ItemConference Paper

Precision Farming on Sugarcane: Drone-Based Disease Detection Using YOLOv8 Neural Models

Title
Precision Farming on Sugarcane: Drone-Based Disease Detection Using YOLOv8 Neural Models
Creator
Abraham, Leo; Joseph, Joshua; Abhilash, Jess Tom; Paul, Abish; Logesh; Shibu, Shine P.; Lonappan, Linu; Elapilla, Manu
Description
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.
Source
2025 IEEE International Conference on Vehicular Technology and Transportation System, ICVTTS 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
deep learning; disease detection; Precision agriculture; Raspberry Pi; sugarcane; unmanned aerial vehicles; YOLOv8
Coverage
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
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833156522-0;
Format
online
Language
English
Type
Conference paper

Citation

Abraham, Leo; Joseph, Joshua; Abhilash, Jess Tom; Paul, Abish; Logesh; Shibu, Shine P.; Lonappan, Linu; Elapilla, Manu, “Precision Farming on Sugarcane: Drone-Based Disease Detection Using YOLOv8 Neural Models,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/26148.

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