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
Uwagi
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.
Słowa kluczowe
personal security, wearable vision, face recognition, temporal tracking, object detection, YOLO, dlib, OpenCV, edge AI, mobile inference
