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arXiv · 2508.04658

YOLOv8-Based Deep Learning Model for Automated Poultry Disease Detection and Health Monitoring paper

Akhil Saketh Reddy Sabbella·Ch. Lakshmi Prachothan·Eswar Kumar Panta
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Abstract

In the poultry industry, detecting chicken illnesses is essential to avoid financial losses. Conventional techniques depend on manual observation, which is laborious and prone to mistakes. Using YOLO v8 a deep learning model for real-time object recognition. This study suggests an AI based approach, by developing a system that analyzes high resolution chicken photos, YOLO v8 detects signs of illness, such as abnormalities in behavior and appearance. A sizable, annotated dataset has been used to train the algorithm, which provides accurate real-time identification of infected chicken and prompt warnings to farm operators for prompt action. By facilitating early infection identification, eliminating the need for human inspection, and enhancing biosecurity in large-scale farms, this AI technology improves chicken health management. The real-time features of YOLO v8 provide a scalable and effective method for improving farm management techniques.

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Akhil Saketh Reddy Sabbella, Ch. Lakshmi Prachothan, Eswar Kumar Panta. 2025-08-06. YOLOv8-Based Deep Learning Model for Automated Poultry Disease Detection and Health Monitoring paper. https://arxiv.org/abs/2508.04658

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