A Novel Signal Processing Based Driver Drowsiness Detection System

Abstract

Drowsiness is a major cause of vehicle collisions and it most of the cases it may cause traffic accidents. This condition necessitates the need to develop a drowsiness detection system. Generally, the degree of sleep may be assessed by the number of eye blinks, yawning, gripping power on the steering wheel, and so on. These methods simply compute the actions of the driver. Henceforth, this research work proposes a Brain Computer Interface (BCI) technology to evaluate the mental state of brain by utilizing the EEG signals. Brain signal analysis is the main process involved in this project. Depending on the mental state of the drivers, the neurons pattern differs. Different electric brain signals will be produced in every neurons pattern. The attention level of brain signal varies from general state when the driver is sleeping mentally with eyes open. Various frequency and amplitude of EEG based brain signal are collected by using a brain wave sensor and the attention level is analyzed by using a level splitter section to which the brain signals are made into packets and transmitted through a medium. Level splitter section (LSS) figures out the driver’s state and provides a drowsiness alarm and retains the vehicle in a self-controlled mode until the driver wakes up. Additionally, this research work will provide an alert to the users and control the vehicle by employing the proposed model.