AeroShield: Advanced Drone Detection and Security Platform Using Deep Learning

The usage of low-altitude drones has grown quickly, posing serious threats to security in sensitive and re- stricted locations. Drones are small and move quickly in complex areas, making it difficult for traditional surveillance systems to detect them. In order to achieve precise real-time detection on edge devices, this study provides an AI-based drone detection and forecasting system that uses a lightweight deep learning model tuned from YOLOv8n. While a time-series forecasting module forecasts future drone activity and creates risk heatmaps for proactive security planning, the system enhances detection performance through effective feature extraction and strong training techniques. It offers role-based monitoring, real-time alerts, and visualization through integration with web and mobile platforms. The technique is appropriate for practical drone surveillance applications since experimental findings demonstrate good detection accuracy with little computational cost.