9th International Conference on ICT for Sustainable Development

Authors - Parth Thakkar, Mohammed Kaif Shaikh, Harsh Sanghavi, Dhruv Shah, Vinodray Thumar, Jaimin Shroff
Abstract - The persistent concern of road safety is to be addressed by introducing a cost-effective and robust model for detection of drowsiness and yawning while driving on road. Utilizing theArduCam camera modules, the system constantly records facial benchmarks to analyze the Eye Aspect Ratio (EAR). In the event of calculated EAR values falling below or exceeding the defined threshold range, indicating driver drowsiness or wakefulness, the system issues timely alerts through a speaker. The scope of this work extends to capturing driver’s images in challenging conditions, optimizing emergency response by sending messages to authorities, and implementing a personalized alert system. The ultimate goal is to significantly reduce road accidents and contribute to enhance road safety.