• Abhishek Bhogavkar
• Smita Badarkhe
• Pratik Samage
• Shraddha Bhavankar

To detect the fatigue of driver using the machine learning and gradient statistics-based. Driver drowsiness detection is developed for the real-time application. The number of accidents can be reduced by driver fatigue and thus improve road safety. In recent years, drowsiness and fatigue have become the supreme reasons for causing severe road accidents in India and worldwide as well. The significant increment in the percentage of road accidents due to drowsiness. The work is based on behaviour analysis, high end installation and Machine Learning algorithm to detect the possible coordinate to identify eyes and mouth. Existing state of art methods are computationally complex as compare to this type of method. Based on real time data capturing and analysis eye blinking and yawn detection are considered important parameters to detect drowsiness and fatigue of the driver and ring the alarm accordingly.

Drowsiness detection, Real-Time Detection, Computer Vision, OpenCV, Haar cascade module

"DRIVER DROWSINESS DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.317-322, May-2023, Available :http://www.jetir.org/papers/JETIRFX06056.pdf

"DRIVER DROWSINESS DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pp317-322, May-2023, Available at : http://www.jetir.org/papers/JETIRFX06056.pdf