This paper proposes a Smartphone-based system for the detection of drowsiness in automotive drivers. The proposed system uses three-stage drowsiness detection technique. The first stage uses the percentage of eyelid closure (PERCLOS) which is obtained by capturing images with the front camera of the Smartphone with a modified eye state classification method. The system uses near-infrared lighting for illuminating the face of the driver during night driving. The second step uses the voiced to the unvoiced ratio (VUR) obtained from the speech data from the microphone, in the event PERCLOS crosses the threshold. The VUR is also compared with a threshold and if it is a value greater than that of the threshold, it moves on to the next verification stage. In the final verification stage, touch response is required within the stipulated time to declare whether the driver is drowsy or not and subsequently sound an alarm. To awake the driver, a vibrating mechanism is done and also the live GPS location is also sent to an emergency contact. We have studied eight other reference papers for the literature review. The system has three advantages over existing drowsiness detection systems. First, the three-stage verification process makes the system more reliable. The second advantage is its implementation on an Android smart-phone, which is readily available to most drivers or cab owners as compared to other general-purpose embedded platforms. The third advantage is the use of SMS service to inform the control room as well as the passenger regarding the loss of attention of the driver.
Drowsiness, Automotive, Drivers, Warning, Detection, PERCLOS
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