AI-Powered Intrusion Detection System for Drone-Based Surveillance Environments
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) fordrone-based surveillance, leveraging YOLO (You Only Look Once) deep learning models for real-time object detection. Thesystem autonomously identifies potential threats, such as weapons, sharp objects, or unauthorized personnel, and triggersautomated alerts. By integrating high-definition cameras and AI-driven decision-making, the proposed system enhancessecurity while reducing human intervention. Experimental evaluations confirm its efficiency in detecting intrusions with highaccuracy. Future enhancements include integrating thermal imaging and LiDAR for improved detection.
Institutions
- Guru Gobind Singh Indraprastha University (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-10-13
- DOI
- https://doi.org/10.5281/zenodo.16608428
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00