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Drowsiness Detection and Parking Assistance for Drivers

Alagu Meyyappan Kailasam *, Ayikumar Mohan **, Devi K. ***, Benjamin Felix Prabhakar ****

*-**** Department of Computer Science and Engineering, SRM Valliammai Engineering College, Kattankulathur, Tamilnadu, India.

Periodicity:July - December'2020
DOI : https://doi.org/10.26634/jic.8.2.18168

Abstract

Traffic on road has increased considerably due to active economy, especially in developing countries. Road accidents have increased with the increasing traffic. Driver fatigue causes around 30% of road accidents. Drowsiness may be caused by restless driving, health issues, extended working hours, etc. Therefore, for road safety, drowsiness of the driver needs to be detected and alerted, and at extreme conditions the vehicle may be parked using assisted parking system. Technology is available through cost effective devices which are simple to be integrated with other systems. This paper proposes a system that uses camera and other devices to achieve the goal. The proposed system will analyze the changes that happen in the face of the driver and process them through a program to detect drowsiness. A prototype will be developed and tested on real time to understand the efficiency of the proposed concept.

Keywords

Drowsiness, Image Processing, Fatigue Detection, Matlab.

How to Cite this Article?

Kailasam, A. M., Mohan, A., Devi, K., and Prabhakar, B. F. (2020). Drowsiness Detection and Parking Assistance for Drivers. i-manager's Journal on Instrumentation and Control Engineering, 8(2), 24-28. https://doi.org/10.26634/jic.8.2.18168

References

[1]. Alioua, N., Amine, A., & Rziza, M. (2014, August). Driver's fatigue detection based on yawning extraction. International Journal of Vehicular Technology, 2014, Article ID: 678786. https://doi.org/10.1155/2014/678786

[2]. Chieh, T. C., Mustafa, M. M., Hussain, A., Hendi, S. F., & Majlis, B. Y. (2005, November). Development of vehicle driver drowsiness detection system using electrooculogram (EOG). In 2005, 1^st International Conference on Computers, Communications, & Signal Processing with Special Track on Biomedical Engineering (pp. 165-168). IEEE. https://doi. org/10.1109/CCSP.2005.4977181

[3]. Gander, P. H., Nguyen, D. E., Rosekind, M. R., & Connell, L. J. (1993). Age, circadian rhythms, and sleep loss in flight crews. Aviation, Space, and Environmental Medicine. 64(3), 189-195.

[4]. Hartley, L., Horberry, T., Mabbott, N., & Krueger, G. P. (2000). Review of fatigue detection and prediction technologies. [Report], National Road Transport Commission, Australia. 1-41.

[5]. Kaplan, S., Guvensan, M. A., Yavuz, A. G., & Karalurt, Y. (2015). Driver behavior analysis for safe driving: A survey. IEEE Transactions on Intelligent Transportation Systems, 16(6), 3017-3032. https://doi.org/10.1109/TITS.2015.24620 84

[6]. Parande, G.D., Khade P.M., Kolpe, S.B., & Gavande, U.R. (2017). Intelligent braking system by using microcontroller and sensor, International Journal of Advance Research in Engineering, Science & Technology, 4(3), 489-493.

[7]. Ram, J., & Kumar, B. (2017). Automatic braking system using ultrasonic sensor. International Journal of Innovative Science and Research Technology, 2(4), 2456 – 2165

[8]. Triyanti, V., & Iridiastadi, H. (2017, December). Challenges in detecting drowsiness based on driver's behavior. In IOP Conference Series: Materials Science and Engineering (Vol. 277, No. 1, p. 012042). IOP Publishing. https://doi.org/10.1088/1757-899X/277/1/012042

[9]. Vargas-Cuentas, N. I., & Roman-Gonzalez, A. (2017, August). Facial image processing for sleepiness estimation. In 2017, 2^nd International Conference on Bioengineering for Smart Technologies (BioSMART) (pp. 1-3). IEEE.

[10]. Wang, T., & Shi, P. (2005, May). Yawning detection for determining driver drowsiness. In Proceedings of 2005 IEEE International Workshop on VLSI Design and Video Technology (pp. 373-376). IEEE. https://doi.org/10.1109/ IWVDVT.2005.1504628

[11]. Yang, S., Xi, J., & Wang, W. (2019, September). Driver drowsiness detection through a vehicle's active probe action. In 2019, IEEE 2^nd Connected and Automated Vehicles Symposium (CAVS) (pp. 1-7). IEEE. https://doi.org/ 10.1109/CAVS.2019.8887773

[12]. Yauri-Machaca, M., Meneses-Claudio, B., Vargas- Cuentas, N., & Roman-Gonzalez, A. (2018, November). Design of a vehicle driver drowsiness detection system through image processing using Matlab. In 2018, IEEE 38^th Central America and Panama Convention (CONCAPAN XXXVIII) (pp. 1-6). IEEE. https://doi.org/10.1109/CONCAPAN. 2018.8596513

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Online	200	35	35	200	15
Pdf	35	35	200	20
Pdf & Online	35	35	400	25

Drowsiness Detection and Parking Assistance for Drivers

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