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

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
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article

AI-Powered Intrusion Detection System for Drone-Based Surveillance Environments

Zenodo (CERN European Organization for Nuclear Research)
UAV Applications and Optimization
article

AI-Powered Intrusion Detection System for Drone-Based Surveillance Environments

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Guru Gobind Singh Indraprastha University (IN)
Peace, Justice and strong institutions
Openalex Percentile: Top 45%
UAV Applications and Optimization
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