Design and Development of EEG Signal based Driver Activity Recognition and Monitoring System

Drivers who drive commercial and personal vehicles report having a "very close to miss" owing to lack of energy, while one in five drivers confess to making a severe mistake because of drowsiness pursuant to a 2012-2013 survey by the National-Sleep-Foundation (NSF). This has been shown that drivers' mental exhaustion contributes to the occurrence of road accidents almost as much as their physical fatigue. Driving is a challenging activity that calls for one's undivided attention and a level head. An individual's ability to drive may be impaired if they are under stress or experiencing intense emotions. A system that constantly assesses the driver's well-being is always required. The brain signals of the drivers have been analyzed by researchers using electroencephalography (EEG). This study delves into the current state of the art of EEG assisted Driver surveillance System technology. The planned mechanism for tracking drivers has also been briefly described. Research have looked into brain waves across both brief and lengthy time periods to enable surveillance at varying frequencies. The suggested method achieves 97.2% accuracy in classification compared to an average human professional in a brief time frame, while requiring sophisticated computing. Additional standard warnings, including electrocardiography (ECG), fingers temperature, epidermal of the skin as well as breathing, are additionally assessed with EEG's reliability in constructing a system of this sort. The findings prove that the system makes decisions at regular one-minute intervals and can compensate for differences between users.