HEART RATE VARIABILITY BASED DRIVER DROWSINESS DETECTION AND ITS VALIDATION WITH EEG

Thrisha G.*
Periodicity:January - June'2024

Abstract

Being drowsy while driving is deemed a very dangerous thing. It is important to address that problem since drivers’ lives are at risk. Preventing accidents would be too hard for them if they feel drowsy. This study aims to develop a device to help drivers, especially at night, to secure themselves from accidents due to drowsiness or sleepiness. It is especially sought to design an electronic device that will detect a person who is drowsy while driving random changes in steering movement leads to reduction in wheel speed. The threshold of the vibration sensor can be varied and accordingly action can be taken. The outcome is that the vibrator attached to eye blink sensor’s frame vibrates if the driver falls asleep and also the LCD displays the warning messages. The wheel is slowed or stopped depending on the condition. This is accompanied by the owner being notified through the IOT module, so the owner can retrieve the driver’s location, photograph and police station list near to driver’s location. This is how the driver can be alerted during drowsiness and the owner can be notified simultaneously configured to detect drowsiness by means of the proposed web application design manager will check system parameters and send a message to his college colleague. In this project, we proposed heartbeat sensor and eye blink sensor to detect driver stress and driver pupil dilation. The proposed system detects the driver’s drowsiness and if detected alert will be given through buzzer, if the driver doesn’t wakes up then vehicle slows down. The Gas sensor indicator is used to buzzer to measure the fuel level or leakage monitor

Keywords

Machine Learning Real Time Monitoring Electroencephalogram(EEG) Heart Rate Variability(HRV) Driver Drowsiness Detection Frequency Domain Analysis Automatic Nervous System Gas sensor

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