CNN-Based Driver Drowsiness Detection System

Abstract

In today’s world where the number of vehicles is continuously increasing with the advancement of technology, the number of accidents is also rapidly growing as each day passes. According to reports, about 25% of the accidents that takes place recently is due to driver drowsiness because the drivers are sleepy and lack rest during their driving period, and this happens when they drive continuously without taking any break. To avoid the accidents, there is an urgent need of an intelligent system that can detect whether the driver is sleepy or not during driving and can also generate warning/alarm signals in real-time. It can thus decrease the chances of accidents as well as the death rate that take place due to driver drowsiness. In this chapter a mobile’s front camera instead of a webcam is used for detecting the drowsiness of the driver. In this chapter, we have analyzed driver drowsiness using different techniques such as support vector machines (SVM), random forest (RF), convolutional neural networks (CNN), and artificial neural network (ANN).