A proposed Accident Preventive model for Smart Vehicles


Now a days, drowsy driving is becoming biggest challenges leading to the traffic collision. Based on the existing data and statistics, several road accidents and causalities happen due to the drowsy driving which leads to severe injuries. To overcome these challenges, various studies have been done in designing systems that can predict the driver fatigue and alert him beforehand, thus avoiding him to fall asleep behind the wheel and cause an accident. Few existing approaches used psychological measures to give higher accuracy in checking the drowsiness of the driver. However, such approaches are actually intrusive as electrodes are supposed to be incorporated on the head as well as the body. In this paper, a nonintrusive and real-time system has been proposed. This system considers eye closure ratio as input to find driver drowsiness. If this ratio decreases from the standard ratio, the driver is alerted with the help of a notification and also an email alert is communicated to the owner of the vehicle. For our system, a Pi camera is used to catch the photos of the driver’s eye and the entire framework is incorporated in a vehicle using Raspberry-Pi.

Rishabh Malik , Naman Mittal

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