting raw data, and it ends with the transfer of information to a database or cloud-based server. Table 5 lists the main technologies and the construction applications that go along with them. When it comes to advanced building, the procedure is all about carefully digitizing resources and assets to create a virtual environment [ 79 , 80 ]. Collecting data from many sources, having two-way real-time connectivity for monitoring and control, and facilitating smooth cyber-physical information interchange are all part of this comprehensive digitization. Following industrial communication protocols, a variety of sensors and communication devices are used to collect physical data at construction sites. Mapping this data onto cyber entities is made easier by methods like point cloud mapping and BIM modelling [ 87 ]. To guarantee correct representation and simulation of construction activities, a variety of techniques are used in the cyber component, including point clouds, 3D models, simulation, and BIM [ 86 , 89 ]. In order to convert raw data into useful information and knowledge, the following computational and data processing layers are essential. By handling data, storage, retrieval, and modules related to analytical processing, this is accomplished. To create meaningful relationships between data nodes and easily integrate diverse data sources, data fusion and semantic modelling are used [ 90 ]. The functional layer is locating essential construction applications and adding domain-specific knowledge, such as stakeholder preferences, safety measures, and regulations [ 91 , 82 ]. End customers are provided with this carefully honed knowledge via user-friendly graphical interfaces. These interfaces enable users to apply system-generated solutions while interacting with and managing physical assets. Certain construction issues can be successfully dealt with and overcome by incorporating these modules [ 84 ]. 4.5. The transition from Bim to twin In the construction context, Design-Build (DTs) refers to a conceptual strategy that improves the process of sector selection by utilizing a variety of technology tools, including Building Information Modelling (BIM) [ 51 , 53 ]. As per Linderoth [ 91 ], BIM is currently the digital modelling technique that the building sector has adopted to the greatest extent. It has been in use for a very long time to create 3D asset representations. However, BIM has changed over time to allow for greater integration since the introduction of the Industry Foundation Classes (IFC) standard. One of the primary benefit of BIM technology, according to Petrova-Antonova & Spasov [ 92 ], is that it provides a semantic 3D model that serves as a database of asset data. Table 2 Modelling and simulation in Building sector. Technology Construction Application Building Information Modelling (BIM) Disaster planning and damage inspection capabilities are essential for improving structural health monitoring (SHM). By combining these elements, the SHM system can more effectively anticipate and address possible structural problems, guaranteeing security and lessening the effects of calamities.[ 64 , 65 ] Facility management enhances building lifecycle management (BLM), comfort, and energy efficiency. Add anomaly detection, maintenance, and decision support systems.[ 51 , 53 ]creating and maximizing resources. Lean manufacturing and configure-to-order techniques can be used to automate construction-related production processes. Make the most of the precast components' production. Develop enduring habits.[ 77 , 78 ] Virtual/Augmented Reality The collaboration of robots and humans. facilitates asset management and two-way communication, which eases task planning and supervision.[ 39 ] Urban planning and design. Multiple viewpoints and usability assessment from non-expert participants in the construction process.[ 39 ] Point Cloud asset design and visualization. uses LiDAR, gestalt design principles, and as-built reconstruction approaches to create city and building models; models are categorized using ML/DL-based point cloud interpretation[ 55 , 69 ]. It looks at a structure's degree of establishment, projects potential harm to a structure, and evaluates services for digitally rendered structures in a virtual reality setting[ 54 , 55 ]. Simulation Optimizing the structure's architecture. The time and cost of developing prototypes may be reduced by using high-resolution analysis and parametric geometric modelling[ 66 , 67 ]. Enhancing the performance of buildings. Turn on infrastructure visualizations to keep an eye on the environment and electricity[ 64 ]. Table 3 Data processing in building sector Technology Construction Application Blockchain project management. increased automation and intelligence development [ 79 ]. enhancing the performance of buildings. Boost the energy efficiency of the new and old structures[ 80 ]. Data Mining Form enduring behaviours. builds an intelligent platform with blockchain integration to support built-up residential buildings[ 81 ]. Project management. Improve service, cooperate with Concerned parties, and implement contracts to increase efficiency[ 56 ]. Modelling creating and maximizing resources. Equipment reconfiguration or re-installation should be allowed to handle interruption of any kind. Find a panorama where the localization mistake is at least one meter. Increase the assets' representation[ 49 ]. Table 4 Decision support enablers in the building sector Technology Construction Application Machine Learning surveillance of construction machinery. Examine an asset's performance under different scenarios[ 82 ]. optimizing construction on-site. Maximize the timeline for the construction process and the structures that make up the building[ 83 ]. authority over security. Construct a security system and DT-based interior safety management system for a three-story elevator in a commercial building[ 84 ]. Computer Vision Facilities management includes movement recognition for maintenance tasks and the restoration of 3D structures from CAD drawings and street view images[ 41 ]. bridge maintenance system. Using image recognition can enhance inspection processes[ 85 ]. Table 5 data acquisition Building sector Technology Construction Application IOT Enhancing the surveillance of structural health (SHM). Preventive maintenance for infrastructure ought to be covered[ 86 ]. enhancing the performance of buildings. Incorporate energy efficiency, enhanced FM system, sustainability assessment, and interior safety management into the BLM process[ 87 ]. Wireless sensor Network To lower building expenses, improve energy efficiency and lifespan management[ 88 ]. It enhances structural health monitoring by utilizing cyber-physical systems (SHM)[ 89 ]. Social Media Enhance the construction lifecycle management process. Included are the plan, design, building, and utilization elements[ 90 ]. However, BIM data may not be readily integrated into other systems, including IoT devices, due to a number of organizational, informational, and technological challenges [ 41 ]. One potential answer to this issue is the creation of a CDE in conjunction with BIM, which allows for the semantic integration of various datasets, attributes, and examples [ 41 ]. This model for system architecture offers a significant chance to enhance decision support, especially in the design stage of the lifecycle. Integration issues still exist, preventing valuable data and information from being connected to other systems, even with current advancements. According to Camposano et al. [ 93 ], the concept of DT has emerged as a viable solution to address the difficulties. Although DTs and BIM are comparable in that they both allow for the creation of 3D renderings of assets, DTs offer greater complexity and integration opportunities due to their emphasis on creating a platform that is user-centric and human-cantered. As-sets are visualized in three dimensions using BIM. Camposano et al. [ 93 ] state that whereas BIM focuses mostly on the object, DT focuses on representing how people interact with the asset. Given the widespread adoption of BIM, it is recommended that the DT idea be used in conjunction with a range of potential applications that BIM can offer to the building process. Clash detection, visual communication, scheduling, safety management, quality control, cost estimation, construction simulation, and site monitoring are a few possible uses [ 94 ]. A key element that makes many aspects of the building and building sector possible is the digital model. However, overcoming the constraints of BIM's integration capabilities will be necessary to fully utilize these functionalities. As a result, it's necessary to develop more integrated platforms that can seamlessly connect with numerous other systems and operations [ 95 ]. The ultimate goal of digital transformations is to reach the highest level of digital maturity that is humanly possible. But since there isn't a single example of a DT that has realized all of its potential, it's difficult to determine whether a DT has [ 93 ] reached its maximum potential because the concept of DTs isn't fully defined. Furthermore, as the use case is what defines maturity, the asset to which a DT idea is implemented directly affects how mature it has become. There are numerous ways to interpret the term because there isn't a single, widely accepted definition for it. various Concerned parties therefore have various requirements for the kind of connection they require and the data that needs to be sent to them. As a result, it is crucial to ensure that the implementation of DT benefits every stakeholder in the building sector [ 95 ]. The abundance of dynamic data that digital twin technology could handle, its meaning (semantics), and its continuous acquisition of knowledge about the physical world would ultimately constitute its additional values [ 94 ]. Given that a digital twin technology would mimic the real world, this would be the case. Because of the more intelligent and effective construction process and the more capable lifecycle management, this has long-term positive effects on the built environment. Decreases in carbon emissions, lifecycle costs, and asset resilience would all naturally follow from a society that becomes more environmentally conscious [ 94 ]. Because of the possible benefits to industry Concerned parties, the government recognizes the potential advantages of implementing Design Thinking (DT) concepts to modify the built environment. As stated in the Gemini principles, which outline the UK's strategy for using digitalization in the industry, everyone is aware that digital transformation is taking place. The government plans to support the transition in its entirety through a variety of aid programs. 4.6 Smart construction site Digital twin technology may be implemented by site managers to streamline the construction process on the construction site. Radio frequency identification (RFID), augmented reality (AR), the Internet of Things (IoT), virtual reality (VR), and other digital tools can be used to monitor and oversee building site projects [ 79 ]. Using technologies like data mining and process modelling can provide insights on various issues, including material logistics, workflow management, and cost prediction. Unmanned aerial vehicles (UAVs) and other imaging vehicles may be used to compare the construction process with the structural model, allowing for a more precise assessment of the site's progress. A list of potential integrations of blockchain technology into different building stages was published by Kifokeris & Koch [ 96 ]. Studies have indicated that the utilization of digital models facilitates the early identification and mitigation of safety issues and possible hazards in the workplace [ 94 , 97 ]. By anticipating potential risks associated with building stages and machine operations, personnel in construction and machine operators may find value in mixed reality simulation. By using virtual reality (VR) to train on specialized construction activities, such constructing and dismantling tower cranes, the dangers associated with hands-on training are substantially reduced. As per Zhang et al. [ 98 ], the incorporation of hazard-detection algorithms with Building Information Modelling (BIM) enables the accurate identification of fall hazards, hence augmenting building site safety. Moreover, Zhang et al. [ 98 ] stressed that, as not all building components may be fully modelled in the early stages, frequent revisions to the algorithm-generated safety plans are necessary. This suggests that there can be discrepancies between the model's stated assumptions and the actual practice of construction activities, necessitating regular algorithm modifications. Boje et al. [ 94 ] suggested that the digital twin technology model be used to handle comparable issues by connecting sensors to live activities for location tracking and worker monitoring in order to detect and avert potentially unsafe scenarios. A lightweight digital twin technique designed for industries not usually associated with high technology has been developed by Greif et al. [ 99 ]. This digital twin technology is used with several sensors to track parameters including quantity, time intervals, and silo utilization. After data collection, planned silo rotations and limitations on truck transportation are combined. The research is carried out in the framework of a supplier of bulk materials. This composite data is analysed by the digital twin technology using artificial intelligence and other algorithms, enabling a detailed assessment that takes historical and contemporary data into account. Based on this data, it then suggests the best courses of action and determines dividends for each unique client. Consequently, the operators can choose to accept the proposed course of action exactly as it is or modify it. Knowing the position of its equipment and the total fill amount at all times helps the firm become more predictable and efficient. The logistics and success of the construction project may be achieved, according to Kifokeris & Koch's [ 96 ] study, When material, information, and financial flows are smoothly and transparently integrated within supply chains, blockchains are recommended as an appropriate technology to validate these attributes. This is due to the necessity for accuracy and dependability in managing these flows, along with the demands for transparency and accountability, as noted by Boje et al. [ 94 ]. 4.7 Built environment. The conventional understanding of the building, engineering, and architecture sectors has recently changed to include facility management and operation under their purview [ 100 ]. This establishes a connection between key construction building Concerned parties, allowing for a broader perspective of the created environment's life-span and a reconsideration of the workflow across the entire delivery process [ 101 ]. The industry is often referred to as AECO (engineering, construction, architecture, and operation) or AEC/FM (architecture, engineering, construction, and facility management) in studies on digital twin technologies utilized in the existing context [ 102 , 103 ]. Urban Planning's earlier study on digital twin technology [ 104 ] brought attention to this technology in relation to the built environment [ 102 ]. Deng et al. [ 102 ] suggested an evolutionary ladder for the established environment. Building information modelling (BIM) was replaced in the plan with digital twin, which augment BIM with simulation, sensors, and artificial intelligence. A structure's capacity to reach the digital twin technology ladder category makes it easier to engage and communicate with established surroundings. According to Deng et al. [ 102 ], the next generation of digital twin technology is scalable, enabling real-time data sharing between buildings at the level of individual buildings, multi-building communities, and even entire cities [ 2 ]. However, the current corpus of study only addresses a number of impractical aspects and important concepts associated with the digital twin technology of the next generation. Typically, the BIM level is divided into several stages, including the designing, structure, and operating portions [ 105 ]. On the other hand, the sophistication of simulation techniques makes it possible to accurately assess energy performance, which makes it easier to simulate construction processes in the future [ 102 ]. The granular control of energy operations, spatial deployment, and thermal comfort settings are improved by integrating the IoT. This feature facilitates the construction process and allows for the thorough evaluation of risks on both an individual and group level. Artificial intelligence (AI) is used to enhance these monitoring and simulation procedures, providing real-time predictive analytics [ 106 ]. 4.7.1. Buildings The transition from BIM to digital twin technologies for asset, activity, and repair management was described by academics [ 2 , 41 , 102 ]. There are various shortcomings in the asset management process while using BIM. These categories include the degree of coordination between the many technological factors requiring LOD and detailed information, the management component that integrates the flow of work and education, as well as standard-setting that aims to harmonize various processes, technologies, and developmental phases by guaranteeing disciplines [ 106 ]. The digital twin technology is more information-rich and has a greater analytical capacity than BIM [ 107 ]. The digital twin technology also needs to fulfil the requirements for interoperability, intelligence, integration, and efficiency. The level of a digital twin technology that corresponds to the building and infrastructure level is called smart asset management in the construction process, encompassing the procedural and repairing phases [ 108 ]. A number of stages, including designing, building, retrofitting, and maintaining a structure, as well as managerial and quality assurance level reports pertaining to DT technology, are already in existence during the construction process [ 109 ]. A framework for digital twin technology has been defined as scalable from the administrative to the building and societal levels within the framework of a case study of a university campus. The framework consists of several levels, including those addressing data integration and models, transmitting, digital modelling, and data gathering [ 110 ]. It is preferable to take the digital twin technology subset, the neighbourhood, and the city into account while analysing the infrastructure and digital twin technology of a building. This relationship may lead to a better understanding of the social and economic effects as well as chances to enhance city services like transportation and waste collection. The service layer of the dynamic building and city digital twin includes transportation, space deployment, health and safety, electricity, events and failure forecasts, asset and environmental management [ 110 ]. 4.7.2 Cities IoT, it need to do with intelligently managing construction systems, is suggested to be used for a variety of construction scenarios by Yang et al. [ 111 ]. Digital twin are not discussed by them. High energy efficiency is predicted for intelligent buildings, which will contribute to energy conservation, provide smart services to develop a sustainable city, manage energy, and enhance the value of an IoT environment chain. Similar to this, Woodhead et al. [ 112 ] also suggested that an IoT network's primary ecosystem component keeps working long after a building project is customarily completed. Furthermore, Yang et al. [ 113 ] recommend that in order to enhance investment incentives and the advancement of relevant technologies, governments give top priority to the removal of regulatory bottlenecks and the provision of rules, user privacy, and security. According to study by Lehner & Dorffner [ 114 ], DT technology for metropolitan settings can be successfully scaled to benefit both Concerned parties and inhabitants, from specific structures or neighborhoods to entire cities. In the meantime, Deren et al. [ 115 ] support the creation of such city-scale digital twin technology through the convergence of artificial intelligence and human expertise with the goal of improving urban management protocols. In order to achieve the best possible energy use, sustainability objectives, and operational efficiency, this digital twin technology needs to work in harmony with smart city infrastructural frameworks that cover transportation, meteorology, and energy distribution, among other areas. 