A SMARTPHONE-BASED DROWSINESS DETECTION AND WARNING SYSTEM FOR AUTOMOTIVE DRIVERS

Abstract

This paper presents a smartphone-based system for the detection of drowsiness in automotive drivers. The proposed framework uses three-stage drowsiness detection. The first stage uses the percentage of eyelid closure (PERCLOS) obtained through images captured by the front camera with a modified eye state classification method. The system uses near infrared lighting for illuminating the face of the driver during nightdriving. The second step uses the voiced to the unvoiced ratio obtained from the speech data from the microphone, in the event PERCLOS crosses the threshold. A final verification stage is used as a touch response within a stipulated time to declare the driver as drowsy and subsequently sound an alarm. The device maintains a log file of the periodic events of the metrics along with the corresponding GPS coordinates. 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. The framework provides 93.33% drowsiness state classification as compared to a single stage which gives 86.66%.

Existing System

CAMSHIFT algorithm, Haar classifier

Proposed System

The system uses a three-stage approach. The first stage computes the PERCLOS using images captured from the front camera of the smartphone. On PERCLOS being higher than a preset threshold, the system asks the driver to say his full name. As a final stage verification, the driver is asked to touch the screen of the smartphone within 10s, once he is found to be fatigued by the earlier two stages, i.e., the PERCLOS and voice-based measures. The system maintains a log file, stored in the root directory of the internal memory. It stores the PERCLOS values for each minute, along with the GPS coordinates. Each time the driver is found to be drowsy he is warned with a sound alarm. In case, the driver is found to be drowsy for consecutive five times; a repeating loud alarm is sounded via the speakers of the car, connected via the Bluetooth module of the smartphone.

Architecture

BLOCK DIAGRAM