AI-POWERED PEST DETECTION SYSTEM FOR IMPROVED CROP PROTECTION

Abstract: Globally, pests are responsible for destroying up to 20–40% of annual crop yields, resulting in economic losses exceeding 1.5 lakh crores. Excessive pesticide use to combat pests not only increases farming costs but also contributes to environmental degradation. This project presents an AI-Powered Pest Detection System to address these challenges. Utilizing advanced computer vision, the tool identifies harmful insects in agricultural fields with high accuracy, enabling farmers to take early action and prevent infestations. Real-time detection and integration with drones or cameras enhance surveillance and support precision agriculture. By targeting pest issues promptly, the system reduces pesticide reliance, supports crop health, and maximizes yields. Its efficiency and adaptability make it ideal for large-scale farms, promoting sustainable farming practices and contributing to global food security through proactive crop management.

Keywords: Pest Detection, Deep learning, YOLOV8, Open CV, AI in Agriculture