4.8 Project Delivery A proposal has been made in the industry to implement smart contracts [ 116 ]. A study was carried out in this specific use of blockchain and digital twin technology to safeguard intellectual property rights (IPR) and maintain confidence among different Concerned parties [ 117 ]. This was achieved by proving that the work produced by a subcontract producer's machinery falls within the agreed-upon tolerance levels, hence establishing the final product's quality[ 118 ]. According to their research, any new form of collaboration must first create a predetermined level of confidence. The company that is the owner of the copyright rights is necessary to grant access to confidential data to the organisation performing the contract, and the contracting company is obliged to furnish details regarding the functioning of their manufacturing processes [ 99 ]. By providing accessibility for all Concerned parties regarding the advancements being made through the use of machines and the use of block-chain technology to confirm the proper usage of information, trust can be established and maintained across various businesses, according to Nielsen et al. [ 116 , 119 ]. Furthermore, they contend that the trust does away with the requirement for attorneys to examine and approve contracts. A blockchain-related framework is proposed and verified by Rawat et al. [ 120 ] to facilitate the project's integrated delivery. They also provide an explanation of the growing body of research on smart contracts in the building sector [121This is done, in part, to ensure that the results of the study conducted by Nielsen et al. [ 116 ] are reflected. As a result, trust is established and maintained among clients, vendors, and subcontractors, enabling milestone payments to be legitimately linked to actual work completed on the project. Dounas et al.'s study [ 122 ] examines how blockchain technology and BIM interact, describing how both technologies authenticate and document how building designs change and evolve during construction. Similarly, research conducted in the sector of building by Kifokeris & Koch (2020) emphasizes the function of blockchain in facilitating smart contracts. They do point out that there aren't many instances of this technology being used successfully. The significant danger of information attrition is highlighted by Mahmoodian et al. [ 123 ] at different points in a construction project, especially while moving from the building phase to the operating phase. Waqar et al. [ 124 ] contribute to this discussion by offering a timetable that outlines the procedures for information linking between several models, resulting in an operational BIM that gathers the necessary information. It is agreed upon by Tchana et al. [ 22 ] that different models need to talk to one other. To safeguard traceable decisions and the model record, they advise, however, linking the used models using digital twin technology (Zhang et al., 2022). We'll take this action to guard against data loss or overwriting. The actual value of digital twin technology utility technologies only becomes evident when employed from the production stage to asset management, according to a study by Love & Matthews [ 15 ]. The adoption of digital technology by asset owners and organizations is recommended by Love et al. [ 125 ]. In order to enable real-time operations and maintenance procedures and provide a more successful and efficient turnover of the asset, asset owners may specify at handover that a digital twin technology be used (Wu et al., 2022). It is better to adopt digital technologies out of need and desire than to be pressured or inundated with the newest technology [ 126 ]. The advantages of practice and lifecycle implementation amplify the automation, extension, and transformational changes that result from the installation of digital technology. Before starting to build a structure, a number of different players look into the required parts [ 127 ]. When it comes to planning the municipality's internal expansion as well as the future development of real estate enterprises. In order to make sure the proposed project complies with municipal standards, this stage of the process may automatically compare the design digital twin technology with current development plans very early in support of construction [ 128 ]. Upon completion of the model, the project can proceed to the next phase, which involves obtaining a building permit [ 129 ]. In both the planning and building phases, the initial design is altered to function as a model for the completed project. Creating a link between the building and the neighbourhood around it guarantees smooth logistics. It enables the pursuit of automatic maintenance of the building based on events that occur close to its location in the future and the structural progress that is being made [ 130 , 131 ]. If data is organized then that all parties can easily see it, there will be less conflict at the construction site and in other ongoing neighbourhood activities [ 132 ]. A final inspection is carried out during the project delivery phase to guarantee that the building meets all specifications and expectations. As of right now, the building functions as an integrated digital twin that is operationally visually connected to the city (Li et al., 2021). Through the use of secure authentication procedures and blockchain technology, Concerned parties at various levels are able to access generated data from the building as well as contextual information. The development of complex sensor systems is inextricably linked to advances in technology and system architecture. These cutting-edge systems, which have robotics, GPS, and cellular networking capabilities, make it easier to collect data in difficult and complex locations by using advanced miniaturization and integration techniques (Wu et al., 2022). Implementing AI-enhanced functions, such as machine learning (ML), computer vision (CV), and optimization algorithms, significantly improves process efficiency and results in better analysis and solutions (Zhang et al., 2022). Moreover, by adding additional project issues inside the same platform, multi-function and integrated Digital Twin Technology (DT) systems aim to enhance operational performance. This includes environmental monitoring, safety management, and building evacuation [ 133 ]. DT systems operate more functionally when their deployment is broader, providing industrial relevance and fully addressing pain points [ 134 ]. In order to support a sizable administrative system and urban planning, city-scale DT systems move the emphasis from building-oriented solutions to virtual cities' mapping and management. The circular economy is still essential to contemporary building methods because of its dedication to sustainability [ 131 ]. Throughout a building's full existence, which includes construction, operation, and eventual decommissioning, it aspires to resource conservation, emission reduction, and efficient waste management. Lean principles incorporated into prefabricated manufacturing frameworks reduce their impact on the environment and increase efficiency [ 132 ]. When subjected to temporal analysis, digital twin (DT) technology can enhance scheduling, reduce interruptions, and limit delay risks—all of which have the potential to completely transform project management. Thorough economic assessments ensure the financial viability of the selected firm model (Li et al., 2021). Moreover, the resilience and robustness of building endeavours are improved by combining DT systems with other cutting-edge techniques that come from earlier research on complicated environmental route planning and Building Information Modelling (BIM)-enabled detecting tools [ 130 ]. This multifaceted strategy signals a model shift in the building industry by opening the door to the augmentation of DT functions. The benefits of applying digital twin technology are categorized along six major dimensions, as shown in Table 6 : Method, Milieu, Measurement, Material, Machine, and Manpower. According to Table 6 represents, all tangible assets related to machinery and equipment utilized in the building sector, like trucks and cranes, are included in the machine aspect. It is now standard procedure for high-value assets to adopt Digital Transformation (DT) technologies in order to increase efficiency and reduce malfunctions during the course of their operational life. Conversely, the human workforce—which performs a variety of tasks during the construction phase, from machine operators to designers—is known as the "manpower" component. A new study mostly concentrates on the on-site building stage, despite the quick acceptance of digital twins in the building process. Even while material performance and tracking—which includes raw materials and intermediate products like precast models—have made significant strides, more research and development can still be done. The measuring element effectively transforms drawing information into precise descriptions and amounts, which is highly helpful in evaluating the value, cost, and price of building work. In order to ensure speed, dependability, and sustainability in the creation of infrastructure in a digitalized society, this procedure is essential. Table 6 Benefits of digital twin technology applications categorized by construction lifecycle stages. Applications categorised Lifecycle Stage Construction Function DT-Enabled Benefits Methods Design & engineering Operations and maintenance Construction logistics Quality evaluation Sustainability enhancement Safety management -Enhance the way that safety is managed on building sites by assessing hazards, employing preventative risk management techniques, and analysing risk variables. - Enable blockchain for traceability, incorporate the intelligent product-service architecture, and facilitate data synchronization[ 99 , 117 , 119 ]. Milieu Operations & maintenance Monitoring construction sites Keeping an eye on building occupancy Managing indoor environments Developing smart cities. - Enhance safety oversight on building sites through threat assessment, proactive risk management, and risk factor analysis. - Boost digitization of construction by automating the detection and tracking of site and assembly progress. - Simplified public explanation of policy, urban planning, and administrative operations through digital prototype analysis and visualization.[ 129 , 135 , 136 ] Measurement Operations & maintenance Tracking greenhouse gas emissions monitoring construction sites; monitoring structural health. - Provide future models for the continuous and real-time use of SHM, including failure prevention, structural damage detection, safety assessment, and support for maintenance work. The ability to create energy saving and emission-reduction plans is enhanced by real-time GHG emissions monitoring[ 118 , 121 , 123 ]. Material Operations & maintenance Decommissioning Design and engineering Tracking material information Recycling and reuse Reliability and reaction tracking Optimizing the structure design - By offering more accurate models, the design validation of the 3D-printed modules is supported. - Boost building material traceability and radiological detection. - Direct material flows toward a sustainable material flow by using quantitative analysis.[ 126 , 128 ] Machine Operations & maintenance Management of assets and safety Automated assembly of robots Control of intelligent equipment - Use concurrent perception modeling to improve robotic building and generative design; - Strengthen the security mechanism for the digital triplet's more confident object detection. enhances context observation for the purpose of applying robot control strategy[ 130 , 132 , 137 ]. Manpower On-site construction Training for workers Safety of workers - Use a virtual practice platform to lower training risk and enhance learning outcomes for professionals in the building sector. - Synchronize data to handle risks in complex and dynamic circumstances[ 133 , 134 , 138 ]. For operations to run well, data about actual objects and target environments must be gathered and monitored. The milieu component provides information about the physical environment in which building activities take place by taking into account ambient data, terrain type, and surrounding layout. As shown by Jiaying Zhang et al. [ 136 ], combining DT with the degree of detail extension in Building Information Modelling (BIM) provides a strong framework for efficient on-site building site monitoring and management. The Method aspect includes efforts to increase building and construction efficiency. When planning and engineering structures, planners and architects can reduce their environmental impact by using a realistic strategy called building form optimization. As a result, the incorporation of technologies is causing a considerable transformation in the building sector. In order to fully realize its potential, scholars and professionals in the industry need to broaden their scope beyond the on-site phase, investigate novel approaches for material performance, and enhance building procedures. In the digital age, building better, faster, and more sustainable infrastructures can be achieved by revolutionizing the construction sector by fusing human experience with state-of-the-art technologies. 5. Conclusion A digital twin is a technique that exists only in the digital realm and is the virtual equivalent of a physical object. This could apply to everything from small-scale buildings and infrastructure to large-scale systems like cities, countries, or even the entire planet in the context of the construction business. A digital model must coexist with its physical counterpart throughout its existence in order to be considered a twin. This suggests that the idea of a new physical structure is inextricably related to the development of digital twin technologies. Moreover, the development of digital and physical things occurs simultaneously, mirroring the functional functions of each. It is not necessary for digital twin technology to replicate every aspect of its physical counterpart, though. Rather, the two organizations need to have characteristics in common that support the built environment's sustainability. These characteristics could include improvements in the building sector's efficiency and project completion. The tolerance of the digital twin should be used to help building projects not just from the beginning of design to the end. It can be linked to the digital twin technology of the city from a very early the ecosystem of digital twin, the design process is maintained during the building's construction and operation. In the early stages, the building's digital twin technology is linked to the city's digital twin technology in terms of urban planning and the associated procurement processes. The scalable city digital twin technology can be integrated with the site logistics, such as the work environment and transit schedules, during the construction phase. If this happened, the place would be more like the smart manufacturing factories. Furthermore, the structure's digital twin technology may interact with the city's to manage expected health and energy usage. In addition to an abundance of newly created technologies, the digital world also encompasses a new style of doing business and a unique way of thinking. the notion of working together for the good of all people and future generations. The results showed that DT might serve as the basis for a data-driven lifecycle that gathers ever-growing volumes of data, information and, in the end, helps make well-informed decisions. Procedures that make it possible to gather important and influential data should therefore be given top importance. The ability of DTs to cover a building's whole lifecycle makes circular construction viable. DTs are distinct from other technologies and more traditional BIM models because of their data-driven methodology. Additionally, it can create new business models based on the capabilities of the DT platform, particularly during the O&M stage. Due to its unique benefits that may be provided to clients and customers through its digital platform and data capacity, DTs offer a compelling value proposition. The extent to which DTs can help with the shift to Construction 4.0 was also looked into in this structure. According to the study, DT can help bring about this transformation. With reference to the SiX Keys to Success Framework, this conclusion is proved [139]. Nonetheless, the interviews revealed that this change will not happen suddenly. When it comes to the construction business, the DT concept is still in its early stages, thus it's possible that the sector will never reach its full potential. Despite this, the goal posts for the DT concept will never be achieved, even though strengthening system integration and progressively enhancing DT capabilities may be the best way to advance. For DT to realize its full potential, all of the industry's Concerned parties must support standardization of tools and procedures as well as data-sharing. As a result, there is less fragmentation in the building business since anybody can access and contribute information to a single platform. This paper elaborates on the critical role that data plays in the Digital Twin Technology (DTs) model, serving as a catalyst and an enabler in equal measure. However, data interchange appears to be a critical factor that needs more research in order to successfully implement DTs. When several Concerned parties are willing to share data, data-centric components inside DTs can never reach their full potential. At the same time, ethical issues including dangers to personal privacy need to be carefully examined because DTs involve a lot of data sharing. Furthermore, when sharing data between different projects with diverse DT models, the question of data ownership becomes even more important. Future research projects might use qualitative or quantitative approaches in addition to case studies to measure the prevalence of data-sharing practices and gauge Concerned parties' preparedness for data exchange. This would help us better understand these complexities. Declarations Author Contribution Dr. Pragya wrote the main manuscript text and Dr. Chandrashekhar prepared figures. Dr. Linesh Collected the data and henerated the results and Dr. Avichandra reviewed the manuscript. References Sepasgozar SME (2021) Differentiating digital twin from digital shadow: Elucidating a paradigm shift to expedite a smart, sustainable built environment. Buildings 11(4):151 Hotový M (2018) Dynamic model of implementation efficiency of Building Information Modelling (BIM) in relation to the complexity of buildings and the level of their safety, MATEC Web of Conferences 146 1010 García de Soto B, Agustí-Juan I, Joss S, Hunhevicz J (2022) Implications of Construction 4.0 to the workforce and organizational structures. Int J Constr Manage 22(2):205–217 Osunsanmi TO, Aigbavboa CO, Emmanuel Oke A, Liphadzi M (2020) Appraisal of stakeholders’ willingness to adopt construction 4.0 technologies for construction projects. Built Environ Proj Asset Manag 10(4):547–565 Starr CW, Saginor J, Worzala E (2020) The rise of PropTech: emerging industrial technologies and their impact on real estate. J Property Invest Finance 39(2):157–169 Lo¨o¨w J, Abrahamsson L, Johansson J (2019) Mining 4.0—the impact of new technology from a work place perspective. Min Metall Explor 36:701–707 Ramirez-Mendoza RA, Morales-Menendez R, Iqbal H, Parra-Saldivar R (2018) Engineering education 4.0:—proposal for a new Curricula. IEEE Global Engineering Education Conference (EDUCON), 2018, pp. 1273–1282 Aheleroff S, Zhong RY, Xu X, Feng Z, Goyal P (2020) Digital Twin enabled mass personalization: a case study of a smart wetland maintenance system, in: International Manufacturing Science and Engineering Conference, vol. 84263, V002T07A025 Caiado RGG, Scavarda LF, de Nascimento DL, Ivson P, Cunha VHC (2020) A maturity model for manufacturing 4.0 in emerging countries. Operations Management for Social Good: 2018 POMS International Conference in Rio, pp. 393–402 Zhang X, Xu YY, Ma L (2023) Information technology investment and digital transformation: the roles of digital transformation strategy and top management. Bus Process Manag J 29(2):528–549 Kor M, Yitmen I, Alizadehsalehi S (2023) An investigation for integration of deep learning and digital twins towards Construction 4.0. Smart Sustainable Built Environ 12(3):461–487 Hu W, Lim KYH, Cai Y (2022) Digital twin and industry 4.0 enablers in building and construction: a Survey, Buildings 12 (11) 2004 Columbus L, McKinsey’s state of machine learning and AI, Forbes F (2017) Com/Sites/Louiscolumbus/2017/07/09/Mckinseys-State-of-Machine- Learning-and-Ai-2017. (Accessed 17 December 2020) Love PED, Matthews J (2019) The ‘how’of benefits management for digital technology: from engineering to asset management. Autom ConStruct 107:102930 Gunderson R (2016) The sociology of technology before the turn to technology. Technol Soc 47:40–48 Orlikowski WJ (2008) Scott, 10 sociomateriality: challenging the separation of technology, work and organization. Acad Manag Ann 2(1):433–474 Teisserenc B, Sepasgozar S (2021) Adoption of blockchain technology through digital twins in the construction industry 4.0: a PESTELS approach. Buildings 11(12):670 Boje C, Kubicki S, Guerriero A (2021) A 4D BIM system architecture for the semantic web. Proceedings of the 18th International Conference on Computing in Civil and Building Engineering: ICCCBE 2020, pp. 561–573 Lim WM, Yap S-F, Makkar M (2021) Home sharing in marketing and tourism at a tipping point: what do we know, how do we know, and where should we be heading? J Bus Res 122:534–566 Negri E, Fumagalli L, Macchi M (2017) A review of the roles of digital twin in CPS- based production systems. Procedia Manuf 11:939–948 Tchana Y, Ducellier G, Remy S (2019) Designing a unique Digital Twin for linear infrastructures lifecycle management. Procedia CIRP 84:545–549 Ketzler B, Naserentin V, Latino F, Zangelidis C, Thuvander L, Logg A (2020) Digital twins for cities: a state of the art review. Built Environ 46(4):547–573 Saieg P, Sotelino ED, Nascimento D, Caiado RGG (2018) Interactions of building information modeling, lean and sustainability on the architectural, engineering and construction industry: a systematic review. J Clean Prod 174:788–806 Li S, Fang Y, Wu X (2020) A systematic review of lean construction in Mainland China. J Clean Prod 257:120581 Jesson J, Matheson L, Lacey FM (2011) Doing Your Literature Review: Traditional and Systematic Techniques Taofeeq D, Moshood G, Nawanir S, Sorooshian O, Okfalisa (2021) Digital twins driven supply chain Visibility within logistics: a new paradigm for future logistics. Appl Syst Innov 4(2). https://doi.org/10.3390/asi4020029 Moshood TD, Nawanir G, Mahmud F, Ajibike WA (2021) Sustainable system for supply chain management in the Malaysian manufacturing industries: a review and research direction. Int J Supply Chain Oper Resil 5(1):79–98 Taofeeq D, Moshood G, Nawanir S, Sorooshian F, Mahmud AQ, Adeleke (2020) Barriers and benefits of ICT adoption in the Nigerian construction industry. A comprehensive literature review. Appl Syst Innov 3(4):46 Taofeeq D, Moshood FE, Rotimi JOB, Rotimi (2022) An integrated paradigm for managing efficient knowledge transfer: towards a more comprehensive philosophy of Transferring knowledge in the construction industry. Constr Econ Building 22(3):65–98. https://doi.org/10.5130/AJCEB. v22i3.8050 Moshood TD, Rotimi FE, Rotimi JOB (2022) Knowledge transfer and management in the construction industry: trends and future challenges. Int J Constr Supply Chain Manage 12(1):72–102. https://doi.org/10.14424/ijcscm120122-72-102 Popkova EG, Zmiyak KV (2019) Priorities of training of digital personnel for industry 4.0: social competencies vs technical competencies. Horizon 27(3/4):138–144 Khan M, Wu X, Xu X, Dou W (2017) Big data challenges and opportunities in the hype of Industry 4.0, in: IEEE International Conference on Communications (ICC), 2017, pp. 1–6 Bonnet D, Westerman G (2020) The new elements of digital transformation. MIT Sloan Manag Rev 62 (2) Qi Q, Tao F, Hu T, Anwer N, Liu A, Wei Y, Wang L, Nee AYC (2021) Enabling technologies and tools for digital twin. J Manuf Syst 58:3–21 Sawhney A, Riley M, Irizarry J, Riley M (2020) in: A. Sawhney, M. Riley, J. Irizarry (Eds.), Construction 4.0 Jazzar ME, Schranz C, Urban H, Nassereddine H (2021) Integrating construction 4.0 technologies: a four-layer implementation plan. Front Built Environ 144 Rao SS (2019) Engineering Optimization: Theory and Practice. Wiley Wang X, Liang C-J, Menassa CC, Kamat VR (2021) Interactive and immersive process-level digital twin for collaborative human–robot construction work. J Comput Civ Eng 35(6):4021023 Yitmen I, Kovacic I, Tagliabue LC (2023) Cognitive digital twins for facilitating construction 4.0: challenges and opportunities for implementation. Front Built Environ 9:1130115 Lu Q, Chen L, Li S, Pitt M (2020) Semi-automatic geometric digital twinning for existing buildings based on images and CAD drawings. Autom ConStruct 115:103183 Nunberg G The Advent of the Internet, 2012. 