Abstract: Drowsy driving is one of the most road accidents. Totally different techniques are reportable in the literature to discover drivers’ sleepiness. However, the majority of the prevailing systems solely alert the motive force if sleepiness is detected. Consequently, the drowsy driver continues driving, with a high risk of a devastating accident. During this paper, we have a tendency to project associate degreed verified an EEG primarily based system that not solely alerts the motive force by alarm, but conjointly puts the vehicle in semiautomatic parking mode by dominant fuel provide if sleepiness is detected. At an equivalent time, it reports closed police offices by SMS that contains necessary info to require essential steps locating the vehicle. hold on EEG signals, obtained with wireless wearable headsets in different subjects {in totally different |in several |in numerous} conditions by different analysis teams, were utilized in this work. Power spectrum analyses were dispensed in MATLAB to see the dominant frequency elements within the brain signals. The slow wave to quick wave ratios of EEG activities was assessed for a variety of epochs to see the driver's sleepiness. GPS and GSM modules were used with Arduino MEGA for the following, remote notification and servomotor management. The performance of the projected system was evaluated by holding on to information that confirmed its feasibility and responsibility.
Keywords: Smart system, driver fatigue detection, remote notifications, drowsiness detection, Arduino MEGA, GPS module.
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DOI:
10.17148/IJARCCE.2022.111227
