Driver Drowsiness Detection using Deep Learning; Approach towards Automating Object Recognition

Drowsiness is the state of being so tired that one feels the urge to rest, and it can result in symptoms that significantly affect how well tasks are performed, such as sluggish response times, brief periods of not being conscious, or microsleeps (blinks lasting more than 500 milliseconds), to mention a few. It is one of the major factors in either serious or deadly car accidents. These symptoms are highly dangerous when driving because they greatly increase the likelihood that drivers will miss road signs or exits, drift into other lanes, or even crash their car and cause an accident. Drivers who are drowsy crash their cars more frequently than those who are alert. So, to avoid these kinds of situations a safety system is used that can help reducing fatal accidents by detecting whether the driver is in drowsy state or not. If the driver is found in drowsy state, the system will start to beep. Hence alerting the driver and co-passengers about the situation. So, the overall goal of our project named driver drowsiness detection is to identify the state when driver feel drowsy and alert him so that fatalities can be terminated.