Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Champatiray, Chiranjibi; Samal, Sonali; Gadekellu, Thippa Reddy; Srivastava, Gautam; Bahubalendruni, Mva Raju Title A name given to the resource HRL-ViT: Human-Robot Collaborative Vision Transformer for AIoT-Enabled Leaf Disease Detection in Precision Agriculture Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Proceedings - 2025 IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CloudCom67567.2025.11331405" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CloudCom67567.2025.11331405</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105034688892?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034688892?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Champatiray C., Christ University, Department of Mechanical &amp; Automobile Engineering, Bengaluru, India; Samal S., Alliance University, Dept. of Computer Science &amp; Engineering, Bengaluru, India; Gadekellu T.R., College of Mathematics and Computer Science, Zhejiang A&amp;F University, Hangzhou, China, Lovely Professional University, Division of Research and Development, Phagwara, India; Srivastava G., Brandon University, Department of Mathematics and Computer Science, MB, Canada; Bahubalendruni M.V.A.R., NIT Puducherry, Dept. of Mechanichal Engineering, Puducherry, India Description An account of the resource The combination of artificial intelligence and Internet of Things (AIoT) technologies is changing precision agriculture by making it possible to automatically check the health of crops. Early detection of leaf diseases is still important for stopping yield losses, but regular convolutional neural networks (CNNs) often don't work as well when they have to deal with different textures, lighting changes, and noise on the field level. To address these constraints, this study presents HRL-ViT, a Human-Robot Collaborative Learning framework that utilizes Vision Transformers for leaf disease identification. The frame-work merges the global attention feature of Vision Transformers with a human-in-the-loop approach, wherein predictions with low confidence are validated by experts and used to improve the model over time. The system is also made for edge-based AIoT deployment, which lets you analyze data in real time in agricultural settings. Experimental research utilizing both benchmark datasets and field-acquired images demonstrates that HRL-ViT consistently surpasses baseline CNN and Transformer models, attaining superior accuracy, precision, and recall while minimizing false detections. Transformers' attention maps can be visualized to make them even easier to understand, which helps users trust them and make decisions. In general, HRL-ViT shows a lot of promise for use in autonomous robotic platforms. It offers an explainable and scalable way to find diseases in precision agriculture. 2025 IEEE. Subject The topic of the resource AIoT; Edge intelligence; Explainable AI; Human-robot collaboration; Leaf disease detection; Precision agriculture; Vision Transformer (ViT) Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833156634-0; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online