AIRIS: a real-time face and object detection system for threat monitoring
Autor
Urbaniak, Ilona Anna
Kosek, Wiktoria Maria
Kowalska, Alicja Maria
Opublikowane w
Technical Transactions
Numeracja
Vol. 123, iss. 1
Data wydania
2026
Miejsce wydania
Warsaw
Wydawca
Sciendo
Sekcja czasopisma
Information and Communication Technology
Język
angielski
ISSN
0011-4561
eISSN
2353-737X
DOI
https://doi.org/10.37705/TechTrans/e2026007
Słowa kluczowe
personal security, wearable vision, face recognition, temporal tracking, object detection, YOLO, dlib, OpenCV, edge AI, mobile inference
Abstrakt
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.