12th April, Courses Madakam S, Lake V, Lake V, Lake V (2015) Internet of things (IoT): a literature review. J Comput Commun 3(5):164 Bilal M, Oyedele LO, Qadir J, Munir K, Ajayi SO, Akinade OO, Owolabi HA, Alaka HA, Pasha M (2016) Big Data in the construction industry: a review of present status, opportunities, and future trends. Adv Eng Inf 30(3):500–521 Sagiroglu S, Sinanc D (2013) Big data: a review. International Conference on Collaboration Technologies and Systems (CTS), 2013, pp. 42–47 Eadie R, Browne M, Odeyinka H, McKeown C, McNiff S (2013) BIM implementation throughout the UK construction project lifecycle: an analysis. Autom ConStruct 36:145–151 Aleksandrova E, Vinogradova V, Tokunova G (2019) Integration of digital technologies in the field of construction in the Russian Federation. Eng Manage Prod Serv 11(3):38–47 Mateev M (2020) Industry 4.0 and the digital twin for building industry. Ind 4 0 5(1):29–32 Wu H, Zhu Q, Guo Y, Zheng W, Zhang L, Wang Q, Zhou R, Ding Y, Wang W, Pirasteh S (2022) Multi-level voxel representations for digital twin models of tunnel geological environment. Int J Appl Earth Obs Geoinf 112:102887 Yitmen I, Alizadehsalehi S, Akıner I˙, Akıner ME (2021) An adapted model of cognitive digital twins for building lifecycle management. Appl Sci 11(9):4276 Desogus G, Quaquero E, Rubiu G, Gatto G, Perra C (2021) Bim and iot sensors integration: a framework for consumption and indoor conditions data monitoring of existing buildings. Sustainability 13(8):4496 Klinc R, Turk Zˇ (2019) Construction 4.0–digital transformation of one of the oldest industries. Econ Bus Rev 21(3):4 Torrecilla-García JA, Pardo-Ferreira MC, Rubio-Romero JC (2022) Aproximacio´n inicial al enfoque basado en BIM-based Digital Twinning en la toma de decisiones sobre Seguridad y Salud Laboral en la industria de la construccio´n. Direccio´n y Organizacio´n 76:5–12 Funari MF, Hajjat AE, Masciotta MG, Oliveira DV, Lourenço PB (2021) A parametric scan-to-FEM framework for the digital twin generation of historic masonry structures. Sustainability 13(19):11088 Münzinger M, Prechtel N, Behnisch M (2022) Mapping the urban forest in detail: from LiDAR point clouds to 3D tree models, Urban For. Urban Green 74:127637 Lee D, Lee SH, Masoud N, Krishnan MS, Li VC (2021) Integrated digital twin and blockchain framework to support accountable information sharing in construction projects. Autom ConStruct 127:103688 Orlikowski WJ, Scott SV (2008) The Entanglement of Technology and Work in Organizations Peine A (2008) Technological paradigms and complex technical systems the case of smart homes. Res Pol 37(3):508–529 Cantwell J, Hayashi T (2019) Paradigm Shift in Technologies and Innovation Systems. Springer Ayinla KO, Adamu Z (2018) Bridging the digital divide gap in BIM technology adoption. Eng Construct Architect Manag 25(10):1398–1416 Bosch-Sijtsema P, Isaksson A, Lennartsson M, Linderoth HCJ (2017) Barriers and facilitators for BIM use among Swedish medium-sized contractors-We wait until someone tells us to use it. Visualization Eng 5:1–12 Dainty A, Leiringer R, Fernie S, Harty C (2017) BIM and the small construction firm: a critical perspective. Build Res Inf 45(6):696–709 Davies R, Harty C (2013) Implementing ‘Site BIM’: a case study of ICT innovation on a large hospital project. Autom ConStruct 30:15–24 Lei Y, Rao Y, Wu J, Lin C-H (2020) BIM based cyber-physical systems for intelligent disaster prevention. J Industrial Inform Integr 20:100171 Taraben J, Morgenthal G (2021) Methods for the automated assignment and comparison of building damage geometries. Adv Eng Inf 47:101186 Kyvelou P, Buchanan C, Gardner L (2022) Numerical simulation and evaluation of the world’s first metal additively manufactured bridge. Structures 42:405–416 Lydon GP, Caranovic S, Hischier I, Schlueter A (2019) Coupled simulation of thermally active building systems to support a digital twin. Energy Build 202:109298 Bosch-Rekveldt M, Bakker H, Hertogh M (2018) Comparing project complexity across different industry sectors, Complexity (2018) Xue F, Lu W, Chen Z, Webster CJ (2020) From LiDAR point cloud towards digital twin city: Clustering city objects based on Gestalt principles. ISPRS J Photogrammetry Remote Sens 167:418–431 Zhuang C, Liu J, Xiong H (2018) Digital twin-based smart production management and control framework for the complex product assembly shop-floor. Int J Adv Des Manuf Technol 96:1149–1163 Grieves M, Vickers J (2017) Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. Transdisciplinary Perspectives on Complex Systems. Springer, pp 85–113 Glaessgen E, Stargel D (2012) The digital twin paradigm for future NASA and US Air Force vehicles, in: 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA, vol. 1818 Schroeder GN, Steinmetz C, Pereira CE, Espindola DB (2016) Digital twin data modeling with automationml and a communication methodology for data exchange. IFAC-PapersOnLine 49(30):12–17 Leng J, Zhou M, Xiao Y, Zhang H, Liu Q, Shen W, Su Q, Li L (2021) Digital twins- based remote semi-physical commissioning of flow-type smart manufacturing systems. J Clean Prod 306:127278 Nochta T, Wan L, Schooling JM, Parlikad AK (2021) A socio-technical perspective on urban analytics: the case of city-scale digital twins. J Urban Technol 28(1–2):263–287 You Z, Feng L (2020) Integration of industry 4.0 related technologies in construction industry: a framework of cyber-physical system, IEEE Access 8 122908–122922 Al-Saeed Y, Edwards DJ, Scaysbrook S (2020) Automating construction manufacturing procedures using BIM digital objects (BDOs) Case study of knowledge transfer partnership project in UK. Construct Innovat 20(3):345–377 Huang L, Pradhan R, Dutta S, Cai Y (2022) BIM4D-based scheduling for assembling and lifting in precast-enabled construction. Autom ConStruct 133:103999 Pan Y, Zhang L (2021) A BIM-data mining integrated digital twin framework for advanced project management. Autom ConStruct 124:103564 Schmidt M, Moreno MV, Schülke A, Macek K, Maˇrík K, Pastor AG (2017) Optimizing legacy building operation: the evolution into data-driven predictive cyber-physical systems. Energy Build 148:257–279 Li CZ, Chen Z, Xue F, Kong XTR, Xiao B, Lai X, Zhao Y (2021) A blockchain-and IoT-based smart product-service system for the sustainability of prefabricated housing construction. J Clean Prod 286:125391 Zhang Y, Yuen K-V (2022) Applications of deep learning in intelligent construction. Struct Health Monit Based Data Sci Techniques 227–245 Saini GS, Pournazari P, Ashok P, van Oort E (2022) Intelligent action planning for well construction operations demonstrated for hole Cleaning optimization and automation. Energies 15(15):5749 Gichane MM, Byiringiro JB, Chesang AK, Nyaga PM, Langat RK, Smajic H, Kiiru CW (2020) Digital triplet approach for real-time monitoring and control of an elevator security system. Designs 4(2):9 Shim C-S, Dang N-S, Lon S, Jeon C-H (2019) Development of a bridge maintenance system for prestressed concrete bridges using 3D digital twin model. Struct Infrastruct Eng 15(10):1319–1332 Zonzini F, Aguzzi C, Gigli L, Sciullo L, Testoni N, De Marchi L, Di Felice M, Cinotti TS, Mennuti C, Marzani A (2020) Structural health monitoring and prognostic of industrial plants and civil structures: a sensor to cloud architecture. IEEE Instrum Meas Mag 23(9):21–27 Liu Z, Zhang A, Wang W (2020) A framework for an indoor safety management system based on digital twin. Sensors 20(20):5771 Grübel J, Thrash T, Aguilar L, Gath-Morad M, He´lal D, Sumner RW, Ho¨lscher C, Schinazi VR (2022) Dense Indoor Sensor Networks: towards passively sensing human presence with LORAWAN. Pervasive Mob Comput 84:101640 Yang L, Fu C, Li Y, Su L (2019) Survey and study on intelligent monitoring and health management for large civil structure. Int J Intell Rob Appl 3:239–254 Zˇ. Turk R, Klinc (2020) A social–product–process framework for construction. Build Res Inf 48(7):747–762 Linderoth HCJ (2010) Understanding adoption and use of BIM as the creation of actor networks. Autom ConStruct 19(1):66–72 Petrova-Antonova D, Spasov A (2021) Towards a semantic 3D model of Sofia city, in: Computational Science and its Applications–ICCSA 2021: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part IV, vol. 21, pp. 230–241 Camposano JC, Smolander K, Ruippo T (2021) Seven metaphors to understand digital twins of built assets. IEEE Access 9:27167–27181 Boje C, Guerriero A, Kubicki S, Rezgui Y (2020) Towards a semantic construction digital twin: directions for future research. Autom ConStruct 114:103179 Ozturk GB (2021) Digital twin research in the AECO-FM industry. J Build Eng 40:102730 Kifokeris D, Koch C (2020) A conceptual digital business model for construction logistics consultants, featuring a sociomaterial blockchain solution for integrated economic, material and information flows. J Inf Technol Constr 25(29):500–521 Nnaji C, Karakhan AA (2020) Technologies for safety and health management in construction: current use, implementation benefits and limitations, and adoption barriers. J Build Eng 29:101212 Zhang S, Sulankivi K, Kiviniemi M, Romo I, Eastman CM, Teizer J (2015) BIM-based fall hazard identification and prevention in construction safety planning. Saf Sci 72:31–45 Greif T, Stein N, Flath CM (2020) Peeking into the void: digital twins for construction site logistics. Comput Ind 121:103264 Yitmen I, Alizadehsalehi S (2021) Towards a digital twin-based smart built environment, BIM-Enabled Cognitive Computing for Smart Built Environment 21–44 Shahzad M, Shafiq MT, Douglas D, Kassem M (2022) Digital twins in built environments: an investigation of the characteristics, applications, and challenges. Buildings 12(2):120 Deng M, Menassa CC, Kamat VR (2021) From BIM to digital twins: a systematic review of the evolution of intelligent building representations in the AEC-FM industry. J Inf Technol Construct 26 Xu J, Lu W, Anumba CJ, Niu Y (2020) From smart construction objects to cognitive facility Management. Cyber-Physical Syst Built Environ 273–296 Lehtola VV, Koeva M, Elberink SO, Raposo P, Virtanen J-P, Vahdatikhaki F, Borsci S (2022) Digital twin of a city: review of technology serving city needs. Int J Appl Earth Obs Geoinf 102915 Delgado JMD, Oyedele L (2021) Digital Twins for the built environment: learning from conceptual and process models in manufacturing. Adv Eng Inf 49:101332 Wang T, Gan VJL, Hu D, Liu H (2022) Digital twin-enabled built environment sensing and monitoring through semantic enrichment of BIM with SensorML. Autom ConStruct 144:104625 Wahbeh W, Kunz D, Hofmann J, Bereuter P (2020) Digital twinning of the built environment–an interdisciplinary topic for innovation in didactics, ISPRS Annals of the Photogrammetry. Remote Sens Spat Inform Sci 4:231–237 Sommer M, Stjepandi´c J, Stobrawa S, von Soden M (2023) Automated generation of digital twin for a built environment using scan and object detection as input for production planning. J Industrial Inform Integr 33:100462 Petri I, Rezgui Y, Ghoroghi A, Alzahrani A (2023) Digital twins for performance management in the built environment. J Industrial Inform Integr 33:100445 Kaewunruen S, Xu N (2018) Digital twin for sustainability evaluation of railway station buildings. Front Built Environ 4:77 Yang C-H, Lee K-C, Li S-E (2020) A mixed activity-based costing and resource constraint optimal decision model for IoT-oriented intelligent building management system portfolios, Sustain. Cities Soc 60:102142 Woodhead R, Stephenson P, Morrey D (2018) Digital construction: from point solutions to IoT ecosystem. Autom ConStruct 93:35–46 Yang Z, Hao C, Shao S, Chen Z, Yang L (2022) Appropriate technology and energy security: from the perspective of biased technological change. Technol Forecast Soc Change 177:121530 Lehner H, Dorffner L (2020) Digital geoTwin Vienna: towards a Digital Twin City as Geodata Hub, Springer Deren L, Wenbo Y, Zhenfeng S (2021) Smart city based on digital twins. Comput Urban Sci 1:1–11 Nielsen CP, da Silva ER, Yu F (2020) Digital twins and blockchain–proof of concept. Procedia Cirp 93:251–255 Jiang W, Ding L, Zhou C (2021) Cyber physical system for safety management in smart construction site. Eng Construct Architect Manag 28(3):788–808 Hao JL, Cheng B, Lu W, Xu J, Wang J, Bu W, Guo Z (2020) Carbon emission reduction in prefabrication construction during materialization stage: a BIM- based life-cycle assessment approach. Sci Total Environ 723:137870 Liu Z, Meng X, Xing Z, Jiang A (2021) Digital twin-based safety risk coupling of prefabricated building hoisting. Sensors 21(11):3583 RawatD B, Chaudhary V, Doku R (2020) Blockchain technology: emerging applications and use cases for secure and trustworthy smart systems. J Cybersecur Priv 1(1):4–18 Chiachío M, Megía M, Chiachío J, Fernandez J, Jalo´n ML (2022) Structural digital twin framework: Formulation and technology integration. Autom ConStruct 140:104333 Dounas T, Lombardi D, Jabi W (2021) Framework for decentralised architectural design BIM and Blockchain integration. Int J Architect Comput 19(2):157–173 Mahmoodian M, Shahrivar F, Setunge S, Mazaheri S (2022) Development of digital twin for intelligent maintenance of civil infrastructure. Sustainability 14(14):8664 Waqar A, Qureshi AH, Alaloul WS (2023) Barriers to Building Information Modeling (BIM) deployment in small construction projects: Malaysian construction industry. Sustainability 15(3):2477 Love PED, Matthews J, Zhou J (2020) Is it just too good to be true? Unearthing the benefits of disruptive technology. Int J Inf Manag 52:102096 Orozco-Messana J, Lopez-Mateu V, Pellicer TM (2022) City Regeneration through modular phase change materials (PCM) Envelopes for Climate Neutral buildings. Sustainability 14(14):8902 Meˇza S, Mauko Pranji´c A, Vezoˇcnik R, Osmokrovi´c I, Lenart S (2021) Digital twins and road construction using secondary raw materials, J. Adv. Transport. (2021) 1–12 He R, Li M, Gan VJL, Ma J (2021) BIM-enabled computerized design and digital fabrication of industrialized buildings: a case study. J Clean Prod 278:123505 Schrotter G, Hürzeler C (2020) The digital twin of the city of Zurich for urban planning. PFG–Journal Photogrammetry Remote Sens Geoinf Sci 88(1):99–112 Lee D, Lee S, Masoud N, Krishnan MS, Li VC (2022) Digital twin-driven deep reinforcement learning for adaptive task allocation in robotic construction. Adv Eng Inf 53:101710 Zhang J, Luo H, Xu J (2022) Towards fully BIM-enabled building automation and robotics: a perspective of lifecycle information flow. Comput Ind 135:103570 Kan C, Fang Y, Anumba CJ, Messner JI (2018) A cyber–physical system (CPS) for planning and monitoring mobile cranes on construction sites, Proceedings of the Institution of Civil Engineers-Management, Procurement and Law 171 (6) 240–250 Sepasgozar SME (2020) Digital twin and web-based virtual gaming technologies for online education: a case of construction management and engineering. Appl Sci 10(13):4678 Akanmu AA, Olayiwola J, Ogunseiju O, McFeeters D (2020) Cyber-physical postural training system for construction workers. Autom ConStruct 117:103272 Wu J, Wang X, Dang Y, Lv Z (2022) Digital twins and artificial intelligence in transportation infrastructure: classification, application, and future research directions. Comput Electr Eng 101:107983 Zhang J, Cheng JCP, Chen W, Chen K (2022) Digital twins for construction sites: concepts, LoD definition, and applications. J Manag Eng 38(2):4021094 Li M, Lu Q, Bai S, Zhang M, Tian H, Qin L (2021) Digital twin-driven virtual sensor approach for safe construction operations of trailing suction hopper dredger. Autom ConStruct 132:103961 Wu S, Hou L, Zhang GK, Chen H (2022) Real-time mixed reality-based visual warning for construction workforce safety. Autom ConStruct 139:104252 Kavadias S, Ladas K, Loch C (2016) The transformative business model. Harv Bus Rev 94(10):91–98 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9039690","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":639597864,"identity":"86099d76-a9ad-4b6e-a6ba-2c268722185b","order_by":0,"name":"Pragya Vaishnav","email":"","orcid":"","institution":"Manipal University Jaipur Jaipur","correspondingAuthor":false,"prefix":"","firstName":"Pragya","middleName":"","lastName":"Vaishnav","suffix":""},{"id":639597865,"identity":"0bea5192-5a8a-4855-b769-138259c38887","order_by":1,"name":"Chandrashekhar Patel","email":"","orcid":"","institution":"Manipal University Jaipur Jaipur","correspondingAuthor":false,"prefix":"","firstName":"Chandrashekhar","middleName":"","lastName":"Patel","suffix":""},{"id":639597869,"identity":"298830fa-466a-4f7c-b201-9445b5dac5b3","order_by":2,"name":"Linesh Raja","email":"data:image/png;base64,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","orcid":"","institution":"Manipal University Jaipur Jaipur","correspondingAuthor":true,"prefix":"","firstName":"Linesh","middleName":"","lastName":"Raja","suffix":""},{"id":639597872,"identity":"23b3594a-916e-4583-8041-0222b6d7f860","order_by":3,"name":"Ningthoujam Avichandra Singh","email":"","orcid":"","institution":"Manipal University Jaipur Jaipur","correspondingAuthor":false,"prefix":"","firstName":"Ningthoujam","middleName":"Avichandra","lastName":"Singh","suffix":""}],"badges":[],"createdAt":"2026-03-05 11:54:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9039690/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9039690/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109282048,"identity":"44c3a81d-4d1c-4064-b2e0-9246a8826ab2","added_by":"auto","created_at":"2026-05-14 18:25:59","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21330,"visible":true,"origin":"","legend":"\u003cp\u003eMethodology framework.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9039690/v1/ac5284940678f36281762c3c.jpg"},{"id":109282050,"identity":"a87a9774-feaf-4123-ba3c-3b65ecfcf7c1","added_by":"auto","created_at":"2026-05-14 18:25:59","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81882,"visible":true,"origin":"","legend":"\u003cp\u003ePublication by Year\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9039690/v1/94d78af740863151e23f1c5b.jpg"},{"id":109296476,"identity":"008c8285-3589-412c-ad7f-13ebfe27874d","added_by":"auto","created_at":"2026-05-15 08:47:14","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":58940,"visible":true,"origin":"","legend":"\u003cp\u003eDigital twin Technology\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9039690/v1/be9616165638c8a7f2816c91.jpg"},{"id":109405887,"identity":"501b81e9-f103-419a-b11b-e97be712a93c","added_by":"auto","created_at":"2026-05-17 13:20:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":550724,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9039690/v1/52a5b726-6379-4e36-8e1d-0bb439f21745.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Digital Twin: A new Technology for Future Building Sector","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe rise of Industry 4.0 and related initiatives across different sectors, such as Smart Cities. Engineering, and manufacture, serve as excellent illustrations of the swift progress in technology that has occurred recently [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These include Manufacturing 4.0 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], Education 4.0 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], Mass personalization [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], Mining 4.0 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], Real Estate 4.0 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], Building 4.0 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and Construction 4.0 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Integrating digital and physical worlds is essential to the Industry 4.0 idea. Notwithstanding these developments, the building sector faced various issues, the most pressing of which was the urgent need for improved environmental sustainability as well as higher levels of output and operational effectiveness. Digitalization and information technology have been major forces behind the growth of several industries in recent decades. To fully reap the future benefits of Industry 4.0, the building sector must find creative solutions to a specific set of challenges. In this instance, For the building sector to continue growing and being eco- friendly, it becomes necessary to address environmental issues and enhance overall operational effectiveness [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It is a part of the latest phase of the Industrial Revolution, which builds upon technological advancements on par with the revolutionary advances in automation, electrification, and mechanization that preceded it [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eA very fragmented manufacturing process is a characteristic feature of the building sector which leads to a slow uptake of technology. Both of these characteristics are the reason why the sector lacks competitiveness as a whole [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Although the emerging digital technologies will have huge long term payoffs, the industry is not yet ready to adopt the new technologies as suggested by Columbus [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Blending styles and fields of construction.\u003c/p\u003e \u003cp\u003eDigitization and information technology can be used to improve performers, participants and Concerned parties at all the levels of project execution. Love \u0026amp; Matthews [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] argue that to achieve the value and benefit of technology, behaviour, practice, expectation, relationships and change in strategy of the company need to be adjusted.\u003c/p\u003e \u003cp\u003eGunderson [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] believes that technology plays an important role in ensuring the existence of a symbiotic relationship between the society and the firms, more so in their ability to impact the environment. Technology should be assessed accordingly with regard to such intricate relations [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Building Information Modelling (BIM) is an important device to the building industry amid the digital transformation. The vast majority of the recent studies have focused on a number of methods to enhance this technology. The 3D models developed nowadays, as described by Boje et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], are not simply models since they also hold digital tools that enable data mining, communication among a large number of Concerned parties, and specific information at the component level. Lim et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] define the term digital twin to refer to an approach that has been extensively adopted in business world to conduct mathematical modelling, simulation and optimization. It helps in exchanging information between the internal and external Concerned parties as far as smart manufacturing is concerned [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe concept of digital twin technology that connects the parts, devices and mechanisms to the specific architecture is becoming more popular in the global debate of urban planning [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In the case of national and urban sceneries being represented with the help of digital twin, the growing consensus is that construction industry may be revolutionized. This will involve virtual testing of complicated systems before actual implementation into the physical life and real time data analysis [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The main goal of the provided research is to participate in a profound investigation of the suitability and viability of the implementation of the digital twin technology into the building surroundings and functioning may make the sustainability more complete, the operational effectiveness more intensive, and the productivity higher. Our study was motivated by the background issue of the development of the sphere of building sector and the implementation of digitalization [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The use of digital twin technology that will be applied in the whole process of constructing a building is still subject to research. This study seeks to generalize its review with the literature on urban planning, construction sites, and site logistics in their review of digital twin technologies in the context of built environments, intelligent buildings, and smart cities.\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThe current work is carried out in accordance with the principles of systematic reviews, outlined by Saieg et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The systematic review methodology allows the research team to locate, filter and review all the literature available which is relevant to a predetermined standard of quality, a process which Booth and Papaioannou, (2012) emphasize. Among the principal advantages of adopting this procedural framework, there is the fact that it imposes a strict and standardized investigative protocol to the area of interest as emphasized by S. Li et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Subsequently, one can make the results transparently free of subjective bias, which is the quality this approach has guaranteed, according to Jesson et al [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The method has a number of problems. Significant studies with non-significant results and articles that are not written in the English language will be overlooked because most journals tend to publish papers that contain significant impacts [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e is the outline of this extensive systematic review.