Intelligent Distraction and Drowsiness Detection System for Automobiles

Road accidents claim millions of lives every year. This statistics calls for a drowsiness detection system that can aid in detecting a lousy driver and help save thousands of lives every year. In this work, a Computer Vision-based approach leveraging Static vector machine (SVM) is adapted in order to produce an innovative solution for the same. The proposed project performs facial feature detection using an incoming live stream of a driver, detects and localizes open and closed eyes. Driver Distraction and Drowsiness Detection System focuses on detecting whether the driver is drowsy and thus distracted from the road using facial feature metrics. It may be used to assign drivers a rating indicating how drowsy a person gets while driving and then this rating can further be used to assign a driver who is less likely to fall asleep. This technology can be provided to companies that provide services like peerto-peer ridesharing and ride service hailing. This will be beneficial to both companies as well as customers. Customers who prefer traveling at night will be the most benefited ones as they will be assigned a more attentive and seasoned driver.