Smart Surveillance of Driver Using Machine Learning

Abstract

Road accidents are often caused by drunk driving and drowsiness. This paper detects the drowsiness of the driver. Besides that, intake of alcohol by the driver is also detected. The main goal of this proposed system is to reduce the number of accidents due to driver's Drowsiness and alcohol intake. This increases the transportation safety. This system also makes use of a USB camera and Alcohol sensor (MQ-135)by which alcohol intake is detected and drowsiness of the driver is also monitored. OpenCV, a machine learning software examines vision-based applications. It is the one which detects the driver's drowsiness. The idea comes with an application which helps to track the drowsiness and also alert the passenger and the owner if the driver is drunk. This will perform tasks like notifying and the customer with alarm by a message notification. The ultimate aim of this system is to design a feasible system that decreases the fatal accidents caused by the drowsiness of the driver and can also display the percentage of alcohol consumed by the driver.