A System for Driver Drowsiness Detection Using Deep Learning

Road accident plays as a factor to increase the number of deaths. Though an accident can occur because of so many facts, but majority cases are happened due to losing of focus. It can become very dangerous and can cause serious financial, security, and health damages. Lack of focus and attentive is usually happens unconsciously due to driver’s sleepiness or fatigue. Those levels of unconsciousness or fatigue play a great role for creating road accident, financial damages, and even death. Those factors are combined to create the long bar of road accident. By using computer science and mathematics those number can be degraded. The drowsiness detection system [DDS] constantly analyze the driver behavior pattern, eye state and notify them to avoid such road accidents and damages. Numerous processes or systems are invented to detect and alert them. Some of them have positive impacts and some of them have negative impacts. But, we invested our time and research to minimize the drawbacks and maximize the benefits which can leap forward. This paper mainly focuses to detect driver drowsiness with mentioning over whelming issue of late warning. This paper is representing the solutions of road accidents due to fatigue or drowsiness by implementing a deep learning-based model which can identify whether the state of eye is opened or closed and those models are implemented with its above mentioning design.