ItemConference Paper

Intelligent YOLOv8-based Rover for Precision Agriculture: Tomato Ripeness and Disease Detection

Title
Intelligent YOLOv8-based Rover for Precision Agriculture: Tomato Ripeness and Disease Detection
Creator
Logesh, Aj.; Narayan L M, Hari; Arunraja, A.; Joshin Ranedae, Js.; Gibson J, Jerome
Description
Tomato cultivation has traditionally relied on manual inspection and generalized irrigation practices, often resulting in inefficient resource use and reduced yield quality. This work presents a compact rover designed to support precision agriculture in tomato farming. The rover is equipped with an OV2640 camera module, a humidity sensor, and a water-level sensor. The OV2640 captures images of tomato fruits and leaves, transmitting them via Wi-Fi to a laptop for analysis. Two custom-trained YOLOv8 deep learning models are employed for visual diagnostics: one determines tomato ripeness, enabling optimal harvest timing, and the other detects common leaf diseases, including Late Blight, Leaf Mold, Leaf Miner, Mosaic Virus, Septoria, Early Blight, Spider Mites, and Yellow Leaf Curl Virus. In addition to visual inspection, the rover measures environmental parameters such as soil moisture and ambient humidity, supporting data-driven irrigation decisions and early preventive measures. Communication between the rover and the processing unit is achieved through live video streaming from the ESP32-CAM, with processed results enabling either manual teleoperation or potential future autonomous navigation. By integrating AI-based plant health assessment with environmental monitoring, the proposed system offers a economically efficient and scalable solution to improve crop quality, optimize resource usage, and enhance decision-making in tomato farming operations. 2026 IEEE.
Source
Proceedings of 4th International Conference on Electronics and Renewable Systems, ICEARS 2026;pp.1662-1669
Date
01-01-2026
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
ESP32-CAM; IoT-based monitoring; Precision agriculture; Ripeness classification; Tomato disease detection; YOLOv8
Coverage
Logesh Aj., Christ (Deemed to Be University), Department of Electronics and Communication, Bangalore, India; Narayan L M H., Christ (Deemed to Be University), Department of Electronics and Communication, Bangalore, India; Arunraja A., Christ (Deemed to Be University), Department of Electronics and Communication, Bangalore, India; Joshin Ranedae Js., Christ (Deemed to Be University), Department of Electronics and Communication, Bangalore, India; Gibson J J., Christ (Deemed to Be University), Department of Electronics and Communication, Bangalore, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833154881-0;
Format
online
Language
English
Type
Conference paper

Citation

Logesh, Aj.; Narayan L M, Hari; Arunraja, A.; Joshin Ranedae, Js.; Gibson J, Jerome, “Intelligent YOLOv8-based Rover for Precision Agriculture: Tomato Ripeness and Disease Detection,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25982.

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