Smart System for Accident Prevention Using Drunk and Drive Controller

Abstract

People are currently involved in numerous accidents while travelling by car. Drunk driving and reckless driving during peak hours are the leading causes of accidents. This project contributes to the prevention of such accidents by developing a system that, using a sensor, prevents an intoxicated driver from driving the vehicle and, as a result, controls the ignition of the vehicle’s engine. Accidents occur frequently near school zones. As a result, controlling the vehicle speed is the most important aspect to deal with. This mechanism regulates the vehicle’s speed in school, college, and hospital zones when the camera detects school and hospital zone signs. The method for gathering and detecting signs is mainly reliant on digital image processing. The image processing algorithm takes the necessary action for the acquired indicators. The traffic signs were captured using image enhancement techniques through the Raspberry Pi camera port. The features of speed signs are investigated using the embedded system small computing platform. At that period of daytime vision, the Haar Cascade approach had been used for form analysis to distinguish traffic symbols. The proposed work uses Raspberry Pi 3 board to implement the existing traffic signaling technique.