Smart Forest Fencing System

The increasing incidents of crop damage and human–wildlife conflict near agrarian and forest boundary areas highlight the need for intelligent and robotic protection systems. Traditional fencing methods often fail to provide real-time monitoring and may harm animals or require constant human supervision. This study presents the design and implementation of a Smart Forest Fencing System, an AI-driven surveillance solution that enhances farm security using computer vision and deep learning techniques. The proposed system monitors farm boundaries using cameras and employs the YOLOv8 deep learning model to detect and classify animals into wild or domestic categories. Based on the classification results, the system automatically triggers appropriate responses such as alerts, visual deterrents, and instant notifications to farmers via SMS or email. By integrating image processing, automated alerts, and intelligent decision-making, the proposed system enhances monitoring effectiveness, reduces crop damage, and promotes a safe and non-lethal approach to wildlife management.