WildGuard: Automated Barrier System for Animal Attack Prevention

In areas that are close to forests, human-wildlife conflict poses serious threats to both human life and property. In order to detect and categorise animals in real-time CCTV camera video feeds, this study presents an intelligent system that makes use of deep learning techniques, particularly Convolutional Neural Networks (CNNs). Using Internet of Things components, the system classifies animals as either harmful or non-threatening and initiates automated reactions for the latter. A red warning sign is triggered in the village, a sound-based trap is set up to draw the animal within the camera’s field of view, and notifications are sent to the appropriate authorities when a dangerous animal is spotted. By improving safety by early detection and real-time response, this proactive system seeks to safeguard communities that are close to woods.