Journal of Ubiquitous Computing and Communication Technologies
Abstract
The problem of road accidents resulting from fatigue and sudden health issues is a significant challenge for an intelligent transportation system. In traditional vehicle safety systems, airbags and seat belts are used for protection after an accident occurs. However, they do not help prevent accidents. In order to overcome the limitation of traditional safety systems, this paper proposes a " Smart Driver Safety and Emergency Response System for Road Accident Prevention " for detecting drivers' fatigue in real time and taking necessary actions for accident prevention. In the proposed system, computer vision technology based on OpenCV and facial landmark detection methods are used for calculating the Eye Aspect Ratio for real-time monitoring. When the EAR value is 0.29 below a threshold for a specific period of time, the system detects a "drowsy" condition and sends control signals automatically to a simulated embedded platform. The motor is stopped, and alert signals are shown. At the same time, rescue actions are initiated for safety purposes. The proposed architecture combines artificial intelligence and control of the embedded system. This is a cost-effective, non-intrusive, and real-time solution for accident prevention. Experimental validation of the proposed approach has confirmed the feasibility of deploying AI-driven proactive safety systems in the context of future smart vehicles.
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