Driver Drowsiness Detection System Using Deep Learning Based on Visual Facial Features

Driver's drowsiness is one of the leading causes of road accidents in the UAE and around the globe. Many lives are daily lost because of drowsy driving making an automatic driver drowsiness detection system an urgent necessity for our modern society. Over the past few years, many such systems have been investigated in academic and industry research but none are yet widely used in our day to day life due to high cost, or limited effectiveness. In this paper, we present the first steps of a realtime, non-intrusive, smart drowsiness detection system that works in different real-world scenarios and lighting conditions. Our system utilizes computer vision techniques to detect the driver's face in an infrared video, then a deep neural network predicts whether the driver is drowsy or not based only on their face. Our initial experiments report a promising 94.39% prediction accuracy which outperforms many previously published work especially in night time conditions or scenarios where the driver is wearing sunglasses.