• Shreyash Wankhede
• Vikrant Salunke
• Faique Khan
• Rushikesh Nalgire
• Prasad Bhosale

Driver drowsiness and fatigue decrease the vehicle management skills of a driver. The operator driving vehicles at night has become a significant downside today. Driver in a drowsing state is one of the important reasons for an increasing amount of road accidents and death. Hence the drowsiness detection of the driver is considered one of the most active research fields. Many ways are created recently to detect the drowsiness of the driver. Existing methods can be classified into three categories based on physiological measures, performance measures of vehicles, and ocular measures.

"Driver Distraction Detection Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.e96-e101, May-2023, Available :http://www.jetir.org/papers/JETIR2305412.pdf

"Driver Distraction Detection Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppe96-e101, May-2023, Available at : http://www.jetir.org/papers/JETIR2305412.pdf