AI-Powered UAV-Patrolling Drone For Real-Time Unauthorized Person Detection

In the modern era, the integrity and safety of secure environments have become critically important. To address these challenges, an AI-powered UAV-patrolling drone system for real-time unauthorized person detection has been proposed. This drone executes predetermined flight paths, strategically covering surveillance gaps left by static CCTV cameras or human guards. The system integrates multiple state-of-the-art technologies, incorporating advanced facial recognition using Dlib-HOG, CNN, VGG-Face, Google FaceNet, and OpenFace, along with comprehensive facial analysis, providing real-time analysis of race, age, gender, and facial expressions. This technology is especially valuable for securing large venues, critical infrastructure, and high-profile events where unauthorized access poses significant risks. The system's hybrid architecture allows for optimal performance across different lighting conditions, angles, and crowd densities, setting a new standard for intelligent surveillance systems.

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Publication Details

Journal
Pakistan Journal of Engineering Technology & Science
Published
2025-07-25
DOI
https://doi.org/10.22555/pjets.v13i1.1349
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
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article

AI-Powered UAV-Patrolling Drone For Real-Time Unauthorized Person Detection

Khalil Ur Rahman, Muhammad Saad Bin Ehtisham, Muzammil Ahmad Khan, Khurram Iqbal et al.
Pakistan Journal of Engineering Technology & Science
Advanced Neural Network Applications
article

AI-Powered UAV-Patrolling Drone For Real-Time Unauthorized Person Detection

Khalil Ur Rahman, Muhammad Saad Bin Ehtisham, Muzammil Ahmad Khan, Khurram Iqbal, Perfshan Erum, Adnan Chohan
article en

Abstract

In the modern era, the integrity and safety of secure environments have become critically important. To address these challenges, an AI-powered UAV-patrolling drone system for real-time unauthorized person detection has been proposed. This drone executes predetermined flight paths, strategically covering surveillance gaps left by static CCTV cameras or human guards. The system integrates multiple state-of-the-art technologies, incorporating advanced facial recognition using Dlib-HOG, CNN, VGG-Face, Google FaceNet, and OpenFace, along with comprehensive facial analysis, providing real-time analysis of race, age, gender, and facial expressions. This technology is especially valuable for securing large venues, critical infrastructure, and high-profile events where unauthorized access poses significant risks. The system's hybrid architecture allows for optimal performance across different lighting conditions, angles, and crowd densities, setting a new standard for intelligent surveillance systems.

Pakistan Journal of Engineering Technology & ScienceVol. 13(1)
Sindh Madressatul Islam University (PK), NED University of Engineering and Technology (PK), National University of Modern Languages (PK), Hamdard University (PK), Sir Syed University of Engineering and Technology (PK)
Openalex Percentile: Top 80%
Advanced Neural Network Applications
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AI-Powered UAV-Patrolling Drone For Real-Time Unauthorized Person Detection — Khalil Ur Rahman, Muhammad Saad Bin Ehtisham, et al. · Pakistan Journal of Engineering Technology & Science (2025) | TGRS Research Map | TGRS