Project Visum

Accident Prevention System caused By Drowsiness Driving

Project Brief

• Utilise Sensors and AI Algorithms: The system employs sensors and algorithms to analyse parameters like eye movement and facial expressions.

• Real-Time Assessment: By constantly assessing these factors like EAR & Facial Expression the system can accurately determine a driver's alertness level.

• Warning and Intervention: When fatigue signs are detected and crosses certain limits, the system issues warnings or takes intervention measures.

• Microcontroller and OpenCV: A microcontroller based independent unit processes the data, and Singles , a library for real-time computer vision & ML Model is used.

• MediaPipe for Facial Landmark Detection: MediaPipe, an open-source library by Google, is utilised for facial landmark detection to Calculate Eye Aspect Ratio.

• Eye Aspect Ratio Calculation: MediaPipe allows for the calculation of the eye aspect ratio, a critical factor in assessing fatigue.

Demo Video

Project Screenshots