Wildlife Poaching Risk Prediction and Detection Using Satellite AI

Abstract: Wildlife poaching is one of the major threats to biodiversity and endangered animal species across forest environments. Traditional monitoring systems based on manual patrolling and static surveillance methods are often slow and ineffective in large geographical regions. This paper proposes a Wildlife Poaching Risk Prediction and Detection System using Satellite AI. The proposed framework integrates satellite imagery analysis, environmental monitoring, machine learning algorithms, and YOLO-based suspicious activity detection for intelligent wildlife monitoring. The system supports automated risk prediction, dashboard-based monitoring, and alert generation for wildlife authorities. The framework aims to improve forest surveillance efficiency and support proactive wildlife conservation strategies.

Keywords: Wildlife Conservation, Satellite AI, Machine Learning, YOLO, Risk Prediction, Real-Time Monitoring