Real Time Based Driver's Safeguard System by Analyzing Human Physiological Signals
International Journal of Engineering Trends and Technology (IJETT) | |
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© 2013 by IJETT Journal | ||
Volume-4 Issue-1 |
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Year of Publication : 2013 | ||
Authors : Nithin.K.Kurian , D.Rishikesh |
Citation
Nithin.K.Kurian , D.Rishikesh. "Real Time Based Driver's Safeguard System b y Analyzing Human Physiological Signals". International Journal of Engineering Trends and Technology (IJETT). V4(1):41-45 Jan 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
In this paper a new approach based on bio - signal sensing was used for real time accident avoidance. A wireless embedded system with real ti me bio - signal processing technique was proposed. The bio - signals sensor module consists of ECG, EEG, EOG and alcohol sensor. These bio - signals were first acquired by the sensor module .Then the signal is processed and scheduled in the processor with the help of the RTOS installed in it. The processed signal is transmitted to the receiving section by using the wireless data communication. The receiver unit can read the sensor data from wireless receiver module using zig - bee protoc ol. This received real time sensor data is compared with the pre - determined data stored in the processor memory and the decision was taken. This can provide warning to the driver by giving alarm and also having vehicle engine ignition control for stopping the vehicle. The parking light must be turned on before the engine stops so that the driver’s coming behind can control the vehicle and thereby accident can be avoided.
References
[1] Fu - Chang Lin, Li - Wei Ko , Member, IEEE , Chun - Hsiang Chuang, Tung - Ping Su, and Chin - Teng Lin , Fellow,” Generalized EEG - Based Drowsiness Prediction System by Using a Self - Organizing Neural FuzzSystem ”, IEEE Transactions on Circuits and Systems — I: Regular Papers 1. 2012 IEEE.
[2] Chin - Teng Lin , Fellow, IEEE , Ruei - Cheng Wu, Sheng - Fu Liang, Wen - Hung Chao, Yu - Jie Chen, and Tzyy - Ping Jung, “EEG - Based Drowsiness Estimation for Safety Driving Using Independent Component Analysis”, IEEE Transactions on Circuits and Systems — I: Regular Papers, Vol. 52, No. 12, December 2005.
[3] Ulrika Svensson, “ Blink behavior based drowsiness detection – method development and validation” Linkoping 2004
[4] Chin - Teng Lin , Fellow, IEEE , Li - Wei Ko, I - Fang Chung, Teng - Yi Huang, Yu - Chieh Chen, Tzyy - Ping Jung, and Sheng - Fu Liang “Adaptive EEG - Based Alertness Estimation System by Using ICA - Based Fuzzy Neural Networks”, IEEE Transactions on Circuits And Systems — I: Regular Papers, Vol. 53, No. 11, November 2006 2469
[5] Xun Yu “Real - time Nonintrusive Detection of Driver Dr owsiness” Department of Mechanical and Industrial Engineering University of Minnesota Duluth Northland Advanced Transportation Systems Research Laboratories (NATSRL) University of Minnesota Duluth Intelligent Transportation Systems Institute Center for Tra nsportation Studies University of Minnesota.
[6] M. Rimini - Doering, T. Altmueller, and U. Ladstaetter, “Effects of lane departure warning on drowsy drivers’ performance and state in a simulator, “in Proc. 3rd Int. Driving Symp. Human Factors in Driver Ass essment, Training Veh. Design , Rockport, ME, Jun. 27 – 30, 2005, pp.88 – 95
[7] S .K. L. Lal and A .Craig, "Driver Fati gue: Electroencephalography and Psychological Assessment," Psychophysiology, vol. 39, pp. 313 - 321, 2002.
[8] G. Kecklund and T. Åkerstedt , " Sleepiness in long distance truck driving: an ambulatory EEG study of night driving," Ergonomics, vol. 36, pp. 1007 - 1017, 1993.
[9] O. G. Okogbaa, R. L. Shell, and D. Filipusic, "On the investigation of the neurophysiological correlates of knowledge w orker mental fatigue using the EEG signal," Applied Ergonomics, vol. 25, pp. 355 - 365, 1994.
[10] S. K. L. Lal, A. Craig, P. Boord, L. Kirkup, and H. Nguyen, "Development of an algorithm for an EEG - based driver fatigue countermeasure," Journ al of Safety Research, vol. 34, pp. 321 - 328, 2003.
[11] Skipper , J.H. and Wierwillie, W. 1986. Drowsy driver detection using discrimination analysis, Human Factors, 28, 527 - 540.
[12] McGregor, D.K. and Stern, J.A. 1996. Time on task and blink effects on saccade duration, Ergonomics, 39, 649 - 660.
[13] Fukui, T. and Morioka, T. 1971. The blink method as an assessment of fatigue, Ergonomics, 14, 23 - 30.
[14] G. J. S. Wilde and J. F. Stinson, "The monitoring of vigilance in locomotive engineers," A ccident Analysis & Prevention, vol. 15, pp. 87 - 93, 1983.
[15] G. D. Edkins and C. M. Pollock, "The infl uence of sustained attention on Railway accidents," Accident Analysis & Prevention, vol. 29, pp. 533 - 539, 1997.
[16] Skipper, J.H. and Wierwillie, W. 1 986. Drowsy driver detection using discrimination analysis, Human Factors, 28, 527 - 540.
[17] P. S. Rau, “Drowsy driver detection and warning system for commercial vehicle drivers: field operational test design, data analysis, and progress,” National Highw ay Traffic Safety Administration , paper number: 05 - 0192, 2005.
[18] J. Chu, L. Jin, L. Guo, K. Guo, and R. Wang, “Driver’s eye state detecting method design based on eye geometry feature,” 2004 IEEE Intelligent Vehicles Symposium , Parma, Italy,pp.357 - 362, 2004.
[19] R. P. Hamlin, “Three - in - one vehicle operator sensor,” , Transportation Research Board, National Research Council, IDEA program project final report ITS - 18, 1995.
Keywords
ECG, EEG, EOG and alcohol sensor, RTOS, zig - bee protocol.