An Efficient Drowsiness Detection System For Pilot Using Wearable Body Sensor Networks

Authors(2) :-Sharmila B, Arafatabudullah A

Driver drowsiness detection is a car safety technology which helps prevent accidents caused by the driver getting drowsy. Various studies have suggested that around 20% of all road accidents are fatigue-related, up to 50% on certain roads. Negative emotional responses are a growing problem among drivers, particularly in countries with heavy traffic, and may lead to serious accidents on the road. The focus of this study was to develop and verify an emotional response-monitoring paradigm for drivers, derived from Respiration signals, photoplethysmography signals, and eye blink signal. The relevant sensors were connected to a microcontroller unit equipped with a ZIGBEE-enabled low energy module, which allows the transmission of those sensor readings to a vehicle. When drowsiness is detected in driver then the driving mode is automatically going to automatic mode for driving using image processing and sent information to the transport department officer using GSM.

Authors and Affiliations

Sharmila B
Master's Program in VLSI in Vandayar engineering college, Thanjavur, Tamilnadu, India
Arafatabudullah A
Assistant Professor of ECE in Vandayar engineering college,Thanjavur, Tamilnadu, India

Negative emotion, Roadway accident, Stress, Wearable system, PPG, ZIGBEE, GSM

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Publication Details

Published in : Volume 3 | Issue 5 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 496-502
Manuscript Number : CSEIT1835115
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sharmila B, Arafatabudullah A, "An Efficient Drowsiness Detection System For Pilot Using Wearable Body Sensor Networks", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.496-502, May-June-2018. |          | BibTeX | RIS | CSV

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