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003cdiv class=\"Heading\"\u003e3.1.1. Research approach and the choice of studies.\u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003cdiv class=\"Heading\"\u003e3.1.1. Data Source Selection\u003c/div\u003e \u003cp\u003eThe current review follows the principles of conducting a systematic review [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] by utilizing a systematic approach to the analysis of a certain amount and quality of studies related to the digital twin technology and construction 4.0 (2) to provide readers with a clear, objective, and standardised technical roadmap that includes information about the database selection, retrieval of studies, and the criteria of target studies selection; and (3) is reproducible and scalable. The key elements of this systematic strategy include; (1) development of a question; (2) identification of relevant studies; (3) selection and assessment of the relevant studies; (4) content-analysis of the relevant studies; and (5) summary of the findings and conclusions [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe researcher used Scopus databases to search relevant literature and some excellent works that explain the state of digital twin technology and building 4.0 in New Zealand were found in foreign publications. Thus, the objective of our study is to explain the flaws of the digital twin technology. Particularly, authi would be concerned with establishing their contributions and potential outcomes. The datasets of S. Li et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] were therefore deemed particularly useful to our study owing to their massive scope and academic bearing. We did not decide to select Scopus as our primary source randomly. It has an amazing coverage of 15,000 journals published by 4000 publishers, including academic giants in terms of abstract and citation collections.\u003c/p\u003e \u003cp\u003eThe choice of literature was made to include the publications published between July 2023 and July 2018, which will ensure the corpus of data will be substantial and exemplified by the academic rigor to ensure a thorough picture of the applications of digital twin technology in the building industry.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003cdiv class=\"Heading\"\u003e3.1.2. Peer Retrieval\u003c/div\u003e \u003cp\u003eFrom January 2023 through July 2023, a monthly search of the databases was conducted using the same search methodology. The Scopus criteria consisted of the phrases \"title,\" \"abstract,\" and \"keywords\" along with the keyboard combination \"Digital Twin\" AND \"Building sector\" OR \"BIM\".\u003c/p\u003e \u003cp\u003eIt was essential in any academic research to thoroughly review the body of existing literature to collect as much information as possible about pertinent studies. The first step of our data retrieval process was a thorough gathering from three different databases, with a focus on studies that explained how digital twin technology was implemented in the construction sector.\u003c/p\u003e \u003cp\u003eAuthor carefully applied filters to obtain the most pertinent outputs. This article highlighted what appears to be a vacuum in our sophisticated retrieval process: there is a noticeable lack of literature on lean construction in the New Zealand setting, indicating a topic that need more in-depth investigation. After the dual-phase data retrieval, two independent researchers carefully evaluated the remaining papers to guarantee rigor and reduce bias. This required a detailed examination of the publications' principal text, abstracts, titles, and keywords.\u003c/p\u003e \u003cp\u003eAuthor used both inclusion and exclusion criteria to reduce the total number of papers taken into consideration [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The requirements stated that any literature that was redundant should be removed, as should any that had nothing to do with applying digital twin technology to the construction sector. Lastly, any material that merely alluded to the concept of digital twin technology but not delved deeply into it had to be eliminated. The evaluation results were classified into 3 categories based on the following standards: not relevant, somewhat relevant, and relevant. First, two researchers talked about the literature that had variable evaluation results and was categorized as either pertinent or not pertinent, as well as the material that was categorized as somewhat relevant. Next, they tried to come to a consensus over what ought to be included and omitted from the study. The members of the lean construction team spoke and ultimately came to an understanding over the literature on which they could not agree. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e is a represent the initial search in the Scopus database.\u003c/p\u003e \u003cp\u003eThe first search yields a set of papers, book chapters, and conference papers. The aforementioned things were subsequently removed, with the exception of the articles. Thus, the search was restricted to articles only. As a result, after the first purification process, 246 publications were retained as articles, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInitially received publications for Insight based on the quantity of search results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSearch engine and Database\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeyword\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResearch\u003c/p\u003e \u003cp\u003e(No of articles)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLimit to\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDocument Type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eInitial Search Results\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScopus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ldquo;Digital twin and Building sector\u0026rdquo; Or BIM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTitle, abstract and keywords\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConference Papers, Books, Book chapter, and article\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eRemoving Duplicates\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScopus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ldquo;Digital twin and Building sector\u0026rdquo; Or BIM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTitle, abstract and keywords\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConference Papers, Books, Book chapter, and article\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Content Analysis\u003c/h2\u003e \u003cp\u003eThe clusters of the topic examined by the research team were aimed at assessing the contribution of the articles to the formation and possible further content direction in New Zealand. Having reviewed the 130 selected publications, the team found out that the research covered a broad array of topics, such as the following: Although some of them discuss the concepts, principles, technologies, and methodologies involved in lean construction, others examine how the digital twin technology is applied to provide supply chain management, construction 4.0, and other scholarly topics [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The factors that affect the use of digital twin technology in the building business are analysed by some and the effectiveness of digital twin [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] is investigated by others. The 130 selected papers were then encoded upon reading their titles, abstracts and keywords lists. In case, the necessary data that could not be located through the title, or abstract of the article, or the keywords, the whole text had to be read and coded. These articles were handled using Microsoft Word [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The articles were organized into one page with all the articles that had a similar subtopic and each article had a subtopic color-coded according to the category it belonged to. Four distinct subject matter groupings were identified during the in-depth analysis of all the 130 articles. The main aspect of the coding was the critical elements of the material and information in the literature. There were four important parts of information that were coded: (1) paper title; (2) the name of the author; (3) publication date; and (4) the title of the journal the article was published in. The issues that were discussed in the literature about studying the digital twins technology were grouped into four groups that included: (1) theory and application of digital twin technology (2) application of digital twin technology in the research areas in the building sector (3) factors that influence the digital twin technology, and (4) evaluation of the impact of the digital twin. Each cluster of subjects was divided into several subtopics. The coding and classification should also be consistent in order to make sure that the content analysis can be accurate [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. It was due to this that a researcher with a lot of experience in using digital twin technology in building sector facilitated a training session in this study that involved two coders engaged in coding activities and a systematic training aspect.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Findings","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Industry 4.0 and Construction 4.0\u003c/h2\u003e \u003cp\u003eIndustry 4.0 or the first phases of the fourth industrial revolution are already underway in the world in various business realms, as Popkova and Zmiyak [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] note. According to Khan et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], the fourth industrial revolution, also known as Industry 4.0, is characterized by the high level of digitization and the utilization of big data and process automation. This is contrary to other three past industrial revolutions which have introduced new technologies. According to Popkova and Zmiyak [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], the fourth industrial revolution, or Industry 4.0 is different as compared to other industrial revolutions in a myriad of previously unseen aspects, including that there are no people or manual decision-making processes involved in the systems.\u003c/p\u003e \u003cp\u003eAccording to Popkova \u0026amp; Zmiyak [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], Bonnet and Westerman [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], Khan et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], and others, the automation of processes is a key to the success of Industry 4.0. Digitalization development has reached the phase of digital enablement and support already and it is finally at the phase of digital control that unites and binds the digital and physical world, as defined by Qi et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The Industry 4.0 is founded on strongly defined siX design notions by Khan et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Widened communication across technology and human, or interoperability, is the capability to operate with the recently developed technologies such as Cyber-Physical Systems (CPS) and the IoT. Virtualization is the visualization and replication of activities in the real world in the digital world (2). (3) Decentralization refers to the procedure that involves the replacement of CPS systems that can make decisions independently with those that previously had to be given approval by a centralized authority. (4) Real-time capability is the capability to utilize real-time data acquisition to examine and find problems in systems and processes. (5). Service orientation is used in decision making by the operators and managers as well as customers using CPS-connected services. (6). This is termed modularity [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] when it is possible to quickly add new machines, processes, and modules. Sawhney et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] gave an outline in support of Construction 4.0. It applies Industry 4.0 design models to the construction industry. The next construction 4.0 definition provided by the authors is as follows: Construction 4.0 is a model that connects the digital layer, comprised of BIM and Common Data Environments (CDE), and the physical layer, comprised of the asset throughout its entire life, through CPS, the IOT, data, and services. This establishes a networked environment, where organizations, processes, and data are incorporated in an efficient manner to design, build and run assets [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn order to understand the numerous layers which comprise Construction 4.0, one should possess a deep knowledge of the technology which facilitates such transition [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Although the other papers in the corpus look at diverse technologies of Construction 4.0, in this article the researchers look at nine technologies commonly cited in the current research corpus [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. All these technologies are outlined in the short paragraphs that follow, in a manner in which the technology enables the user to passively view the information presented to them; augmented reality (AR) is an information aggregator, as well as, a publishing platform of data. Virtual reality (VR) involves the use of headgear with 360-degree vision that provides users with an intensive virtual experience and introduces a distinct degree of expertise to the users [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCompared to standard Building Information Modelling (BIM), Integrated Building Information Modelling (iBIM) is seen as being at a higher level. Robots that can perform or mimic human behaviours are used in robotics. Additive manufacturing, refer as 3D printing, is the process of turning a computer-aided design (CAD) model into a complex, real 3D object [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The term artificial intelligence (AI) describes the capacity of a computer program to mimic human cognitive function [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Drones, also known as unmanned aerial vehicles (UAVs), are small, unmanned aircraft that may be operated from a distance.\u003c/p\u003e \u003cp\u003eBased on common and compatible communication protocols, the Internet of Things (IoT) is a dynamic, worldwide network infrastructure with self-configuring capabilities [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The phrase \"Internet of Things,\" which is frequently shortened to \"IoT,\" is a combination of the terms \"Internet\" and \"things.\" The Internet is a massive, worldwide network of linked computer networks that serves billions of people worldwide by using the standard Internet protocol suite (TCP/IP) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. With millions of private, public, academic, corporate, and government networks of all sizes connected by a variety of optical, wireless, and electronic networking technologies, it functions as a network of networks. The term \"things\" refers to a wide range of recognizable items or entities in the physical world. These can be commonplace objects like electronics and high-tech products, or they can be more unusual objects that aren't always thought of as electronic, like food, clothes, furniture, materials, parts, equipment, merchandise, specialized items, monuments, works of art, and the various aspects of commerce, culture, and sophistication that are all around us [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. One definition of big data, according to Bilal et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], is the capacity to handle vast volumes of data and extract insightful knowledge from it. Large datasets with a variety of complex structures and large sizes are referred to as \"big data,\" which poses storage, processing, and visualization problems for later steps or results [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. At the initial stage of Construction 4.0 integration activities, a life-cycle view on technology utilization is taken into consideration. A project moved on to the design, construction, and facility management phases after the initial planning stage. Eadie et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] state that integrating technology at the right point in a building project's lifespan allows for the full use of that technology. Teisserenc \u0026amp; Sepasgozar [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] state that improved communication and interaction amongst the Construction 4.0 technologies are necessary for the second phase of integration efforts.\u003c/p\u003e \u003cp\u003eAs per the findings of Aleksandrova et al. [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], the all-encompassing integration of digital technology signifies a noteworthy model change in the building process, establishing a cohesive digital ecosystem. The shift to Construction 4.0 calls for modifications to both methodology and thought processes. The development of digital technologies and their adaptation to the needs of the building sector are extremely dynamic, expensive, and highly customizable [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Furthermore, educating employees and workers to adjust to their new roles is necessary when deploying new technologies. As a result, integrating the new technologies into daily operations and making them usable for a variety of projects is the only method for construction companies to generate excess value [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Rather of taking the more traditional project-oriented approach, one must embrace a process-oriented perspective in order to successfully shift to Construction 4.0 [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. On the other hand, this change in perspective forces construction companies to digitize the processes they currently employ, which creates an additional obstacle for two reasons: 1) Not all procedures can be instantly digitalized, and 2) Most current procedures were developed pas years the currently available digital technologies were even imagined. Because of this, all of the current procedures must be redesigned to accommodate the mentality change and enable the construction organizations' transition to Industry 4.0. A comprehensive framework for Construction 4.0 is also presented by Sawhney et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and is built on the concepts that drive Industry 4.0. Using digital technologies, the digital layer serves as an interface to connect several physical layers. As a result, a strong connection is made between the real and digital worlds.\u003c/p\u003e \u003cp\u003eThe authors stress the value of Common Data Environments (CDE) and Building Information Modelling (BIM) in creating a DT [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. While Building Information Modelling (BIM) allows for a model-centric approach and visible 3D connectivity, CDE offers a continuous stream of data and data management [\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Throughout the complete life cycle of an asset, from its conception to its demolition, these digital layers support downstream activities in addition to aiding in the design and construction of the asset itself. This remains valid even after they have given their approval for the planning and execution of an investment [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Technology in Construction\u003c/h2\u003e \u003cp\u003eConducting an effective examination into corporate management requires taking into account and critically analyzing the role that technology plays [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Depending on the many technological theories, this role of technology may change. According to Orlikowski \u0026amp; Scott (2008), organizational activity is typically constructively interwoven under certain conditions. Because of this, technology cannot be understood in isolation from its context, significance, and effects. Ideas should be flexible and frequently evolve to keep up with the advancement of technology and the application industry [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. This will guarantee that technical innovations are not associated with any intentions or attributes. As the relationship between technology and work in organizations has not yet been conceived, a more advanced theoretical lens will eventually need to be created. Understanding the integrated, diverse, and always changing role of technology probably requires drawing from a variety of technological perspectives and conceptual frameworks.\u003c/p\u003e \u003cp\u003eAccording to Gunderson [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], technology's overt presence may eventually fade as it gets increasingly integrated into society. This gently alludes to the intricate relationship between technology and the social consequences that follow. Similarly, Lee et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] contend that even in cases where the technical component is not directly linked to organizational functions, theoretical frameworks that study the effects and dynamics of technology provide insightful glasses through which to see the world. According to this model, technology transcends its physical form to take on the roles and purposes intended for it. Therefore, the idea of digital twin technology should not be understood in terms of its technological architecture alone, but rather in terms of its potential for interaction with organizational processes and its applicability to current and future construction methodologies. Orlikowski \u0026amp; Scott [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] state that the focus on technology in organizational study is often motivated by the ways in which technology interacts and influences the field. Gunderson [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] asserts that technology affects how societies engage with their constructed and natural surroundings, as well as how organizations interact with one another. Although digital twin technologies are becoming more and more incorporated into different situational practices, they have not yet become widely accepted as a crucial component of organizational operations in the building sector.