A Deep Learning-Based Model for the Detection and Tracking of Animals for Safety and Management of Financial Loss

Abstract

The paper presents a deep learning-based model for detecting and tracking animals to protect agricultural fields. It addresses the challenge of crop destruction by stray animals, a significant issue for farmers, by proposing an intelligent camera-based solution. This solution utilizes IoT for real-time information transfer and employs advanced image and video processing methods, including YoloV5, for efficient animal detection and classification. The study evaluates various existing solutions and highlights the advantages of the proposed model in terms of accuracy and cost-effectiveness, offering a promising approach to mitigate animal raids on crops.