Citation

Díaz-Santos S, Cigala-Álvarez, Gonzalez-Sosa E, Caballero-Gil P, Caballero-Gil C. Appl. Sci. (Basel) 2024; 14(6): e2603.

Copyright

(Copyright © 2024, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/app14062603

PMID

unavailable

Abstract

This paper introduces a cutting-edge approach that combines facial recognition and drowsiness detection technologies with Internet of Things capabilities, including 5G/6G connectivity, aimed at bolstering vehicle security and driver safety. The delineated two-phase project is tailored to strengthen security measures and address accidents stemming from driver distraction and fatigue. The initial phase is centered on facial recognition for driver authentication before vehicle initiation. Following successful authentication, the subsequent phase harnesses continuous eye monitoring features, leveraging edge computing for real-time processing to identify signs of drowsiness during the journey. Emphasis is placed on video-based identification and analysis to ensure robust drowsiness detection. Finally, the study highlights the potential of these innovations to revolutionize automotive security and accident prevention within the context of intelligent transport systems.

Language: en

Keywords

driver safety; drowsiness detection; facial recognition; machine learning; video-based identification