Drowsiness Detection System Using Deep Learning Methods

Abstract

Drowsiness and driver fatigue cause a great percentage of road accidents. The number of deaths and fatalities injuries due to sleeplessness is increasing every year globally. The drowsy state, caused due to no breaks during a long-distance journey can be detected with an attention assist system, a method that can warn inactiveness and warn the driver about the current state of fatigue by detecting eyes as the region of interest. Our system will locate, track and analyze the driver’s eyes and create an alert for the navigation system. The monitoring system is a real-time system that will use machine learning and computer vision to detect driver fatigue and distraction and efficiently avoid and reduce road-accidents caused. The model is able to predict the drowsiness of driver. It is able to analyze whether the eyes are open or closed and face not detected and displayed the intended output with 99.8% accuracy.