Driver Identification and Detection of Drowsiness while Driving
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Sleep and Work-Related Fatigue · Artificial Intelligence and Decision Support Systems · IoT and GPS-based Vehicle Safety Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Engineering and Systems, University of La Laguna, 38271 Tenerife, Spain
eXtended Reality Lab, Nokia, 28045 Madrid, Spain
Funding
CDTI (Centre for the Development of Industrial Technology) · the Ministry of Economy Industry and Competitiveness · European Regional Development Fund · European Union (Next Generation)
References (34)
Show source-provided references
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