Fatigued driving is becoming a dangerous and widespread occurrence for drivers, and it is a key contributor to deadly car accidents. To detect tiredness in drivers, machine learning researchers used a variety of sources of data. The morphological features of both the eye and mouth regions were combined in this work, which looked at the fatigue detection problem in terms of feature quantities, classifiers, and modelling parameters. This particular YOLO model is trained to detect two classes. They are “eyes_open” and “eyes_closed”. As soon as the model detects that a person is closing his/her eyes it rings an alarm to alert the driver and passengers.