Driver Drowsiness Detection From Multiple Facial Features Using Mobile Devices

One of the crucial features in advanced driver assistance systems for minimizing catastrophic accidents caused by drivers is drowsiness detection. Drowsy driving has resulted in numerous fatalities or serious injuries for pedestrians and drivers. Being a victim of micro sleeps, a tired driver is probably much more dangerous on the road than a fast motorist. With the help of many technological solutions, automotive researchers and manufacturers are attempting to control this issue before it becomes a crisis. One potential use for intelligent car systems is the identification of sleepy drivers. Therefore, it is a significant task to create a driver drowsiness detection and prevention approach in order to avert these losses of life and property. The current challenges are the increasedcomplexity to produce such a method and also the high costassociated with the development of the method. These challenges can be overcome by using image processing for decreasing the complexity of the systems and using existing hardware like smart phones for drowsiness detection which can in turn decrease the cost associated with the development of the method.