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

Authors

  • Khurram Iqbal Department of Computing, Faculty of Engineering Sciences and Technology, Hamdard University, Karachi, Sindh, Pakistan
  • Muhammad Saad Bin Ehtisham National University of Modern Languages, Department of Computer Science, Faculty of Engineering and Computing, Karachi, Sindh, Pakistan
  • Muzammil Ahmad Khan Sir Syed University of Engineering and Technology, Computer Engineering Department, Karachi, Sindh, Pakistan
  • Adnan Chohan Hamdard University, Department of Computing, Faculty of Engineering Science and Technology, Karachi, Sindh, Pakistan
  • Perfshan Erum NED University of Engineering and Technology, Department of Mathematics, Karachi, Sindh, Pakistan
  • Khalil ur Rahman Nazeer Hussain University, Department of Electrical Engineering, Karachi, Sindh, Pakistan,

DOI:

https://doi.org/10.22555/pjets.v13i1.1349

Keywords:

Drone surveillance, Unconstrained Environment , Un-authorized Person Detection, Surveillance Videos, Face Recognition, Facial expression Analysis & Prediction.

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.

References

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Published

2025-07-25

How to Cite

AI-Powered UAV-Patrolling Drone For Real-Time Unauthorized Person Detection. (2025). Pakistan Journal of Engineering, Technology and Science, 13(1), 103-112. https://doi.org/10.22555/pjets.v13i1.1349

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