Authors: Mr.Ayush, Mr.Aditya
Abstract: The rapid advancements in artificial intelligence (AI) and drone technology have revolutionized surveillance, enabling real-time, automated security solutions. This paper presents an AI-powered intrusion detection system (IDS) for drone-based surveillance, leveraging YOLO (You Only Look Once) deep learning models for real-time object detection. The system autonomously identifies potential threats, such as weapons, sharp objects, or unauthorized personnel, and triggers automated alerts. By integrating high-definition cameras and AI-driven decision-making, the proposed system enhances security while reducing human intervention. Experimental evaluations confirm its efficiency in detecting intrusions with high accuracy. Future enhancements include integrating thermal imaging and LiDAR for improved detection.
DOI: http://doi.org/10.5281/zenodo.16608428
