Vision-Based Tactile Sensors in Precision Agriculture: Deep Learning Approaches, Applications, and Limitations

Vision-Based Tactile Sensors in Precision Agriculture: Deep Learning Approaches, Applications, and Limitations | 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 Vision-Based Tactile Sensors in Precision Agriculture: Deep Learning Approaches, Applications, and Limitations Israa Fahmy, Taimur Hassan, Irfan Hussain, Lakmal Seneviratne, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4173331/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The integration of artificial intelligence with sensor technologies has revolutionized precision agriculture, offering unprecedented opportunities for enhancing crop management and productivity. This review focuses on the latest advancements in vision-based tactile sensors, a technology at the forefront of this transformation. By combining tactile data with vision-based techniques, these sensors provide a more comprehensive understanding of the agricultural environment. We investigate thoroughly the role of deep learning approaches in refining the functionality of these sensors, highlighting their potential to significantly improve the accuracy and efficiency of agricultural operations. The paper also explores the importance of specialized datasets in training deep neural networks for vision-based tactile applications, assessing the current landscape and identifying gaps in the available data. Through a thorough examination of the current state of the art, this review paper aims to shed light on the potential of AI-driven tactile sensing in precision agriculture and outline future research directions to further advance this field. Vision-based tactile sensors Slip detection Produce handling Precision agriculture Deep neural network Deep learning approaches Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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-4173331","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":287761383,"identity":"d110d8bc-255a-4cb8-a0ca-85c3e5ed169a","order_by":0,"name":"Israa Fahmy","email":"","orcid":"","institution":"Khalifa University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Israa","middleName":"","lastName":"Fahmy","suffix":""},{"id":287761385,"identity":"e3480d55-c211-464e-aa2c-b435384a7873","order_by":1,"name":"Taimur Hassan","email":"","orcid":"","institution":"Abu Dhabi University","correspondingAuthor":false,"prefix":"","firstName":"Taimur","middleName":"","lastName":"Hassan","suffix":""},{"id":287761386,"identity":"8429f1dc-baa2-41aa-ac49-a8fc7c9b728e","order_by":2,"name":"Irfan Hussain","email":"","orcid":"","institution":"Khalifa University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Irfan","middleName":"","lastName":"Hussain","suffix":""},{"id":287761387,"identity":"b81bf9d1-b9ed-48eb-a43c-a0723c4d080a","order_by":3,"name":"Lakmal Seneviratne","email":"","orcid":"","institution":"Khalifa University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Lakmal","middleName":"","lastName":"Seneviratne","suffix":""},{"id":287761388,"identity":"eddf6df5-5dc7-4705-a48b-93368c9302e7","order_by":4,"name":"Naoufel Werghi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIie3RvWoCQRDA8QkLa7MPMCL4DBMONoqHvkrCwVYWgo2FRSpt1NrX8A1GDu6aI7YHFiEINklxIWAlJqtiuvWjC2T/sGwzP3ZgAXy+v1oPaodbAIV0HckAT8TcTCC+TB5KcYLcQ6B0vHrvdBYBsXgroB86SX1kDHJmSZbqxpSWmlgGCIlxEuK2rnwOEHRuZKBoGRKDBpCxmyw+NM53lryu9+TFktIGYPftJnnbkuf9K1KsFLFdTGm4G/AZso5qnKBqZUYKRVFQjlUXnybRmcWiec79sFoeJuJLbZv3k3Q4K4pN00lOKXvk7+/A40VwTBRXDvp8Pt8/6wev00+lqkiMfAAAAABJRU5ErkJggg==","orcid":"","institution":"Khalifa University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Naoufel","middleName":"","lastName":"Werghi","suffix":""}],"badges":[],"createdAt":"2024-03-27 04:14:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4173331/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4173331/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73598258,"identity":"ec06d0ff-05bf-49fc-88ea-e44d55a8d8f4","added_by":"auto","created_at":"2025-01-12 14:31:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2199818,"visible":true,"origin":"","legend":"","description":"","filename":"AIReview.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4173331/v1_covered_2b93b49b-b51c-4677-98fc-2201a6640eb5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Vision-Based Tactile Sensors in Precision Agriculture: Deep Learning Approaches, Applications, and Limitations","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Vision-based tactile sensors, Slip detection, Produce handling, Precision agriculture, Deep neural network, Deep learning approaches","lastPublishedDoi":"10.21203/rs.3.rs-4173331/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4173331/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The integration of artificial intelligence with sensor technologies has revolutionized precision agriculture, offering unprecedented opportunities for enhancing crop management and productivity. 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