AI-Driven Ultrasound System for Wildlife Detection and Sustainable Crop Protection

Abstract: The intrusion of wild animals into agricultural areas significantly threatens crop productivity and farmer safety. Conventional deterrent techniques frequently prove inefficient, require excessive manual effort, or risk harming wildlife and ecosystems. This study introduces an intelligent system combining IoT and artificial intelligence (AI) to detect wildlife in real time and protect crops sustainably. The proposed framework employs a camera module for continuous field surveillance, utilizing a Convolutional Neural Network (CNN) powered by the YOLO algorithm to identify animals. Once detected, an IoTconnected ultrasound emitter activates, humanely repelling the animals without physical harm. Additionally, the system captures the animal’s image and transmits an instant alert via GSM to the farmer, including the visual data for remote monitoring. This non-invasive approach enhances eco-friendly agriculture, minimizes crop damage, and provides farmers with real-time alerts, supporting smarter and more sustainable farming.