• Aishwarya B. Raundal
• Shruti S. Kale
• Pooja S. Janjire
• Prajakta V. Karkhile
• Prof. Amol N. Rindhe

This project presents a method to automatically detect driver emotion if sleeping or not using Linux based system. Co-ordinates, distance and movement of tracked points were used to create features from visual input that captured facial expressions, head, and face gestures. Spectral features, prosodic features were extracted using the web camera. Face API was used for calculation of features. A combined feature vector was created by feature level fusion and cascade classifier was used for emotion detection. Live participants and actions are to be used for recording simultaneous mixed emotional experience. As per calculated result system we generate the sound when driver any emotion driving the car. If we analysis then accident. We also the different sensor’s like heartbeat sensor, temperature to verify the human health for emergency situation.

Drowsy, machine learning, face detection, eye detection, image processing, open computer vision (OpenCV).

"Drowsy Driving with Health Monitoring and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.903-907, April-2019, Available :http://www.jetir.org/papers/JETIR1904R38.pdf

"Drowsy Driving with Health Monitoring and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp903-907, April-2019, Available at : http://www.jetir.org/papers/JETIR1904R38.pdf