Application of Machine Learning in Driver Drowsiness Detection

In today’s world, road accidents are mainly caused due to drunken driving, or a driver being fatigued. Therefore, the best way to judge whether the driver is feeling fatigue or not is by checking the state of the driver i.e., drowsiness. With the increase in the road accidents, driver drowsiness detection has become an important factor and is widely accepted. Determining the number of accidents caused by driver drowsiness has become quite difficult as it is not considered most of the time. The shift from feeling fatigue to snoozing usually goes unnoticed by the driver. This led to the requirement of addressing this issue by creating a driver drowsiness detection system to decrease the accidents caused due to drowsiness. Few parameters should be considered to develop such application. One of these parameters includes counting the number of eye blinks in a particular period. The proposed work will keep a record of the eye movements continuously. If the driver is proven to be drowsy then a warning alarm will be initiated. To implement the proposed application, OpenCV library and ML algorithms have been used. This work will benefit in saving several human lives by avoiding road accidents.