Neural Network Based Driver Warning System

According to reports, an astounding 69% of adult drivers report driving while drowsy at least once a month in the previous year according to The National Sleep Foundation. In today's fast-moving world people are usually stressed and sleep-deprived due to their demanding career. As a result of this such people fall asleep behind the wheel. Visual fatigue and drowsiness cause many accidents due to which many deaths and injuries are taking place around the world. To increase vehicle security, we propose an advanced driver assistance system (ADAS). This system aims to locate and estimate the driver's eye condition and head position using a camera that will be an indication of his drowsiness level. We also propose a speed control system to detect signboards on the way and instruct the driver either to continue with the same speed or to decelerate the vehicle based on machine learning. This system also calculates the distance between two vehicles, based on the distance it instructs the driver either to continue with the same speed or to slow down. With the system on board of multiple vehicles the safety of the travel increases and the rate of accidents caused due to driver negligence will be reduced.