Many people know that driving while drowsy is dangerous, but they may not know how to detect their own level of sleepiness. The proposed solution will provide you with information on how to look for signs of potential driver drowsiness and take appropriate action. The existing techniques are classified into three major classes namely: vehicular based, behavioral based and physiological based methods. The vehicular based methods utilize parameters like steering control, brake control, acceleration on the pedal and lane deviations. The behavioral based methods utilize parameters like eye blinking, mouth ratio for yawning and head pose. The physiological based methods utilize parameters like heart rate activity, muscle activity and brain activity. These systems are designed to monitor the driver's sleepy state and alert him for prevention of road accidents. However, the accuracy for detecting sleepiness is very low and hence the proposed system will combine these methods to introduce a hybrid system to improve the detection rate. A buzzer is placed to alert the driver when the sleepiness is detected. This would allow the driver to rest or have a coffee instead of driving for long periods without realizing that he is too tired. The proposed solution will also detect the collision of the vehicle and send the location information of the driver through a SMS to the vehicle owner, in case if he is not awakened by the buzzer and met with any minor accident.


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    Titel :

    An Effective IOT based Driver's Drowsiness Detection and Monitoring System to Avoid Real-Time Road Accidents


    Beteiligte:


    Erscheinungsdatum :

    2022-10-07


    Format / Umfang :

    2242076 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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