\u003c/p\u003e \u003cp\u003eAccording to Peine [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], a technological model can explain some aspects of how technology develops in response to particular circumstances, but it is unable to explain how innovation occurs overall. Peine (2008) characterizes it as a technological model with a prevailing design, mutual obligation, and mentality. Scientific models, which are expected solutions to a problem that are widely accepted by all Concerned parties, are the source of this concept. If the dominating design has been correctly developed throughout an industry, the technological model can represent the cumulative technical advancement within that industry quite well. However, it is more difficult to coordinate around a shared commitment and mindset. Peine's [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] description of the technological model is similar to that of Cantwell \u0026amp; Hayashi [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. They characterize it as the similarities among a collection of innovations and discoveries that take place throughout time and at a period when organizational procedures and scientific concepts are similar. The model shifts and the integration of key technological aspects and novel forms of information, institutions, and production variables serve as the best illustrations of process of invention and societal evolution. These technological, socioeconomic, and political models may be applied in the manufacturing industry, in technological domains, or in society, claim Cantwell \u0026amp; Hayashi [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Digitalisation in the Building sector\u003c/h2\u003e \u003cp\u003eIn the building sector, there is currently a clear differentiation between companies that have adopted digital technologies and procedures. Building Information Modelling (BIM), Tekla, and other CAD-related apps are a few examples, along with others that still depend on more traditional methods. This \"digital divide\" can be attributed, according to Ayinla \u0026amp; Adamu [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], to a number of distinct limitations and constraints that companies face while seeking to apply digitalization. Ayinla \u0026amp; Adamu [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] looked into the idea that an organization's adoption of digitalization is heavily influenced by financial reasons. The government, project owners, or customers may place external demands or obligations on this procedure. Governments are increasingly requiring the use of BIM, especially for larger contractors, and as a delivery format, according to Bosch-Sijtsema et al. [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. This has increased the quantity of digitalization in projects [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor SMEs, however, the adoption of BIM has happened more gradually. This purported value states that the main determinant of whether BIM is deployed or not is BIM [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. While non-users do not appreciate the value in technology to the same extent as actual users, the latter strongly believe in its benefits and support its use. Additionally, despite the creation of regulations that strengthen the need for BIM, small and medium-sized firms (SMEs) are impacted by the implementation of BIM since they lack the resources to invest in BIM technology to the same extent as larger players. Two of these barriers include, according to Dainty et al. [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], the cost of software and training. The ability of companies, especially those built with \"innovation thinking\" as a guiding principle, is crucial in evaluating the influence of these factors, claim Ayinla \u0026amp; Adamu [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. The digital gap is more prevalent in larger firms, as specific employees are impacted by the skill and motivational barriers associated with BIM, according to Dainty et al. [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to Davies \u0026amp; Harty [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], a person's willingness to adopt BIM is correlated with how they see the technology's potential to help them in their field of work. Workers' decisions on whether or not to adopt BIM will be influenced by their newly developed understanding of what constitutes performance in their current role and how implementing BIM will either enhance or diminish that performance [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. There is still variation in the level of true digitalization, even among those using digital tools. For example, some organizations think that their digitalization criteria may be satisfied by only moving from paper to digital documents. But the industry's digital transformation involves a much more complex set of conditions, and in order for companies to evolve and achieve saturation, they must yield to pressure from both the inside and the outside [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Bosch-Rekveldt et al. [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] state that the construction sector is unique in a number of ways. Its organization, for instance, is project-based; large construction projects might take decades to complete, while smaller construction projects operate almost exactly like separate businesses. In hierarchical organizations, project managers perform a role similar to that of the chief executive officer.\u003c/p\u003e \u003cp\u003eCompared to other industries like manufacturing, the building sector is said to have a vertical structure, which limits the exchange of knowledge and data between projects [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.4 The idea of Digital twin\u003c/h2\u003e \u003cp\u003eDigital twins are a very recent notion that is constantly changing. However, since the 1960s, the idea which came about as a result of NASA's space missions has been used in a number of sectors[\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. The DT model phrase was credited to Dr. Michael Grieves in 2002. Nonetheless, since the 1960s, the idea has been used in a variety of businesses. Despite the traditional definition of DTs, one approach to conceptualize it is as the integration of a physical thing, its digital representation, and the ways in which both are interconnected. When there is a bidirectional relationship between the two, a true DT is completed, providing a legitimate and accurate representation of the physical asset [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Depending on the use, the physical and digital products' connectivity may change. However, when there is a link between the two in both directions, a true DT is produced. Because of its enormous potential benefits, the notion of DTs is especially relevant to the building sector. The idea of digital twin technology is seen in Fig.\u0026nbsp;3.\u003c/p\u003e \u003cp\u003eHowever, there are a variety of definitions of DTs in this industry because there isn't one that is widely acknowledged. It is necessary to look into these often used definitions. A DT technique is defined as an integrated multi-physics, multi-scale, probabilistic simulation of a complex product by Glaessgen \u0026amp; Stargel [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. To simulate the life of its corresponding twin, this simulation makes use of the greatest physical models currently available, sensor updates, and other similar features. A cyber-physical system product lifecycle model, according to Schroeder et al. [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], is a virtual representation of an actual product that includes data about the product from the beginning of its lifecycle to its disposal. Leng et al. [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] describe the linked representation as a digital twin technology of the machine that runs on the cloud platform and simulates the state of health by combining other physically accessible knowledge with data-driven analytical algorithms. The Centre for Digital Built Britain (CDBB) proposed two distinct definitions of a DT in its Gemini Principles: the first highlighted the model's dynamism, while the second highlighted the model's strategic significance. A dynamic model of an asset is one that gives real-time control to its physical twin in the form of live data flows from sensors, receiving current performance data from the physical twin and feeding it back [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. By employing corporate plans to a system model for the system's static strategic planning reacts to the physical twin through the capital investment, using imputed long-term data from the physical twin.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFig: 3 Digital twin Technology\u003c/p\u003e \u003cp\u003eAdopting Digital Twin Technology solutions is becoming increasingly common as the demand for increased efficiency and competitiveness in construction develops [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This entails the integration of several Industry 4.0 technologies specifically designed for building environments [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. The application of Industry 4.0 technologies to the four fundamental components of DT is covered in detail in the following sections. These characteristics include data collection, data processing, modelling and simulation, and enablers for decision support [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eModelling and Simulation\u003c/strong\u003e \u003cp\u003eThe core elements of DT technologies are modelling and simulation. Both make use of high-fidelity 3D models and simulations to offer intricate visual aids for assessing specific scenarios and verifying automatically generated solutions. These features work in concert with the other construction-related technologies shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData processing\u003c/strong\u003e \u003cp\u003eIt is essential to managing the enormous volumes of heterogeneous, real-time data that are gathered. In order to obtain useful information for modelling and analysis, raw data must be converted and treated. A review of the facilitating technology tools used in different academic works to address issues unique to the construction sector is given in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEnablers for decision support\u003c/strong\u003e \u003cp\u003eAn essential component of construction systems, decision support gives them the ability to manage disruptions and guarantee seamless lifecycle transitions. The key to this capability is the implementation of diverse tools and methodologies for semantic solution generation, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The importance of AI in decision support is emphasized, and particular AI domains are crucial in this regard.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData acquisition\u003c/strong\u003e \u003cp\u003eThe data acquisition procedure starts the process of extracting raw data, and it ends with the transfer of information to a database or cloud-based server. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e lists the main technologies and the construction applications that go along with them.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eWhen it comes to advanced building, the procedure is all about carefully digitizing resources and assets to create a virtual environment [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Collecting data from many sources, having two-way real-time connectivity for monitoring and control, and facilitating smooth cyber-physical information interchange are all part of this comprehensive digitization. Following industrial communication protocols, a variety of sensors and communication devices are used to collect physical data at construction sites. Mapping this data onto cyber entities is made easier by methods like point cloud mapping and BIM modelling [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. To guarantee correct representation and simulation of construction activities, a variety of techniques are used in the cyber component, including point clouds, 3D models, simulation, and BIM [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. In order to convert raw data into useful information and knowledge, the following computational and data processing layers are essential. By handling data, storage, retrieval, and modules related to analytical processing, this is accomplished. To create meaningful relationships between data nodes and easily integrate diverse data sources, data fusion and semantic modelling are used [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. The functional layer is locating essential construction applications and adding domain-specific knowledge, such as stakeholder preferences, safety measures, and regulations [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. End customers are provided with this carefully honed knowledge via user-friendly graphical interfaces. These interfaces enable users to apply system-generated solutions while interacting with and managing physical assets. Certain construction issues can be successfully dealt with and overcome by incorporating these modules [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.5. The transition from Bim to twin\u003c/h2\u003e \u003cp\u003eIn the construction context, Design-Build (DTs) refers to a conceptual strategy that improves the process of sector selection by utilizing a variety of technology tools, including Building Information Modelling (BIM) [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. As per Linderoth [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e], BIM is currently the digital modelling technique that the building sector has adopted to the greatest extent. It has been in use for a very long time to create 3D asset representations. However, BIM has changed over time to allow for greater integration since the introduction of the Industry Foundation Classes (IFC) standard. One of the primary benefit of BIM technology, according to Petrova-Antonova \u0026amp; Spasov [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e], is that it provides a semantic 3D model that serves as a database of asset data.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModelling and simulation in Building sector.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnology\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Application\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuilding Information Modelling (BIM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDisaster planning and damage inspection capabilities are essential for improving structural health monitoring (SHM). By combining these elements, the SHM system can more effectively anticipate and address possible structural problems, guaranteeing security and lessening the effects of calamities.[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eFacility management enhances building lifecycle management (BLM), comfort, and energy efficiency. Add anomaly detection, maintenance, and decision support systems.[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]creating and maximizing resources. Lean manufacturing and configure-to-order techniques can be used to automate construction-related production processes. Make the most of the precast components' production. Develop enduring habits.[\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVirtual/Augmented Reality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe collaboration of robots and humans. facilitates asset management and two-way communication, which eases task planning and supervision.[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eUrban planning and design. Multiple viewpoints and usability assessment from non-expert participants in the construction process.[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoint Cloud\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003easset design and visualization. uses LiDAR, gestalt design principles, and as-built reconstruction approaches to create city and building models; models are categorized using ML/DL-based point cloud interpretation[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt looks at a structure's degree of establishment, projects potential harm to a structure, and evaluates services for digitally rendered structures in a virtual reality setting[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSimulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimizing the structure's architecture. The time and cost of developing prototypes may be reduced by using high-resolution analysis and parametric geometric modelling[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. \u003c/p\u003e \u003cp\u003eEnhancing the performance of buildings. Turn on infrastructure visualizations to keep an eye on the environment and electricity[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eData processing in building sector\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnology\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Application\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlockchain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eproject management. increased automation and intelligence development [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eenhancing the performance of buildings. Boost the energy efficiency of the new and old structures[\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData Mining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForm enduring behaviours. builds an intelligent platform with blockchain integration to support built-up residential buildings[\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. \u003c/p\u003e \u003cp\u003eProject management. Improve service, cooperate with Concerned parties, and implement contracts to increase efficiency[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModelling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecreating and maximizing resources. Equipment reconfiguration or re-installation should be allowed to handle interruption of any kind. Find a panorama where the localization mistake is at least one meter. Increase the assets' representation[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDecision support enablers in the building sector\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnology\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Application\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMachine Learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esurveillance of construction machinery. Examine an asset's performance under different scenarios[\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. \u003c/p\u003e \u003cp\u003eoptimizing construction on-site. Maximize the timeline for the construction process and the structures that make up the building[\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. \u003c/p\u003e \u003cp\u003eauthority over security. Construct a security system and DT-based interior safety management system for a three-story elevator in a commercial building[\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComputer Vision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFacilities management includes movement recognition for maintenance tasks and the restoration of 3D structures from CAD drawings and street view images[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. \u003c/p\u003e \u003cp\u003ebridge maintenance system. Using image recognition can enhance inspection processes[\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003edata acquisition Building sector\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnology\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Application\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIOT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnhancing the surveillance of structural health (SHM). Preventive maintenance for infrastructure ought to be covered[\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. \u003c/p\u003e \u003cp\u003eenhancing the performance of buildings. Incorporate energy efficiency, enhanced FM system, sustainability assessment, and interior safety management into the BLM process[\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWireless sensor Network\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTo lower building expenses, improve energy efficiency and lifespan management[\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. \u003c/p\u003e \u003cp\u003eIt enhances structural health monitoring by utilizing cyber-physical systems (SHM)[\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Media\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnhance the construction lifecycle management process. Included are the plan, design, building, and utilization elements[\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHowever, BIM data may not be readily integrated into other systems, including IoT devices, due to a number of organizational, informational, and technological challenges [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. One potential answer to this issue is the creation of a CDE in conjunction with BIM, which allows for the semantic integration of various datasets, attributes, and examples [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This model for system architecture offers a significant chance to enhance decision support, especially in the design stage of the lifecycle.\u003c/p\u003e \u003cp\u003eIntegration issues still exist, preventing valuable data and information from being connected to other systems, even with current advancements. According to Camposano et al. [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e], the concept of DT has emerged as a viable solution to address the difficulties. Although DTs and BIM are comparable in that they both allow for the creation of 3D renderings of assets, DTs offer greater complexity and integration opportunities due to their emphasis on creating a platform that is user-centric and human-cantered. As-sets are visualized in three dimensions using BIM.\u003c/p\u003e \u003cp\u003eCamposano et al. [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e] state that whereas BIM focuses mostly on the object, DT focuses on representing how people interact with the asset. Given the widespread adoption of BIM, it is recommended that the DT idea be used in conjunction with a range of potential applications that BIM can offer to the building process. Clash detection, visual communication, scheduling, safety management, quality control, cost estimation, construction simulation, and site monitoring are a few possible uses [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA key element that makes many aspects of the building and building sector possible is the digital model. However, overcoming the constraints of BIM's integration capabilities will be necessary to fully utilize these functionalities. As a result, it's necessary to develop more integrated platforms that can seamlessly connect with numerous other systems and operations [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]. The ultimate goal of digital transformations is to reach the highest level of digital maturity that is humanly possible. But since there isn't a single example of a DT that has realized all of its potential, it's difficult to determine whether a DT has [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e] reached its maximum potential because the concept of DTs isn't fully defined.