AI and IoT-Based Smart Surveillance for Wildlife Protection

Wildlife poaching and habitat destruction pose significant threats to biodiversity, leading to the rapid declineof endangered species. This paper presents a sustainable, AI-driven Internet of Things (IoT) surveillanceframework for real-time wildlife monitoring and poaching prevention. The proposed system integrates thermalimaging, acoustic sensors, and unmanned aerial vehicles (UAVs) with convolutional neural networks (CNN)for automated detection and classification of potential threats. Data is transmitted via low-power wide-areanetworks (LPWAN) to cloud servers for centralized analytics, alert dissemination, and decision-making. Theapproach focuses on energy efficiency, cost-effectiveness, and scalability to remote forest reserves. Simulationand prototype evaluations demonstrate a detection accuracy of over 94% for human intrusions and an averagelatency of under 2 seconds for alert transmission, making it a viable solution for large-scale wildlife protection.