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Intelligent Industrial Systems
Published in: Intelligent Industrial Systems 1/2017

06-03-2017 | Original Paper

A Fast and Simple Drowsiness Detection System Based on ARM Microcontrollers

Authors: F. Hashemzadeh, M. J. Ostadi, B. Mohammadi-ivatloo

Published in: Intelligent Industrial Systems | Issue 1/2017

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Abstract

Drowsiness and fatigue of the drivers are responsible for sever accidents and large human life losses and monetary losses. This paper presents a method based on the image processing for drowsiness detection. Fast and simple algorithms are proposed for face and pupil detection. The proposed method is implemented using a cheap and commercial microcontroller. The implemented device can be calibrated easily for each driver in their first usage. The proposed method is simulated using MATLAB and after getting the satisfactory simulation results, the proposed method is implemented and experimental results are obtained. Using the proposed method, the drowsiness detection system can be used widely in larger communities.
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Literature
1.
Albanese, L.F., Licciardo, G.-D.: High speed CAVLC encoder suitable for field programmable platforms. In: 2010 International Conference on Signals and Electronic Systems (ICSES), IEEE, pp. 327–330 (2010)
2.
Azim, T., Jaffar, M.A., Mirza, A.M.: Automatic fatigue detection of drivers through pupil detection and yawning analysis. In: 2009 Fourth International Conference on Innovative Computing, Information and Control (ICICIC), IEEE, pp. 441–445 (2009)
3.
Azmi, N.: A Driver Fatigue Monitoring and Haptic Jacket-based Warning System. University of Ottawa, Ottawa (2012)
4.
Baronti, F., Lenzi, F., Roncella, R., Saletti, R.: Distributed sensor for steering wheel grip force measurement in driver fatigue detection. In: Proceedings of the Conference on Design, Automation and Test in Europe, pp. 894–897. European Design and Automation Association (2009)
5.
Cerone, V., Chinu, A., Regruto, D.: Experimental results in vision-based lane keeping for highway vehicles. In: Proceedings of the 2002 American Control Conference, IEEE, pp. 869–874 (2002)
6.
Chieh, T.C., Mustafa, M.M., Hussain, A., Zahedi, E., Majlis, B.Y.: Driver fatigue detection using steering grip force. In: Proceedings. Student Conference on Research and Development, SCORED 2003, IEEE, pp. 45–48 (2003)
7.
Dong, W., Wu, X.: Fatigue detection based on the distance of eyelid. In: Proceedings of 2005 IEEE International Workshop on VLSI Design and Video Technology, IEEE, pp. 365–368 (2005)
8.
Facts, T.S.: A compilation of motor vehicle crash data from the fatality analysis reporting system and the general estimates system. Natl. Highway Traffic Saf. Adm. DOT HS 809, 775 (2003)
9.
Gharagozlou, F., et al.: Investigating EEG alpha variations for mental fatigue detection on car driving simulator. J. Ergon. 1, 5–13 (2013)
10.
Hammoud, R.I., Zhang, H.: Alertometer: detecting and mitigating driver drowsiness and fatigue using an integrated human factors and computer vision approach. In: Hammoud, R.I. (ed.) Passive Eye Monitoring, pp. 301–321. Springer (2008)
11.
Horne, J.A., Reyner, L.A.: Driver sleepiness. J. Sleep Res. 4, 23–29 (1995)
12.
Ji, Q., Yang, X.: Real-time eye, gaze, and face pose tracking for monitoring driver vigilance. Real-Time Imaging 8, 357–377 (2002)CrossRefMATH
13.
Li, G., Chung, W.-Y.: Detection of driver drowsiness using wavelet analysis of heart rate variability and a support vector machine classifier. Sensors 13, 16494–16511 (2013)CrossRef
14.
Licciardo, G.D., Albanese, L.F.: Design of a context-adaptive variable length encoder for real-time video compression on reconfigurable platforms. IET Image Process. 6, 301–308 (2012)
15.
Licciardo, G.D., Boesch, T., Pau, D., Di Benedetto, L.: Frame bufferless stream processor for accurate real-time interest point detection. Integr. VLSI J. 54, 10–23 (2016)CrossRef
16.
Lin, C.-T., Wu, R.-C., Liang, S.-F., Chao, W.-H., Chen, Y.-J., Jung, T.-P.: EEG-based drowsiness estimation for safety driving using independent component analysis. IEEE Trans. Circuits Syst. I Regul. Papers 52, 2726–2738 (2005)CrossRef
17.
Maycock, G.: Driver sleepiness as a factor in car and HGV accidents. TRL Report (1995)
18.
McCartt, A.T., Ribner, S.A., Pack, A.I., Hammer, M.C.: The scope and nature of the drowsy drivingproblem in New York state. Accid. Anal. Prev. 28, 511–517 (1996)CrossRef
19.
Nahvi, A., Azadi, S., Niknejad, M., Sadeghi, A.: Drowsy driving analysis based on steering & lane position variables using passenger driving simulator. Modares Mech. Eng. 14 (2014)
20.
Parmar, N.: Drowsy driver detection system. Engineering Design Project Thesis, Ryerson University (2002)
21.
Saradadevi, M., Bajaj, P.: Driver fatigue detection using mouth and yawning analysis. Int. J. Comput. Sci. Netw. Secur. 8, 183–188 (2008)
22.
Solaz, J., de Rosario, H., Gameiro, P., Bande, D.: Drowsiness and fatigue sensing system based on driver’s physiological signals. In: Transport Research Arena (TRA) 5th Conference: Transport Solutions from Research to Deployment (2014)
23.
Tripathy, B.N., Dash, A.: Prototype drowsiness detection system. PhD dissertation, National Institute of Technology Rourkela (2012)
24.
Wierwille, W.W.: Overview of research on driver drowsiness definition and driver drowsiness detection. In: Proceedings: International Technical Conference on the Enhanced Safety of Vehicles, pp. 462–468. National Highway Traffic Safety Administration (1995)
Metadata
Title
A Fast and Simple Drowsiness Detection System Based on ARM Microcontrollers
Authors
F. Hashemzadeh
M. J. Ostadi
B. Mohammadi-ivatloo
Publication date
06-03-2017
Publisher
Springer Singapore
Published in
Intelligent Industrial Systems / Issue 1/2017
Print ISSN: 2363-6912
Electronic ISSN: 2199-854X
DOI
https://doi.org/10.1007/s40903-017-0069-x

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