AIRIS: A Real-Time Face and Object Detection System for Threat Monitoring

This study presents AIRIS (Advanced Intelligent Recognition & Interception System), a real-time personal security monitoring platform integrating computer vision and artificial intelligence for mobile threat detection. The system is based on a three-layer architecture comprising adaptive face detection, temporal tracking, and hazardous object recognition using deep learning models. The main contribution lies in system-level integration and engineering validation under realistic deployment constraints. Individual identification combines embedding-based recognition with position-based tracking, while temporal persistence algorithms assess presence duration to identify potential risks. The implementation employs multithreaded processing and graceful degradation mechanisms to ensure reliable real-time operation in a wearable–mobile configuration. Experimental evaluation demonstrates 87% trial-level detection success for hazardous object presentation trials, 91% alert correctness, and processing throughput of 5–10 FPS with 120–180 ms latency.