\u003c/p\u003e \u003cp\u003eFurthermore, as the use case is what defines maturity, the asset to which a DT idea is implemented directly affects how mature it has become. There are numerous ways to interpret the term because there isn't a single, widely accepted definition for it. various Concerned parties therefore have various requirements for the kind of connection they require and the data that needs to be sent to them. As a result, it is crucial to ensure that the implementation of DT benefits every stakeholder in the building sector [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe abundance of dynamic data that digital twin technology could handle, its meaning (semantics), and its continuous acquisition of knowledge about the physical world would ultimately constitute its additional values [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. Given that a digital twin technology would mimic the real world, this would be the case. Because of the more intelligent and effective construction process and the more capable lifecycle management, this has long-term positive effects on the built environment. Decreases in carbon emissions, lifecycle costs, and asset resilience would all naturally follow from a society that becomes more environmentally conscious [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBecause of the possible benefits to industry Concerned parties, the government recognizes the potential advantages of implementing Design Thinking (DT) concepts to modify the built environment. As stated in the Gemini principles, which outline the UK's strategy for using digitalization in the industry, everyone is aware that digital transformation is taking place. The government plans to support the transition in its entirety through a variety of aid programs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Smart construction site\u003c/h2\u003e \u003cp\u003eDigital twin technology may be implemented by site managers to streamline the construction process on the construction site. Radio frequency identification (RFID), augmented reality (AR), the Internet of Things (IoT), virtual reality (VR), and other digital tools can be used to monitor and oversee building site projects [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Using technologies like data mining and process modelling can provide insights on various issues, including material logistics, workflow management, and cost prediction. Unmanned aerial vehicles (UAVs) and other imaging vehicles may be used to compare the construction process with the structural model, allowing for a more precise assessment of the site's progress. A list of potential integrations of blockchain technology into different building stages was published by Kifokeris \u0026amp; Koch [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e]. Studies have indicated that the utilization of digital models facilitates the early identification and mitigation of safety issues and possible hazards in the workplace [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e]. By anticipating potential risks associated with building stages and machine operations, personnel in construction and machine operators may find value in mixed reality simulation.\u003c/p\u003e \u003cp\u003eBy using virtual reality (VR) to train on specialized construction activities, such constructing and dismantling tower cranes, the dangers associated with hands-on training are substantially reduced. As per Zhang et al. [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e], the incorporation of hazard-detection algorithms with Building Information Modelling (BIM) enables the accurate identification of fall hazards, hence augmenting building site safety. Moreover, Zhang et al. [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e] stressed that, as not all building components may be fully modelled in the early stages, frequent revisions to the algorithm-generated safety plans are necessary. This suggests that there can be discrepancies between the model's stated assumptions and the actual practice of construction activities, necessitating regular algorithm modifications. Boje et al. [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e] suggested that the digital twin technology model be used to handle comparable issues by connecting sensors to live activities for location tracking and worker monitoring in order to detect and avert potentially unsafe scenarios.\u003c/p\u003e \u003cp\u003eA lightweight digital twin technique designed for industries not usually associated with high technology has been developed by Greif et al. [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e]. This digital twin technology is used with several sensors to track parameters including quantity, time intervals, and silo utilization.\u003c/p\u003e \u003cp\u003eAfter data collection, planned silo rotations and limitations on truck transportation are combined. The research is carried out in the framework of a supplier of bulk materials. This composite data is analysed by the digital twin technology using artificial intelligence and other algorithms, enabling a detailed assessment that takes historical and contemporary data into account. Based on this data, it then suggests the best courses of action and determines dividends for each unique client. Consequently, the operators can choose to accept the proposed course of action exactly as it is or modify it. Knowing the position of its equipment and the total fill amount at all times helps the firm become more predictable and efficient. The logistics and success of the construction project may be achieved, according to Kifokeris \u0026amp; Koch's [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e] study, When material, information, and financial flows are smoothly and transparently integrated within supply chains, blockchains are recommended as an appropriate technology to validate these attributes. This is due to the necessity for accuracy and dependability in managing these flows, along with the demands for transparency and accountability, as noted by Boje et al. [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.7 Built environment.\u003c/h2\u003e \u003cp\u003eThe conventional understanding of the building, engineering, and architecture sectors has recently changed to include facility management and operation under their purview [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e]. This establishes a connection between key construction building Concerned parties, allowing for a broader perspective of the created environment's life-span and a reconsideration of the workflow across the entire delivery process [\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e]. The industry is often referred to as AECO (engineering, construction, architecture, and operation) or AEC/FM (architecture, engineering, construction, and facility management) in studies on digital twin technologies utilized in the existing context [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e]. Urban Planning's earlier study on digital twin technology [\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e] brought attention to this technology in relation to the built environment [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e]. Deng et al. [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e] suggested an evolutionary ladder for the established environment. Building information modelling (BIM) was replaced in the plan with digital twin, which augment BIM with simulation, sensors, and artificial intelligence.\u003c/p\u003e \u003cp\u003eA structure's capacity to reach the digital twin technology ladder category makes it easier to engage and communicate with established surroundings. According to Deng et al. [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e], the next generation of digital twin technology is scalable, enabling real-time data sharing between buildings at the level of individual buildings, multi-building communities, and even entire cities [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, the current corpus of study only addresses a number of impractical aspects and important concepts associated with the digital twin technology of the next generation. Typically, the BIM level is divided into several stages, including the designing, structure, and operating portions [\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, the sophistication of simulation techniques makes it possible to accurately assess energy performance, which makes it easier to simulate construction processes in the future [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e]. The granular control of energy operations, spatial deployment, and thermal comfort settings are improved by integrating the IoT. This feature facilitates the construction process and allows for the thorough evaluation of risks on both an individual and group level. Artificial intelligence (AI) is used to enhance these monitoring and simulation procedures, providing real-time predictive analytics [\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e4.7.1. Buildings\u003c/h2\u003e \u003cp\u003eThe transition from BIM to digital twin technologies for asset, activity, and repair management was described by academics [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e]. There are various shortcomings in the asset management process while using BIM. These categories include the degree of coordination between the many technological factors requiring LOD and detailed information, the management component that integrates the flow of work and education, as well as standard-setting that aims to harmonize various processes, technologies, and developmental phases by guaranteeing disciplines [\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e]. The digital twin technology is more information-rich and has a greater analytical capacity than BIM [\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e]. The digital twin technology also needs to fulfil the requirements for interoperability, intelligence, integration, and efficiency. The level of a digital twin technology that corresponds to the building and infrastructure level is called smart asset management in the construction process, encompassing the procedural and repairing phases [\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA number of stages, including designing, building, retrofitting, and maintaining a structure, as well as managerial and quality assurance level reports pertaining to DT technology, are already in existence during the construction process [\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e]. A framework for digital twin technology has been defined as scalable from the administrative to the building and societal levels within the framework of a case study of a university campus. The framework consists of several levels, including those addressing data integration and models, transmitting, digital modelling, and data gathering [\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e]. It is preferable to take the digital twin technology subset, the neighbourhood, and the city into account while analysing the infrastructure and digital twin technology of a building. This relationship may lead to a better understanding of the social and economic effects as well as chances to enhance city services like transportation and waste collection. The service layer of the dynamic building and city digital twin includes transportation, space deployment, health and safety, electricity, events and failure forecasts, asset and environmental management [\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e4.7.2 Cities\u003c/h2\u003e \u003cp\u003eIoT, it need to do with intelligently managing construction systems, is suggested to be used for a variety of construction scenarios by Yang et al. [\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e]. Digital twin are not discussed by them. High energy efficiency is predicted for intelligent buildings, which will contribute to energy conservation, provide smart services to develop a sustainable city, manage energy, and enhance the value of an IoT environment chain. Similar to this, Woodhead et al. [\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e] also suggested that an IoT network's primary ecosystem component keeps working long after a building project is customarily completed. Furthermore, Yang et al. [\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e] recommend that in order to enhance investment incentives and the advancement of relevant technologies, governments give top priority to the removal of regulatory bottlenecks and the provision of rules, user privacy, and security. According to study by Lehner \u0026amp; Dorffner [\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e], DT technology for metropolitan settings can be successfully scaled to benefit both Concerned parties and inhabitants, from specific structures or neighborhoods to entire cities. In the meantime, Deren et al. [\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e] support the creation of such city-scale digital twin technology through the convergence of artificial intelligence and human expertise with the goal of improving urban management protocols. In order to achieve the best possible energy use, sustainability objectives, and operational efficiency, this digital twin technology needs to work in harmony with smart city infrastructural frameworks that cover transportation, meteorology, and energy distribution, among other areas.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.8 Project Delivery\u003c/h2\u003e \u003cp\u003eA proposal has been made in the industry to implement smart contracts [\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e]. A study was carried out in this specific use of blockchain and digital twin technology to safeguard intellectual property rights (IPR) and maintain confidence among different Concerned parties [\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e]. This was achieved by proving that the work produced by a subcontract producer's machinery falls within the agreed-upon tolerance levels, hence establishing the final product's quality[\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e]. According to their research, any new form of collaboration must first create a predetermined level of confidence. The company that is the owner of the copyright rights is necessary to grant access to confidential data to the organisation performing the contract, and the contracting company is obliged to furnish details regarding the functioning of their manufacturing processes [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e]. By providing accessibility for all Concerned parties regarding the advancements being made through the use of machines and the use of block-chain technology to confirm the proper usage of information, trust can be established and maintained across various businesses, according to Nielsen et al. [\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e]. Furthermore, they contend that the trust does away with the requirement for attorneys to examine and approve contracts. A blockchain-related framework is proposed and verified by Rawat et al. [\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e] to facilitate the project's integrated delivery. They also provide an explanation of the growing body of research on smart contracts in the building sector [121This is done, in part, to ensure that the results of the study conducted by Nielsen et al. [\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e] are reflected. As a result, trust is established and maintained among clients, vendors, and subcontractors, enabling milestone payments to be legitimately linked to actual work completed on the project.\u003c/p\u003e \u003cp\u003eDounas et al.'s study [\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e] examines how blockchain technology and BIM interact, describing how both technologies authenticate and document how building designs change and evolve during construction. Similarly, research conducted in the sector of building by Kifokeris \u0026amp; Koch (2020) emphasizes the function of blockchain in facilitating smart contracts. They do point out that there aren't many instances of this technology being used successfully. The significant danger of information attrition is highlighted by Mahmoodian et al. [\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e123\u003c/span\u003e] at different points in a construction project, especially while moving from the building phase to the operating phase. Waqar et al. [\u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e124\u003c/span\u003e] contribute to this discussion by offering a timetable that outlines the procedures for information linking between several models, resulting in an operational BIM that gathers the necessary information. It is agreed upon by Tchana et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] that different models need to talk to one other. To safeguard traceable decisions and the model record, they advise, however, linking the used models using digital twin technology (Zhang et al., 2022). We'll take this action to guard against data loss or overwriting. The actual value of digital twin technology utility technologies only becomes evident when employed from the production stage to asset management, according to a study by Love \u0026amp; Matthews [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The adoption of digital technology by asset owners and organizations is recommended by Love et al. [\u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e125\u003c/span\u003e]. In order to enable real-time operations and maintenance procedures and provide a more successful and efficient turnover of the asset, asset owners may specify at handover that a digital twin technology be used (Wu et al., 2022). It is better to adopt digital technologies out of need and desire than to be pressured or inundated with the newest technology [\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e126\u003c/span\u003e]. The advantages of practice and lifecycle implementation amplify the automation, extension, and transformational changes that result from the installation of digital technology. Before starting to build a structure, a number of different players look into the required parts [\u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e127\u003c/span\u003e]. When it comes to planning the municipality's internal expansion as well as the future development of real estate enterprises.\u003c/p\u003e \u003cp\u003eIn order to make sure the proposed project complies with municipal standards, this stage of the process may automatically compare the design digital twin technology with current development plans very early in support of construction [\u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e128\u003c/span\u003e]. Upon completion of the model, the project can proceed to the next phase, which involves obtaining a building permit [\u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e129\u003c/span\u003e]. In both the planning and building phases, the initial design is altered to function as a model for the completed project.\u003c/p\u003e \u003cp\u003eCreating a link between the building and the neighbourhood around it guarantees smooth logistics. It enables the pursuit of automatic maintenance of the building based on events that occur close to its location in the future and the structural progress that is being made [\u003cspan citationid=\"CR130\" class=\"CitationRef\"\u003e130\u003c/span\u003e, \u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e131\u003c/span\u003e]. If data is organized then that all parties can easily see it, there will be less conflict at the construction site and in other ongoing neighbourhood activities [\u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e132\u003c/span\u003e]. A final inspection is carried out during the project delivery phase to guarantee that the building meets all specifications and expectations. As of right now, the building functions as an integrated digital twin that is operationally visually connected to the city (Li et al., 2021). Through the use of secure authentication procedures and blockchain technology, Concerned parties at various levels are able to access generated data from the building as well as contextual information.\u003c/p\u003e \u003cp\u003eThe development of complex sensor systems is inextricably linked to advances in technology and system architecture. These cutting-edge systems, which have robotics, GPS, and cellular networking capabilities, make it easier to collect data in difficult and complex locations by using advanced miniaturization and integration techniques (Wu et al., 2022).\u003c/p\u003e \u003cp\u003eImplementing AI-enhanced functions, such as machine learning (ML), computer vision (CV), and optimization algorithms, significantly improves process efficiency and results in better analysis and solutions (Zhang et al., 2022). Moreover, by adding additional project issues inside the same platform, multi-function and integrated Digital Twin Technology (DT) systems aim to enhance operational performance. This includes environmental monitoring, safety management, and building evacuation [\u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e133\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDT systems operate more functionally when their deployment is broader, providing industrial relevance and fully addressing pain points [\u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e134\u003c/span\u003e]. In order to support a sizable administrative system and urban planning, city-scale DT systems move the emphasis from building-oriented solutions to virtual cities' mapping and management. The circular economy is still essential to contemporary building methods because of its dedication to sustainability [\u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e131\u003c/span\u003e]. Throughout a building's full existence, which includes construction, operation, and eventual decommissioning, it aspires to resource conservation, emission reduction, and efficient waste management. Lean principles incorporated into prefabricated manufacturing frameworks reduce their impact on the environment and increase efficiency [\u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e132\u003c/span\u003e]. When subjected to temporal analysis, digital twin (DT) technology can enhance scheduling, reduce interruptions, and limit delay risks\u0026mdash;all of which have the potential to completely transform project management. Thorough economic assessments ensure the financial viability of the selected firm model (Li et al., 2021).\u003c/p\u003e \u003cp\u003eMoreover, the resilience and robustness of building endeavours are improved by combining DT systems with other cutting-edge techniques that come from earlier research on complicated environmental route planning and Building Information Modelling (BIM)-enabled detecting tools [\u003cspan citationid=\"CR130\" class=\"CitationRef\"\u003e130\u003c/span\u003e]. This multifaceted strategy signals a model shift in the building industry by opening the door to the augmentation of DT functions. The benefits of applying digital twin technology are categorized along six major dimensions, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e: Method, Milieu, Measurement, Material, Machine, and Manpower.\u003c/p\u003e \u003cp\u003eAccording to Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e represents, all tangible assets related to machinery and equipment utilized in the building sector, like trucks and cranes, are included in the machine aspect. It is now standard procedure for high-value assets to adopt Digital Transformation (DT) technologies in order to increase efficiency and reduce malfunctions during the course of their operational life. Conversely, the human workforce\u0026mdash;which performs a variety of tasks during the construction phase, from machine operators to designers\u0026mdash;is known as the \"manpower\" component.\u003c/p\u003e \u003cp\u003eA new study mostly concentrates on the on-site building stage, despite the quick acceptance of digital twins in the building process. Even while material performance and tracking\u0026mdash;which includes raw materials and intermediate products like precast models\u0026mdash;have made significant strides, more research and development can still be done. The measuring element effectively transforms drawing information into precise descriptions and amounts, which is highly helpful in evaluating the value, cost, and price of building work. In order to ensure speed, dependability, and sustainability in the creation of infrastructure in a digitalized society, this procedure is essential.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBenefits of digital twin technology applications categorized by construction lifecycle stages.