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 Abraham, Leo; Joseph, Joshua; Abhilash, Jess Tom; Paul, Abish; Logesh; Shibu, Shine P.; Lonappan, Linu; Elapilla, Manu Title A name given to the resource Precision Farming on Sugarcane: Drone-Based Disease Detection Using YOLOv8 Neural Models 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 2025 IEEE International Conference on Vehicular Technology and Transportation System, ICVTTS 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICVTTS67119.2025.11296538" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICVTTS67119.2025.11296538</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105032133063?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105032133063?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 Abraham L., CHRIST(Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India; Joseph J., CHRIST(Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India; Abhilash J.T., CHRIST(Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India; Paul A., CHRIST(Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India; Logesh, CHRIST(Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India; Shibu S.P., CHRIST(Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India; Lonappan L., CHRIST(Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India; Elapilla M., CHRIST(Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India Description An account of the resource Precision agriculture is being revolutionized by the use of UAVs and AI, enabling more efficient and sustainable crop monitoring. This study presents a drone-based solution for real-time detection of sugarcane diseases such as Rust, Red Rot, Mosaic, and Yellow Leaf. A custom quadcopter, outfitted with a high-resolution camera and Raspberry Pi 4, is used to capture aerial imagery. The onboard YOLOv8 model processes images in real time, with data stored locally on an SD card for further evaluation. The paper covers the complete system setup, including hardware components, neural network deployment, and the end-to-end workflowfrom image capture to decision support. This integrated approach supports early intervention, better yield outcomes, and cost-effective disease management in sugarcane farming. 2025 IEEE. Subject The topic of the resource deep learning; disease detection; Precision agriculture; Raspberry Pi; sugarcane; unmanned aerial vehicles; YOLOv8 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833156522-0; 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