AI-Based Face Covering Detection and Alert System for Secure and Restricted Areas
Abstract
In high-security environments, the presence of unauthorized face coverings (masks, helmets, or balaclavas) can pose significant security risks by hindering facial identification. This paper proposes an automated detection and alert system leveraging the YOLO (You Only Look Once) v8 architecture and IoT-enabled notification protocols. We utilized a custom dataset of 5,000+ images to train a model capable of distinguishing between "No Face Covering," "Medical Mask," and "Unauthorized Covering" with a mean Average Precision (mAP) of 97.4%. The system integrates with existing CCTV infrastructure to provide real-time alerts to security personnel via a cloud-based dashboard, ensuring rapid response in restricted zones.
Fields of Study & Subjects
Advanced Neural Network Applications
Face recognition and analysis
Video Surveillance and Tracking Methods
Publication details
- Journal / source
- International Journal of Science Strategic Management and Technology
- Volume
- 02
- Issue
- 03
- Pages
- 1–9
- Publication date
- 4 March 2026
- Language
- EN