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApplications categorised\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLifecycle Stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConstruction Function\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDT-Enabled Benefits\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDesign \u0026amp; engineering\u003c/p\u003e \u003cp\u003eOperations and maintenance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConstruction logistics\u003c/p\u003e \u003cp\u003eQuality evaluation\u003c/p\u003e \u003cp\u003eSustainability enhancement\u003c/p\u003e \u003cp\u003eSafety management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-Enhance the way that safety is managed on building sites by assessing hazards, employing preventative risk management techniques, and analysing risk variables. \u003c/p\u003e \u003cp\u003e- Enable blockchain for traceability, incorporate the intelligent product-service architecture, and facilitate data synchronization[\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMilieu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOperations \u0026amp; maintenance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMonitoring construction sites\u003c/p\u003e \u003cp\u003eKeeping an eye on building occupancy\u003c/p\u003e \u003cp\u003eManaging indoor environments\u003c/p\u003e \u003cp\u003eDeveloping smart cities.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e- Enhance safety oversight on building sites through threat assessment, proactive risk management, and risk factor analysis. \u003c/p\u003e \u003cp\u003e- Boost digitization of construction by automating the detection and tracking of site and assembly progress. \u003c/p\u003e \u003cp\u003e- Simplified public explanation of policy, urban planning, and administrative operations through digital prototype analysis and visualization.[\u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e129\u003c/span\u003e, \u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e135\u003c/span\u003e, \u003cspan citationid=\"CR136\" class=\"CitationRef\"\u003e136\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasurement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOperations \u0026amp; maintenance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTracking greenhouse gas emissions\u003c/p\u003e \u003cp\u003emonitoring construction sites; monitoring structural health.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e- Provide future models for the continuous and real-time use of SHM, including failure prevention, structural damage detection, safety assessment, and support for maintenance work. \u003c/p\u003e \u003cp\u003eThe ability to create energy\u003c/p\u003e \u003cp\u003esaving and emission-reduction plans is enhanced by real-time GHG emissions monitoring[\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e, \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e, \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e123\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaterial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOperations \u0026amp; maintenance\u003c/p\u003e \u003cp\u003eDecommissioning\u003c/p\u003e \u003cp\u003eDesign and engineering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTracking material information\u003c/p\u003e \u003cp\u003eRecycling and reuse \u003c/p\u003e \u003cp\u003e Reliability and reaction tracking\u003c/p\u003e \u003cp\u003eOptimizing the structure design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e- By offering more accurate models, the design validation of the 3D-printed modules is supported. \u003c/p\u003e \u003cp\u003e- Boost building material traceability and radiological detection. \u003c/p\u003e \u003cp\u003e- Direct material flows toward a sustainable material flow by using quantitative analysis.[\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e126\u003c/span\u003e, \u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e128\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMachine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOperations \u0026amp; maintenance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eManagement of assets and safety \u003c/p\u003e \u003cp\u003eAutomated assembly of robots\u003c/p\u003e \u003cp\u003eControl of intelligent equipment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e- Use concurrent perception modeling to improve robotic building and generative design;\u003c/p\u003e \u003cp\u003e- Strengthen the security mechanism for the digital triplet's more confident object detection. enhances context observation for the purpose of applying robot control strategy[\u003cspan citationid=\"CR130\" class=\"CitationRef\"\u003e130\u003c/span\u003e, \u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e132\u003c/span\u003e, \u003cspan citationid=\"CR137\" class=\"CitationRef\"\u003e137\u003c/span\u003e].\u003c/p\u003e\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManpower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOn-site construction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTraining for workers\u003c/p\u003e \u003cp\u003eSafety of workers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e- Use a virtual practice platform to lower training risk and enhance learning outcomes for professionals in the building sector. \u003c/p\u003e \u003cp\u003e- Synchronize data to handle risks in complex and dynamic circumstances[\u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e133\u003c/span\u003e, \u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e134\u003c/span\u003e, \u003cspan citationid=\"CR138\" class=\"CitationRef\"\u003e138\u003c/span\u003e].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor operations to run well, data about actual objects and target environments must be gathered and monitored. The milieu component provides information about the physical environment in which building activities take place by taking into account ambient data, terrain type, and surrounding layout. As shown by Jiaying Zhang et al. [\u003cspan citationid=\"CR136\" class=\"CitationRef\"\u003e136\u003c/span\u003e], combining DT with the degree of detail extension in Building Information Modelling (BIM) provides a strong framework for efficient on-site building site monitoring and management. The Method aspect includes efforts to increase building and construction efficiency. When planning and engineering structures, planners and architects can reduce their environmental impact by using a realistic strategy called building form optimization. As a result, the incorporation of technologies is causing a considerable transformation in the building sector. In order to fully realize its potential, scholars and professionals in the industry need to broaden their scope beyond the on-site phase, investigate novel approaches for material performance, and enhance building procedures. In the digital age, building better, faster, and more sustainable infrastructures can be achieved by revolutionizing the construction sector by fusing human experience with state-of-the-art technologies.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eA digital twin is a technique that exists only in the digital realm and is the virtual equivalent of a physical object. This could apply to everything from small-scale buildings and infrastructure to large-scale systems like cities, countries, or even the entire planet in the context of the construction business. A digital model must coexist with its physical counterpart throughout its existence in order to be considered a twin. This suggests that the idea of a new physical structure is inextricably related to the development of digital twin technologies. Moreover, the development of digital and physical things occurs simultaneously, mirroring the functional functions of each. It is not necessary for digital twin technology to replicate every aspect of its physical counterpart, though. Rather, the two organizations need to have characteristics in common that support the built environment's sustainability. These characteristics could include improvements in the building sector's efficiency and project completion. The tolerance of the digital twin should be used to help building projects not just from the beginning of design to the end. It can be linked to the digital twin technology of the city from a very early the ecosystem of digital twin, the design process is maintained during the building's construction and operation. In the early stages, the building's digital twin technology is linked to the city's digital twin technology in terms of urban planning and the associated procurement processes. The scalable city digital twin technology can be integrated with the site logistics, such as the work environment and transit schedules, during the construction phase. If this happened, the place would be more like the smart manufacturing factories. Furthermore, the structure's digital twin technology may interact with the city's to manage expected health and energy usage. In addition to an abundance of newly created technologies, the digital world also encompasses a new style of doing business and a unique way of thinking. the notion of working together for the good of all people and future generations.\u003c/p\u003e \u003cp\u003eThe results showed that DT might serve as the basis for a data-driven lifecycle that gathers ever-growing volumes of data, information and, in the end, helps make well-informed decisions. Procedures that make it possible to gather important and influential data should therefore be given top importance. The ability of DTs to cover a building's whole lifecycle makes circular construction viable. DTs are distinct from other technologies and more traditional BIM models because of their data-driven methodology.\u003c/p\u003e \u003cp\u003eAdditionally, it can create new business models based on the capabilities of the DT platform, particularly during the O\u0026amp;M stage. Due to its unique benefits that may be provided to clients and customers through its digital platform and data capacity, DTs offer a compelling value proposition. The extent to which DTs can help with the shift to Construction 4.0 was also looked into in this structure.\u003c/p\u003e \u003cp\u003eAccording to the study, DT can help bring about this transformation. With reference to the SiX Keys to Success Framework, this conclusion is proved [139]. Nonetheless, the interviews revealed that this change will not happen suddenly. When it comes to the construction business, the DT concept is still in its early stages, thus it's possible that the sector will never reach its full potential. Despite this, the goal posts for the DT concept will never be achieved, even though strengthening system integration and progressively enhancing DT capabilities may be the best way to advance. For DT to realize its full potential, all of the industry's Concerned parties must support standardization of tools and procedures as well as data-sharing. As a result, there is less fragmentation in the building business since anybody can access and contribute information to a single platform. This paper elaborates on the critical role that data plays in the Digital Twin Technology (DTs) model, serving as a catalyst and an enabler in equal measure. However, data interchange appears to be a critical factor that needs more research in order to successfully implement DTs. When several Concerned parties are willing to share data, data-centric components inside DTs can never reach their full potential. At the same time, ethical issues including dangers to personal privacy need to be carefully examined because DTs involve a lot of data sharing. Furthermore, when sharing data between different projects with diverse DT models, the question of data ownership becomes even more important. Future research projects might use qualitative or quantitative approaches in addition to case studies to measure the prevalence of data-sharing practices and gauge Concerned parties' preparedness for data exchange. This would help us better understand these complexities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDr. Pragya wrote the main manuscript text and Dr. Chandrashekhar prepared figures. Dr. Linesh Collected the data and henerated the results and Dr. Avichandra reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSepasgozar SME (2021) Differentiating digital twin from digital shadow: Elucidating a paradigm shift to expedite a smart, sustainable built environment. Buildings 11(4):151\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHotov\u0026yacute; M (2018) Dynamic model of implementation efficiency of Building Information Modelling (BIM) in relation to the complexity of buildings and the level of their safety, MATEC Web of Conferences 146 1010\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarc\u0026iacute;a de Soto B, Agust\u0026iacute;-Juan I, Joss S, Hunhevicz J (2022) Implications of Construction 4.0 to the workforce and organizational structures. Int J Constr Manage 22(2):205\u0026ndash;217\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOsunsanmi TO, Aigbavboa CO, Emmanuel Oke A, Liphadzi M (2020) Appraisal of stakeholders\u0026rsquo; willingness to adopt construction 4.0 technologies for construction projects. Built Environ Proj Asset Manag 10(4):547\u0026ndash;565\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStarr CW, Saginor J, Worzala E (2020) The rise of PropTech: emerging industrial technologies and their impact on real estate. J Property Invest Finance 39(2):157\u0026ndash;169\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLo\u0026uml;o\u0026uml;w J, Abrahamsson L, Johansson J (2019) Mining 4.0\u0026mdash;the impact of new technology from a work place perspective. Min Metall Explor 36:701\u0026ndash;707\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamirez-Mendoza RA, Morales-Menendez R, Iqbal H, Parra-Saldivar R (2018) Engineering education 4.0:\u0026mdash;proposal for a new Curricula. IEEE Global Engineering Education Conference (EDUCON), 2018, pp. 1273\u0026ndash;1282\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAheleroff S, Zhong RY, Xu X, Feng Z, Goyal P (2020) Digital Twin enabled mass personalization: a case study of a smart wetland maintenance system, in: International Manufacturing Science and Engineering Conference, vol. 84263, V002T07A025\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaiado RGG, Scavarda LF, de Nascimento DL, Ivson P, Cunha VHC (2020) A maturity model for manufacturing 4.0 in emerging countries. Operations Management for Social Good: 2018 POMS International Conference in Rio, pp. 393\u0026ndash;402\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang X, Xu YY, Ma L (2023) Information technology investment and digital transformation: the roles of digital transformation strategy and top management. Bus Process Manag J 29(2):528\u0026ndash;549\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKor M, Yitmen I, Alizadehsalehi S (2023) An investigation for integration of deep learning and digital twins towards Construction 4.0. Smart Sustainable Built Environ 12(3):461\u0026ndash;487\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu W, Lim KYH, Cai Y (2022) Digital twin and industry 4.0 enablers in building and construction: a Survey, Buildings 12 (11) 2004\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColumbus L, McKinsey\u0026rsquo;s state of machine learning and AI, Forbes F (2017) Com/Sites/Louiscolumbus/2017/07/09/Mckinseys-State-of-Machine- Learning-and-Ai-2017. (Accessed 17 December 2020)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLove PED, Matthews J (2019) The \u0026lsquo;how\u0026rsquo;of benefits management for digital technology: from engineering to asset management. Autom ConStruct 107:102930\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGunderson R (2016) The sociology of technology before the turn to technology. Technol Soc 47:40\u0026ndash;48\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrlikowski WJ (2008) Scott, 10 sociomateriality: challenging the separation of technology, work and organization. Acad Manag Ann 2(1):433\u0026ndash;474\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeisserenc B, Sepasgozar S (2021) Adoption of blockchain technology through digital twins in the construction industry 4.0: a PESTELS approach. Buildings 11(12):670\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoje C, Kubicki S, Guerriero A (2021) A 4D BIM system architecture for the semantic web. Proceedings of the 18th International Conference on Computing in Civil and Building Engineering: ICCCBE 2020, pp. 561\u0026ndash;573\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLim WM, Yap S-F, Makkar M (2021) Home sharing in marketing and tourism at a tipping point: what do we know, how do we know, and where should we be heading? J Bus Res 122:534\u0026ndash;566\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNegri E, Fumagalli L, Macchi M (2017) A review of the roles of digital twin in CPS- based production systems. Procedia Manuf 11:939\u0026ndash;948\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTchana Y, Ducellier G, Remy S (2019) Designing a unique Digital Twin for linear infrastructures lifecycle management. Procedia CIRP 84:545\u0026ndash;549\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKetzler B, Naserentin V, Latino F, Zangelidis C, Thuvander L, Logg A (2020) Digital twins for cities: a state of the art review. Built Environ 46(4):547\u0026ndash;573\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaieg P, Sotelino ED, Nascimento D, Caiado RGG (2018) Interactions of building information modeling, lean and sustainability on the architectural, engineering and construction industry: a systematic review. J Clean Prod 174:788\u0026ndash;806\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi S, Fang Y, Wu X (2020) A systematic review of lean construction in Mainland China. J Clean Prod 257:120581\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJesson J, Matheson L, Lacey FM (2011) Doing Your Literature Review: Traditional and Systematic Techniques\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaofeeq D, Moshood G, Nawanir S, Sorooshian O, Okfalisa (2021) Digital twins driven supply chain Visibility within logistics: a new paradigm for future logistics. Appl Syst Innov 4(2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/asi4020029\u003c/span\u003e\u003cspan address=\"10.3390/asi4020029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoshood TD, Nawanir G, Mahmud F, Ajibike WA (2021) Sustainable system for supply chain management in the Malaysian manufacturing industries: a review and research direction. Int J Supply Chain Oper Resil 5(1):79\u0026ndash;98\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaofeeq D, Moshood G, Nawanir S, Sorooshian F, Mahmud AQ, Adeleke (2020) Barriers and benefits of ICT adoption in the Nigerian construction industry. A comprehensive literature review. Appl Syst Innov 3(4):46\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaofeeq D, Moshood FE, Rotimi JOB, Rotimi (2022) An integrated paradigm for managing efficient knowledge transfer: towards a more comprehensive philosophy of Transferring knowledge in the construction industry. Constr Econ Building 22(3):65\u0026ndash;98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5130/AJCEB. v22i3.8050\u003c/span\u003e\u003cspan address=\"10.5130/AJCEB. v22i3.8050\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoshood TD, Rotimi FE, Rotimi JOB (2022) Knowledge transfer and management in the construction industry: trends and future challenges. Int J Constr Supply Chain Manage 12(1):72\u0026ndash;102. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.14424/ijcscm120122-72-102\u003c/span\u003e\u003cspan address=\"10.14424/ijcscm120122-72-102\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePopkova EG, Zmiyak KV (2019) Priorities of training of digital personnel for industry 4.0: social competencies vs technical competencies. Horizon 27(3/4):138\u0026ndash;144\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan M, Wu X, Xu X, Dou W (2017) Big data challenges and opportunities in the hype of Industry 4.0, in: IEEE International Conference on Communications (ICC), 2017, pp. 1\u0026ndash;6\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonnet D, Westerman G (2020) The new elements of digital transformation. MIT Sloan Manag Rev 62 (2)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQi Q, Tao F, Hu T, Anwer N, Liu A, Wei Y, Wang L, Nee AYC (2021) Enabling technologies and tools for digital twin. J Manuf Syst 58:3\u0026ndash;21\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSawhney A, Riley M, Irizarry J, Riley M (2020) in: A. Sawhney, M. Riley, J. Irizarry (Eds.), Construction 4.0\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJazzar ME, Schranz C, Urban H, Nassereddine H (2021) Integrating construction 4.0 technologies: a four-layer implementation plan. Front Built Environ 144\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRao SS (2019) Engineering Optimization: Theory and Practice. Wiley\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang X, Liang C-J, Menassa CC, Kamat VR (2021) Interactive and immersive process-level digital twin for collaborative human\u0026ndash;robot construction work. J Comput Civ Eng 35(6):4021023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYitmen I, Kovacic I, Tagliabue LC (2023) Cognitive digital twins for facilitating construction 4.0: challenges and opportunities for implementation. Front Built Environ 9:1130115\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu Q, Chen L, Li S, Pitt M (2020) Semi-automatic geometric digital twinning for existing buildings based on images and CAD drawings. Autom ConStruct 115:103183\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNunberg G The Advent of the Internet, 2012. 