Drowsiness and Alcohol Detection in Vehicles to Prevent Accidents using IOT Technology

In recent years, the usage of vehicles increased and this increase given raise to the road accidents. The road accidents are mostly caused by the fatigue drivers and drunken drivers. In order to reduce this we managed to make a system which closely monitors the driver’s drowsiness and alcohol state, by doing so if the driver fall asleep or the alcohol state of the driver is high then the vehicle automatically stops. This monitoring system is connected to the vehicle braking system which is electromagnetic braking system helps to control the vehicle moment based on driver’s state. This design is made for some type electrical vehicles which use DC motors in braking system. The drowsiness of the driver is continuously monitored on the webcam and the alcohol state of driver is monitored by the MQ3 alcohol sensor. The webcam detects the pupil moments of the eyes using a python program. This Python program uses Perclos algorithm to detect the eyes of driver. If the eye closes for a specific time then the signal is given to relay to apply brake of the vehicle. If the alcohol rate is high in the driver range then the alcohol sensor gives signal to the relay to apply brake same as drowsiness system. The MQ3 sensor is connected to Arduino board to work. The Arduino board acts as a microcontroller chip in this total system.