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Driver’s status is crucial because one of the main reasons for motor vehicular accidents is related to driver’s inattention or drowsiness. Drowsiness detector on a car can reduce numerous accidents.
This software is a real-time drowsiness detection system that will constantly monitor the driver's eyelids and detect sleepiness patterns. If it detects any signs of drowsiness, it will ring an alarm in hopes of alerting the driver.
A system that monitors the driver’s face from when the car starts. This mainly helps us to completely monitor the driver’s eye blinking and observe it continuously
Successfully established a deep learning model which can accurately predict the drowsiness state of an individual and thereby alert a driver who is in a drowsy state for preventing fatal accidents.
Project topic is DrowsiShield that ensures drivers safety. The main aim of this system is to avoid accidents by instantly detecting the driver’s level of drowsiness and sending alerts through audio and haptic stimulation.
In this project we will train our model on open and close eyes dataset then use that with face recognition library to check if the driver is sleeping or not.