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

  1. Yuichi Saito, Makoto Itoh, Toshiyuki Inagaki, "Driver Assistance System With a Dual Control Scheme: Effectiveness of Identifying Driver Drowsiness and Preventing Lane Departure Accidents" IEEE Transactions on Human-Machine Systems March 21, 2016.
  2. D. Tran, E. Tadesse and W. Sheng, Y. Sun, M. Liu and S. Zhang, "A Driver Assistance Framework Based on Driver Drowsiness Detection" The 6th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems June 19-22, 2016.
  3. A. Mittal, K. Kumar, S. Dhamija, M. Kaur "Head Movement-Based Driver Drowsiness Detection: A Review of State-of-Art Techniques" 2nd IEEE International Conference on Engineering and Technology(ICETECH) March 17-18, 2016.
  4. Alesandar, Oge Marques and BorkoFurht "Design and Implementation of a Driver Drowsiness Detection System A Practical Approach".
  5. Anjali K U, Athiramol K Thampi, AthiraVijayaraman, Franiya Francis M, Jeffy James N, Bindhu K Rajan " Real-Time Nonintrusive Monitoring and Detection of Eye Blinking in View of Accident Prevention Due to Drowsiness" 2016 International Conference on Circuit ,Power and Computing TechnologiesICCPCT].
  6. J. Ahmed, Jain–Ping Li, S. Ahmed Khan, R. Ahmed Shaikh "Eye Behavior Based Drowsiness Detection System".
  7. A. Rahman, M. Sirshar, A. Khan "Real Time Drowsiness Detection Using Eye Blink Monitoring" 2015 National Software Engineering Conference(NSEC 2015).
  8. NilaNovita Sari and Yo-Ping Haung "A Two-Stage Intelligent Model To Extract Features From PPG for Drowsiness Detection" 2016 International Conference on System Science and Engineering (ICSSE) National Chi Nan University July 7-9, 2016.
  9. Jian-Da Wu, Tuo Rung Chen, ?Development of a drowsiness warning system based on the fuzzy logic images analysis?, Elsevier, Expert System with Applications, vol.34, pp.1556-1561, 2008
  10. Vijayalaxmi, D.Elizabeth Rani, ?Eye state Detection Using Image Processing Technique?,ajer, vol.04, pp.44-48, 2015
  11. Nidhi Sharma, Prof. V.K. Banga, ?Development of a Drowsiness Warning System based on the fuzzy logic?, International journal of Computer Applications (0975-8887) vol.8, 2010
  12. Itenderpal Singh, V.K. Banga, ?DevelopmentOf A Drowsiness Warning System UsingNeural Networks?, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol.2, pp.36143623, August 2013
  13. K. Dwivedi, K. Biswaranjan, A. Sethi, ?Drowsy driver detection using representation learning?, IEEE, International Advance Computing Conference, pp.995-999, Feb-2014

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.
Journal URL : http://ijsrcseit.com/CSEIT1835115

Follow Us

Contact Us