Animal Intrusion Detection and Alert System for Crop Protection - Goyal, Nitika; Sandhu, Navneet Kaur (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Detection of the wild animals in the field is still an open issue and needs to be addressed with an effective and accurate solution. By using the YOLOv5 network, this model has been trained to efficiently detect and track live animals in real-time. With the added advantage of IoT capabilities, real-time alerts are sent to the farmers, allowing them to take immediate actions. The system has been tested across various animal categories such as elephants, horses, cows, deer, rabbits, birds, and foxes. Preliminary results showcase the model’s high accuracy rates, with most of the detections ranging between 85% to 95% .