Accident Prevention System caused By Drowsiness Driving
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Utilise Sensors and AI Algorithms: The system employs sensors and algorithms to analyse parameters like eye movement and facial expressions.
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Real-Time Assessment: By constantly assessing these factors like EAR & Facial Expression the system can accurately determine a driver's alertness level.
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Warning and Intervention: When fatigue signs are detected and crosses certain limits, the system issues warnings or takes intervention measures.
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Microcontroller and OpenCV: A microcontroller based independent unit processes the data, and Singles , a library for real-time computer vision & ML Model is used.
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MediaPipe for Facial Landmark Detection: MediaPipe, an open-source library by Google, is utilised for facial landmark detection to Calculate Eye Aspect Ratio.
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Eye Aspect Ratio Calculation: MediaPipe allows for the calculation of the eye aspect ratio, a critical factor in assessing fatigue.
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