A New Step To Smart City: Smart Waste Collection Ecosystem Enabled By Real Time Fill Level Monitoring IoT-Based Digital Dustbins

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Abstract Efficient waste management is still a major challenge for urban and industrial areas. It often leads to high operational costs and significant carbon emissions because of ineffective collection schedules and routing. This paper discusses the design and implementation of a smart waste management system based on the Internet of Things (IoT). This system aims to improve waste collection processes, cut operational costs, and lessen environmental impact. The system includes sensor-equipped smart bins that check fill levels in real-time and send data to a central cloud platform. This data is used to plan collection routes and schedules dynamically based on actual needs instead of fixed routines. This approach ensures timely waste disposal and reduces unnecessary vehicle trips, which lowers fuel use and related carbon emissions. Simulation and pilot deployment results show a potential reduction in collection costs by up to 33% per year in terms of fuel cost via route optimization and a decrease in carbon dioxide emissions by 33.3%. This highlights the system’s effectiveness in supporting sustainability. The proposed model acts as a scalable and eco-friendly solution for today’s waste management systems.
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A New Step To Smart City: Smart Waste Collection Ecosystem Enabled By Real Time Fill Level Monitoring IoT-Based Digital Dustbins | 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 A New Step To Smart City: Smart Waste Collection Ecosystem Enabled By Real Time Fill Level Monitoring IoT-Based Digital Dustbins Tanvir Ahmed Momin, Jannatul Ferdaus Khan Lisa, Weney Hasan Shammo, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9167572/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Efficient waste management is still a major challenge for urban and industrial areas. It often leads to high operational costs and significant carbon emissions because of ineffective collection schedules and routing. This paper discusses the design and implementation of a smart waste management system based on the Internet of Things (IoT). This system aims to improve waste collection processes, cut operational costs, and lessen environmental impact. The system includes sensor-equipped smart bins that check fill levels in real-time and send data to a central cloud platform. This data is used to plan collection routes and schedules dynamically based on actual needs instead of fixed routines. This approach ensures timely waste disposal and reduces unnecessary vehicle trips, which lowers fuel use and related carbon emissions. Simulation and pilot deployment results show a potential reduction in collection costs by up to 33% per year in terms of fuel cost via route optimization and a decrease in carbon dioxide emissions by 33.3%. This highlights the system’s effectiveness in supporting sustainability. The proposed model acts as a scalable and eco-friendly solution for today’s waste management systems. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 18 May, 2026 Reviewers agreed at journal 12 May, 2026 Reviews received at journal 09 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers invited by journal 21 Apr, 2026 Editor assigned by journal 28 Mar, 2026 Submission checks completed at journal 28 Mar, 2026 First submitted to journal 19 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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