A new approach for a safe car assistance system
This work addresses drowsiness detection for drivers, but it appears incremental as it combines existing methods like Viola-Jones and fuzzy logic without introducing major innovations.
The authors tackled the problem of drowsiness detection in drivers to prevent serious motorway accidents by proposing a system that uses physiological signals and eye blinking, with an experiment conducted to justify its utility.
Drowsiness, which is the state when drivers do not have scheduled breaks while traveling long distances, is the main reason behind serious motorway accidents. Accordingly, experts claim that drowsy state is hard to be recognized early enough to prevent serious accidents that may lead even to road deaths. In this work, we propose a new drowsiness state detection system based on physiological signals and eye blinking. An experiment has been directed to justify the utility of the proposed approach. This system uses a smart video camera that takes drivers faces images and supervises the eye blink (open and close); also, it uses the Emotiv EPOC headset to acquire the electroencephalogram (EEG) signals. Eye detection is done by Viola and Jones technique, EEG. Finally, we have chosen the fuzzy logic techniques to classify the EEG signals and eye blinking detection to analyze the results.