A person while driving a vehicle - if does not have proper sleep or rest, is more inclined to fall asleep which may cause
a traffic accident.
This is why a system is required which will detect the drowsiness of the driver. Recently, in research and development, machine
learning methods have been used to predict a driver's conditions. Those conditions can be used as information that will improve
road safety.
A driver's condition can be estimated by basic characteristics age, gender and driving experience. Also, driver's driving
behaviours, facial expressions, bio-signals can prove helpful in the estimation. Machine Learning has brought progression in
video processing which enables images to be analysed with accuracy. In this paper, we proposed a method for detecting
drowsiness by using convolution neural network model over position of eyes and extracting detailed features of the mouth using
OpenCV and Dlib to count the yawning
