AI-Powered Intrusion Detection System for Drone-Based Surveillance Environments
Year: 2025
Type: article
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) 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.
Authors: Ayush, Mr., Adity, Mr.
Institution: Guru Gobind Singh Indraprastha University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893375013
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