Abstract:
A temporary condition that distinguishes a state between consciousness and sleep is drowsiness. One of the main contributing factors to all accidents worldwide is driver weariness. One of the best ways to gauge driver weariness is by observing the driver's level of sleepiness. In this project, we want to create a drowsiness detection system prototype. This technology detects driving drowsiness by tracking the driver's eyes and vibrating and emitting an alarm. The system is intended to be a real-time monitoring system that is not obtrusive. The emphasis is on making the driver and passengers in the car safer without being intrusive. In this project, a sensor picks up the driver's eye blink. Drivers are considered to be drowsy and are awakened and warned by an alert that sounds and vibrates if their eyes are closed for an extended amount of time. The face feature detection for this is programmed using the Haarcascade package in OpenCV (Open Source Computer Vision). The idea behind the suggested system in this work, which makes use of the OpenCV library, is to use real-time facial image analysis to alert drivers when they are falling asleep or not paying attention, hence reducing the risk of accidents. Under various operating circumstances, the suggested system's effectiveness as a sleepiness warning system is assessed. In order for the expert system to function well, we are attempting to obtain the experimental outcomes is increasing safety in driving.