12th April, Courses\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMadakam S, Lake V, Lake V, Lake V (2015) Internet of things (IoT): a literature review. J Comput Commun 3(5):164\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBilal M, Oyedele LO, Qadir J, Munir K, Ajayi SO, Akinade OO, Owolabi HA, Alaka HA, Pasha M (2016) Big Data in the construction industry: a review of present status, opportunities, and future trends. Adv Eng Inf 30(3):500\u0026ndash;521\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSagiroglu S, Sinanc D (2013) Big data: a review. International Conference on Collaboration Technologies and Systems (CTS), 2013, pp. 42\u0026ndash;47\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEadie R, Browne M, Odeyinka H, McKeown C, McNiff S (2013) BIM implementation throughout the UK construction project lifecycle: an analysis. Autom ConStruct 36:145\u0026ndash;151\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAleksandrova E, Vinogradova V, Tokunova G (2019) Integration of digital technologies in the field of construction in the Russian Federation. Eng Manage Prod Serv 11(3):38\u0026ndash;47\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMateev M (2020) Industry 4.0 and the digital twin for building industry. Ind 4 0 5(1):29\u0026ndash;32\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu H, Zhu Q, Guo Y, Zheng W, Zhang L, Wang Q, Zhou R, Ding Y, Wang W, Pirasteh S (2022) Multi-level voxel representations for digital twin models of tunnel geological environment. Int J Appl Earth Obs Geoinf 112:102887\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYitmen I, Alizadehsalehi S, Akıner I˙, Akıner ME (2021) An adapted model of cognitive digital twins for building lifecycle management. Appl Sci 11(9):4276\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDesogus G, Quaquero E, Rubiu G, Gatto G, Perra C (2021) Bim and iot sensors integration: a framework for consumption and indoor conditions data monitoring of existing buildings. Sustainability 13(8):4496\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlinc R, Turk Zˇ (2019) Construction 4.0\u0026ndash;digital transformation of one of the oldest industries. Econ Bus Rev 21(3):4\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorrecilla-Garc\u0026iacute;a JA, Pardo-Ferreira MC, Rubio-Romero JC (2022) Aproximacio\u0026acute;n inicial al enfoque basado en BIM-based Digital Twinning en la toma de decisiones sobre Seguridad y Salud Laboral en la industria de la construccio\u0026acute;n. Direccio\u0026acute;n y Organizacio\u0026acute;n 76:5\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFunari MF, Hajjat AE, Masciotta MG, Oliveira DV, Louren\u0026ccedil;o PB (2021) A parametric scan-to-FEM framework for the digital twin generation of historic masonry structures. Sustainability 13(19):11088\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026uuml;nzinger M, Prechtel N, Behnisch M (2022) Mapping the urban forest in detail: from LiDAR point clouds to 3D tree models, Urban For. Urban Green 74:127637\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee D, Lee SH, Masoud N, Krishnan MS, Li VC (2021) Integrated digital twin and blockchain framework to support accountable information sharing in construction projects. Autom ConStruct 127:103688\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrlikowski WJ, Scott SV (2008) The Entanglement of Technology and Work in Organizations\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeine A (2008) Technological paradigms and complex technical systems the case of smart homes. Res Pol 37(3):508\u0026ndash;529\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCantwell J, Hayashi T (2019) Paradigm Shift in Technologies and Innovation Systems. Springer\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAyinla KO, Adamu Z (2018) Bridging the digital divide gap in BIM technology adoption. Eng Construct Architect Manag 25(10):1398\u0026ndash;1416\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBosch-Sijtsema P, Isaksson A, Lennartsson M, Linderoth HCJ (2017) Barriers and facilitators for BIM use among Swedish medium-sized contractors-We wait until someone tells us to use it. Visualization Eng 5:1\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDainty A, Leiringer R, Fernie S, Harty C (2017) BIM and the small construction firm: a critical perspective. Build Res Inf 45(6):696\u0026ndash;709\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavies R, Harty C (2013) Implementing \u0026lsquo;Site BIM\u0026rsquo;: a case study of ICT innovation on a large hospital project. Autom ConStruct 30:15\u0026ndash;24\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLei Y, Rao Y, Wu J, Lin C-H (2020) BIM based cyber-physical systems for intelligent disaster prevention. J Industrial Inform Integr 20:100171\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaraben J, Morgenthal G (2021) Methods for the automated assignment and comparison of building damage geometries. Adv Eng Inf 47:101186\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKyvelou P, Buchanan C, Gardner L (2022) Numerical simulation and evaluation of the world\u0026rsquo;s first metal additively manufactured bridge. Structures 42:405\u0026ndash;416\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLydon GP, Caranovic S, Hischier I, Schlueter A (2019) Coupled simulation of thermally active building systems to support a digital twin. Energy Build 202:109298\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBosch-Rekveldt M, Bakker H, Hertogh M (2018) Comparing project complexity across different industry sectors, Complexity (2018)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXue F, Lu W, Chen Z, Webster CJ (2020) From LiDAR point cloud towards digital twin city: Clustering city objects based on Gestalt principles. ISPRS J Photogrammetry Remote Sens 167:418\u0026ndash;431\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhuang C, Liu J, Xiong H (2018) Digital twin-based smart production management and control framework for the complex product assembly shop-floor. Int J Adv Des Manuf Technol 96:1149\u0026ndash;1163\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrieves M, Vickers J (2017) Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. Transdisciplinary Perspectives on Complex Systems. Springer, pp 85\u0026ndash;113\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlaessgen E, Stargel D (2012) The digital twin paradigm for future NASA and US Air Force vehicles, in: 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA, vol. 1818\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchroeder GN, Steinmetz C, Pereira CE, Espindola DB (2016) Digital twin data modeling with automationml and a communication methodology for data exchange. IFAC-PapersOnLine 49(30):12\u0026ndash;17\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeng J, Zhou M, Xiao Y, Zhang H, Liu Q, Shen W, Su Q, Li L (2021) Digital twins- based remote semi-physical commissioning of flow-type smart manufacturing systems. J Clean Prod 306:127278\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNochta T, Wan L, Schooling JM, Parlikad AK (2021) A socio-technical perspective on urban analytics: the case of city-scale digital twins. J Urban Technol 28(1\u0026ndash;2):263\u0026ndash;287\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYou Z, Feng L (2020) Integration of industry 4.0 related technologies in construction industry: a framework of cyber-physical system, IEEE Access 8 122908\u0026ndash;122922\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Saeed Y, Edwards DJ, Scaysbrook S (2020) Automating construction manufacturing procedures using BIM digital objects (BDOs) Case study of knowledge transfer partnership project in UK. Construct Innovat 20(3):345\u0026ndash;377\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang L, Pradhan R, Dutta S, Cai Y (2022) BIM4D-based scheduling for assembling and lifting in precast-enabled construction. Autom ConStruct 133:103999\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan Y, Zhang L (2021) A BIM-data mining integrated digital twin framework for advanced project management. Autom ConStruct 124:103564\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmidt M, Moreno MV, Sch\u0026uuml;lke A, Macek K, Maˇr\u0026iacute;k K, Pastor AG (2017) Optimizing legacy building operation: the evolution into data-driven predictive cyber-physical systems. Energy Build 148:257\u0026ndash;279\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi CZ, Chen Z, Xue F, Kong XTR, Xiao B, Lai X, Zhao Y (2021) A blockchain-and IoT-based smart product-service system for the sustainability of prefabricated housing construction. J Clean Prod 286:125391\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Yuen K-V (2022) Applications of deep learning in intelligent construction. Struct Health Monit Based Data Sci Techniques 227\u0026ndash;245\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaini GS, Pournazari P, Ashok P, van Oort E (2022) Intelligent action planning for well construction operations demonstrated for hole Cleaning optimization and automation. Energies 15(15):5749\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGichane MM, Byiringiro JB, Chesang AK, Nyaga PM, Langat RK, Smajic H, Kiiru CW (2020) Digital triplet approach for real-time monitoring and control of an elevator security system. Designs 4(2):9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShim C-S, Dang N-S, Lon S, Jeon C-H (2019) Development of a bridge maintenance system for prestressed concrete bridges using 3D digital twin model. Struct Infrastruct Eng 15(10):1319\u0026ndash;1332\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZonzini F, Aguzzi C, Gigli L, Sciullo L, Testoni N, De Marchi L, Di Felice M, Cinotti TS, Mennuti C, Marzani A (2020) Structural health monitoring and prognostic of industrial plants and civil structures: a sensor to cloud architecture. IEEE Instrum Meas Mag 23(9):21\u0026ndash;27\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Z, Zhang A, Wang W (2020) A framework for an indoor safety management system based on digital twin. Sensors 20(20):5771\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGr\u0026uuml;bel J, Thrash T, Aguilar L, Gath-Morad M, He\u0026acute;lal D, Sumner RW, Ho\u0026uml;lscher C, Schinazi VR (2022) Dense Indoor Sensor Networks: towards passively sensing human presence with LORAWAN. Pervasive Mob Comput 84:101640\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang L, Fu C, Li Y, Su L (2019) Survey and study on intelligent monitoring and health management for large civil structure. Int J Intell Rob Appl 3:239\u0026ndash;254\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZˇ. Turk R, Klinc (2020) A social\u0026ndash;product\u0026ndash;process framework for construction. Build Res Inf 48(7):747\u0026ndash;762\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLinderoth HCJ (2010) Understanding adoption and use of BIM as the creation of actor networks. Autom ConStruct 19(1):66\u0026ndash;72\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetrova-Antonova D, Spasov A (2021) Towards a semantic 3D model of Sofia city, in: Computational Science and its Applications\u0026ndash;ICCSA 2021: 21st International Conference, Cagliari, Italy, September 13\u0026ndash;16, 2021, Proceedings, Part IV, vol. 21, pp. 230\u0026ndash;241\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCamposano JC, Smolander K, Ruippo T (2021) Seven metaphors to understand digital twins of built assets. IEEE Access 9:27167\u0026ndash;27181\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoje C, Guerriero A, Kubicki S, Rezgui Y (2020) Towards a semantic construction digital twin: directions for future research. Autom ConStruct 114:103179\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOzturk GB (2021) Digital twin research in the AECO-FM industry. J Build Eng 40:102730\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKifokeris D, Koch C (2020) A conceptual digital business model for construction logistics consultants, featuring a sociomaterial blockchain solution for integrated economic, material and information flows. J Inf Technol Constr 25(29):500\u0026ndash;521\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNnaji C, Karakhan AA (2020) Technologies for safety and health management in construction: current use, implementation benefits and limitations, and adoption barriers. J Build Eng 29:101212\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang S, Sulankivi K, Kiviniemi M, Romo I, Eastman CM, Teizer J (2015) BIM-based fall hazard identification and prevention in construction safety planning. Saf Sci 72:31\u0026ndash;45\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreif T, Stein N, Flath CM (2020) Peeking into the void: digital twins for construction site logistics. Comput Ind 121:103264\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYitmen I, Alizadehsalehi S (2021) Towards a digital twin-based smart built environment, BIM-Enabled Cognitive Computing for Smart Built Environment 21\u0026ndash;44\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShahzad M, Shafiq MT, Douglas D, Kassem M (2022) Digital twins in built environments: an investigation of the characteristics, applications, and challenges. Buildings 12(2):120\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeng M, Menassa CC, Kamat VR (2021) From BIM to digital twins: a systematic review of the evolution of intelligent building representations in the AEC-FM industry. J Inf Technol Construct 26\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu J, Lu W, Anumba CJ, Niu Y (2020) From smart construction objects to cognitive facility Management. Cyber-Physical Syst Built Environ 273\u0026ndash;296\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLehtola VV, Koeva M, Elberink SO, Raposo P, Virtanen J-P, Vahdatikhaki F, Borsci S (2022) Digital twin of a city: review of technology serving city needs. Int J Appl Earth Obs Geoinf 102915\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDelgado JMD, Oyedele L (2021) Digital Twins for the built environment: learning from conceptual and process models in manufacturing. Adv Eng Inf 49:101332\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang T, Gan VJL, Hu D, Liu H (2022) Digital twin-enabled built environment sensing and monitoring through semantic enrichment of BIM with SensorML. Autom ConStruct 144:104625\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWahbeh W, Kunz D, Hofmann J, Bereuter P (2020) Digital twinning of the built environment\u0026ndash;an interdisciplinary topic for innovation in didactics, ISPRS Annals of the Photogrammetry. Remote Sens Spat Inform Sci 4:231\u0026ndash;237\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSommer M, Stjepandi\u0026acute;c J, Stobrawa S, von Soden M (2023) Automated generation of digital twin for a built environment using scan and object detection as input for production planning. J Industrial Inform Integr 33:100462\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetri I, Rezgui Y, Ghoroghi A, Alzahrani A (2023) Digital twins for performance management in the built environment. J Industrial Inform Integr 33:100445\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaewunruen S, Xu N (2018) Digital twin for sustainability evaluation of railway station buildings. Front Built Environ 4:77\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang C-H, Lee K-C, Li S-E (2020) A mixed activity-based costing and resource constraint optimal decision model for IoT-oriented intelligent building management system portfolios, Sustain. Cities Soc 60:102142\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWoodhead R, Stephenson P, Morrey D (2018) Digital construction: from point solutions to IoT ecosystem. Autom ConStruct 93:35\u0026ndash;46\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang Z, Hao C, Shao S, Chen Z, Yang L (2022) Appropriate technology and energy security: from the perspective of biased technological change. Technol Forecast Soc Change 177:121530\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLehner H, Dorffner L (2020) Digital geoTwin Vienna: towards a Digital Twin City as Geodata Hub, Springer\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeren L, Wenbo Y, Zhenfeng S (2021) Smart city based on digital twins. Comput Urban Sci 1:1\u0026ndash;11\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNielsen CP, da Silva ER, Yu F (2020) Digital twins and blockchain\u0026ndash;proof of concept. Procedia Cirp 93:251\u0026ndash;255\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang W, Ding L, Zhou C (2021) Cyber physical system for safety management in smart construction site. Eng Construct Architect Manag 28(3):788\u0026ndash;808\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHao JL, Cheng B, Lu W, Xu J, Wang J, Bu W, Guo Z (2020) Carbon emission reduction in prefabrication construction during materialization stage: a BIM- based life-cycle assessment approach. Sci Total Environ 723:137870\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Z, Meng X, Xing Z, Jiang A (2021) Digital twin-based safety risk coupling of prefabricated building hoisting. Sensors 21(11):3583\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRawatD B, Chaudhary V, Doku R (2020) Blockchain technology: emerging applications and use cases for secure and trustworthy smart systems. J Cybersecur Priv 1(1):4\u0026ndash;18\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiach\u0026iacute;o M, Meg\u0026iacute;a M, Chiach\u0026iacute;o J, Fernandez J, Jalo\u0026acute;n ML (2022) Structural digital twin framework: Formulation and technology integration. Autom ConStruct 140:104333\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDounas T, Lombardi D, Jabi W (2021) Framework for decentralised architectural design BIM and Blockchain integration. Int J Architect Comput 19(2):157\u0026ndash;173\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMahmoodian M, Shahrivar F, Setunge S, Mazaheri S (2022) Development of digital twin for intelligent maintenance of civil infrastructure. Sustainability 14(14):8664\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaqar A, Qureshi AH, Alaloul WS (2023) Barriers to Building Information Modeling (BIM) deployment in small construction projects: Malaysian construction industry. Sustainability 15(3):2477\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLove PED, Matthews J, Zhou J (2020) Is it just too good to be true? Unearthing the benefits of disruptive technology. Int J Inf Manag 52:102096\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrozco-Messana J, Lopez-Mateu V, Pellicer TM (2022) City Regeneration through modular phase change materials (PCM) Envelopes for Climate Neutral buildings. Sustainability 14(14):8902\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeˇza S, Mauko Pranji\u0026acute;c A, Vezoˇcnik R, Osmokrovi\u0026acute;c I, Lenart S (2021) Digital twins and road construction using secondary raw materials, J. Adv. Transport. (2021) 1\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe R, Li M, Gan VJL, Ma J (2021) BIM-enabled computerized design and digital fabrication of industrialized buildings: a case study. J Clean Prod 278:123505\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchrotter G, H\u0026uuml;rzeler C (2020) The digital twin of the city of Zurich for urban planning. PFG\u0026ndash;Journal Photogrammetry Remote Sens Geoinf Sci 88(1):99\u0026ndash;112\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee D, Lee S, Masoud N, Krishnan MS, Li VC (2022) Digital twin-driven deep reinforcement learning for adaptive task allocation in robotic construction. Adv Eng Inf 53:101710\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang J, Luo H, Xu J (2022) Towards fully BIM-enabled building automation and robotics: a perspective of lifecycle information flow. Comput Ind 135:103570\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKan C, Fang Y, Anumba CJ, Messner JI (2018) A cyber\u0026ndash;physical system (CPS) for planning and monitoring mobile cranes on construction sites, Proceedings of the Institution of Civil Engineers-Management, Procurement and Law 171 (6) 240\u0026ndash;250\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSepasgozar SME (2020) Digital twin and web-based virtual gaming technologies for online education: a case of construction management and engineering. Appl Sci 10(13):4678\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkanmu AA, Olayiwola J, Ogunseiju O, McFeeters D (2020) Cyber-physical postural training system for construction workers. Autom ConStruct 117:103272\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu J, Wang X, Dang Y, Lv Z (2022) Digital twins and artificial intelligence in transportation infrastructure: classification, application, and future research directions. Comput Electr Eng 101:107983\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang J, Cheng JCP, Chen W, Chen K (2022) Digital twins for construction sites: concepts, LoD definition, and applications. J Manag Eng 38(2):4021094\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi M, Lu Q, Bai S, Zhang M, Tian H, Qin L (2021) Digital twin-driven virtual sensor approach for safe construction operations of trailing suction hopper dredger. Autom ConStruct 132:103961\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu S, Hou L, Zhang GK, Chen H (2022) Real-time mixed reality-based visual warning for construction workforce safety. Autom ConStruct 139:104252\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKavadias S, Ladas K, Loch C (2016) The transformative business model. Harv Bus Rev 94(10):91\u0026ndash;98\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"city-and-built-environment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cben","sideBox":"Learn more about [City and Built Environment](https://www.springer.com/journal/44213/)","snPcode":"44213","submissionUrl":"https://www.editorialmanager.com/cben/default.aspx","title":"City and Built Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"EM KeenBeans","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Digital twin, Construction, Smart City, computer-aided design (CAD), and Building Information Modelling (BIM)","lastPublishedDoi":"10.21203/rs.3.rs-9039690/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9039690/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe building sector's historically sluggish adoption of digital technologies, due to these results are ineffective workflows, frequent cost overruns, and delays. Moreover, these challenges are exacerbated by the fact that it is a disjointed organization due to market forces. Through the promotion of innovation and enhanced collaboration, the digitalization and shift towards Industry 4.0 can potentially increase the productivity and efficiency of construction significantly and reduce the number of the information gaps and inconsistencies in data. The motivation behind the study is the fact that the digital twin-technology may be applied at different stages of the building, starting with a simple design, all the way to project delivery. Existing studies indicate the innovative impact of digital twin technology on ensuring environmental sustainability and innovative building approaches. These virtual replicas are important in simplifying the manufacturing processes in industries through synchronization of social interactions and production. The analysis in depth, the applications of the digital twin technology to the construction industry demonstrate how the technology can be used to accelerate the coordination process and can be used to facilitate the process of sharing the data between the interested parties. Landlords are driving the digitization of collaborative innovation processes in construction as they become more aware of the value of digital twin technologies in local environment. Enhancing asset quality, optimizing project delivery, and promoting social sustainability are all achieved by including digital twin technology from the beginning of a project and maintaining its use throughout the design phase. With the growing connection between sustainability objectives and technology, the construction sector is poised for a profound shift.\u003c/p\u003e","manuscriptTitle":"Digital Twin: A new Technology for Future Building Sector","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 18:25:56","doi":"10.21203/rs.3.rs-9039690/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-11T14:15:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"53800872621419314434694085041649687392","date":"2026-05-06T07:01:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-05T23:35:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-07T13:16:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-07T13:16:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"City and Built Environment","date":"2026-03-05T11:43:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"city-and-built-environment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cben","sideBox":"Learn more about [City and Built Environment](https://www.springer.com/journal/44213/)","snPcode":"44213","submissionUrl":"https://www.editorialmanager.com/cben/default.aspx","title":"City and Built Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"EM KeenBeans","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33ab33d1-0be4-4a06-aa62-35be985cda02","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-11T14:15:36+00:00","index":11,"fulltext":""},{"type":"reviewerAgreed","content":"53800872621419314434694085041649687392","date":"2026-05-06T07:01:53+00:00","index":10,"fulltext":""},{"type":"reviewersInvited","content":"4","date":"2026-05-05T23:35:56+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T18:25:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 18:25:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9039690","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9039690","identity":"rs-9039690","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}