Project Title

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A New Approach For A Safe Car Assistance System
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. The changes between conscious and drowsiness state are mapped and used as threshold values for triggering the alarm. Result shows that the drowsy state is detected when the average value of low-alpha is below 0.7, the high-alpha value fall below 0.6 and the theta values is below 0.7 from the normal condition. The low-alpha values are sufficient enough to show the condition of drowsiness, but the high-alpha and theta value can be used to minimize the false alarm event. DrowTion application is developed based on this result. DrowTion is implemented with Mind wave headset with the capability of minimizing false alarm and having the capability of giving multiple alarms. Accuracy of DrowTion application in normal condition is about 68.11%. The proposed work of this project is to develop a system that can be used with real-time wireless monitoring systems which are designed and implemented through wireless network and are able to record and transmit bio-signals of drivers.
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Duration:30 day(s)
Technology:Artificial Intelligence
Price:Rs. 16000 (Group)
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