Drowsy Driving Detection System – IoT Perspective

Abstract

This paper proposes a true time Drowsy Driving Detection System for the prevention of road accidents using IOT. One among the main issues for the traffic collision is Sluggishness Driving. An outsized number of road accidents occur due to this which ends up in severe injuries and deaths. For this reason, various studies were wiped out designing systems which will examine the sluggishness of driver and alert him before the accident occurs, thus preventing him to fall sluggishness and cause an accident. The measurements are highly influenced by structure of road, sort of vehicle and driving skills. These are the vehicle based (traditional approaches) measures who designs the system. Other approaches used are psychological measures for his or her system that tend to provide better accuracy in monitoring the drowsiness of the driver. However, in this techniques we use intrusive such as electrodes are required to be placed on the head and body. Furthermore, there are few existing researches during which subjective measurements are used because the input for the system, but, these sorts of methods can distract the driving forces and lead to an ambiguous result. In this paper, we proposed a framework that is absolutely non- intrusive and real-time. Our proposed framework uses the attention closure ratio as input parameter to detect the sluggishness of the driver. If the attention closure ratio deteriorates from the quality ratio, the driver is alerted with the help of a buzzer, water sprinkler on the drives face, back indicator. For our framework, a Pi camera is employed to capture the pictures of the eye of driver . Alcohol detection Sensor is used to detect the Alcohol level consumed by the Driver. Thus, the whole system is incorporated using Raspberry-Pi.