Traffic accidents pose a serious threat to modern societies, causing harm at both individual and community levels, including health issues, economic losses, and fatalities. The majority of these accidents (65%) are caused by human factors. Therefore, it is crucial to provide continuous feedback to drivers during their driving behavior to assess their mental states and adjust accordingly. This paper introduces a proactive driver monitoring and assistance system aimed at improving road safety. The system utilizes Artificial Intelligence and the Internet of Things to continuously monitor drivers’ mental state and behavior, providing suitable assistance. The system outperforms current solutions due to its portability, and regular update capability. The system technology uses non-intrusive devices and machine learning algorithms to anticipate potential accidents, monitor real-time driver behavior including facial expressions, eye movements, and head position. The system also uses emotion detection to evaluate a driver’s emotional state, making corresponding adjustments to enhance comfort and safety. The effectiveness of our system was validated in tests conducted at Cadi Ayyad University using a driving simulator.
An Efficient Driver Monitoring: Road Crash and Driver Behavior Analysis
Lect. Notes in Networks, Syst.
The International Conference on Artificial Intelligence and Smart Environment ; 2023 ; Errachidia, Morocco November 23, 2023 - November 25, 2023
2024-01-30
7 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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