Intelligent Habitat Surveillance and Protection System

Abstract— As mortal-wildlife commerce grows further frequent, and wildlife territories face adding environmental pressures, covering beast get has come pivotal for conservation sweats and ecological exploration. This paper presents an AI-driven Wildlife behavior Monitoring System using computer vision, deep literacy, and YOLOv8 to descry, classify, and dissect wildlife conditioning in real-time. The proposed system directly identifies species and tracks actions similar to feeding, movement, resting, and social relations across different territories. It provides detailed receptivity through spatial and temporal mapping, revealing patterns like migration routes and seasonal behavioral changes. Advanced anomaly discovery flags unusual actions, such as torture or eventuality coddling, driving cautions for conservationists. The system’s dashboard visualizes live beast discovery, literal data, and geste reports, aiding experimenters in studying long- term behavioral trends. Unborn features include prophetic analytics for vaccinating wildlife geste, edge AI for remote monitoring, and aural recognition to cover fugitive species. By offering real-time monitoring and data-driven receptivity, this AI-powered system aims to revise wildlife exploration and conservation, including visionary protection and sustainable wildlife operation. Keywords— AI-Powered System, Wildlife behavior, Computer Vision, Yolov8, Animal Tracking, behavior Bracket, Conservation