Monitoring Behaviour of Driver Through Sensors and Location of Accident Through Wireless Technology

Sowmya*, I. Suneetha**, N. Pushpalatha***
*** Assistant Professor, Department of ECE, Annamacharya Institute of Technology and Sciences, Tirupati, India.
Periodicity:February - April'2014
DOI : https://doi.org/10.26634/jes.3.1.2949

Abstract

A large number of serious or fatal accidents are occurred due to excessive or inappropriate speed of the vehicle. Distraction and drowsiness of the driver has been important factors for a large number of major accidents. They reduce the decision making capability and perception level of the driver which negatively affect the ability of the driver to control the vehicle. Monitoring the driver behavior is one of the ways to prevent the fatal accidents and it is necessary to alert the driver when they are drowsy or in a distracted state. With the new developed systems, there is a possibility of self controlling the vehicle when the driver was drunk or reckless or fatigue so that major accidents may be reduced. There is also a possibility of tracking the location of accident, if occurs, through Wireless Access Technology (GSM, GPS) so that proper measures are taken at correct time.

Keywords

Artificial Neural Networks, Driver Behavior, Global Position System (GPS), Global System for Mobile (GSM),

How to Cite this Article?

Sowmya., Suneetha., and Pushpalatha. (2014). Monitoring Behaviour Of Driver Through Sensors And Location Of Accident Through Wireless Technology. i-manager’s Journal on Embedded Systems, 3(1), 12-18. https://doi.org/10.26634/jes.3.1.2949

References

[1]. N. Xu, (2002). “A survey of sensor network applications,” IEEE Commun. Mag., Vol. 40, No. 8, pp. 1–9.
[2]. Q. Ji, Z. Zhu, P. Lan, (2004). “Real-Time Nonintrusive Monitoring and Prediction of Driver Fatigue,” IEEE Transactions on Vehicular Technology, Vol. 53.
[3]. H. Singh, J. S. Bhatia, and J. Kaur, (2005), “Eye tracking based driver fatigue monitoring and warning system,” in Proc. IEEE IICPE, New Delhi, India, pp. 1-6.
[4]. P. Bouchner, R. Pieknik, S. Novontny, J. Pekny, M. Hajny, and C. Borzová, (2006). “Fatigue of car drivers - detection and classification based on experiments on car simulators,” in Proc. 6th Int. Conf. Simul., Model., Optim., Lisbon, Portugal,pp. 727–732.
[5]. J. C. McCall and M. M. Trivedi, (2007). “Driver behavior and situation aware brake assistance for intelligent vehicles,” in Proceedings of the IEEE, Vol. 95, No. 2.
[6]. M. S. Devi and P. R. Bajaj, (2008). “Driver fatigue detection based on eye tracking,” in Proc. IEEE ICETET, Nagpur, Maharashtra, pp. 649 –652.
[7]. E. Rogado, J. Garcia, R. Barea, L. Bergasa and E. Lopez, (2009). “Driver Fatigue Detection System,” Proc. IEEE Int. Conf. Robotics and Biomimetics, 2009.
[8]. Y. Liang, (2009). “Detecting driver distraction,” Ph. D thesis, University of Iowa.
[9]. B. Yin, X. Fan, Y. Sun, (2009). “Multiscale dynamic features based Driver fatigue detection,” Int. J. Pattern Recogn. Artif. Intell. Vol 23, No 575–589.
[10]. J. Dai, J. Teng, X. Bai, Z. Shen, and D. Xuan, (2010). “Mobile phone based drunk driving detection,” in Proc. IEEE Pervasive Health No Permissions, Munich, Germany, pp. 1-8.
[11]. M. Jabon, J. Bailenson, E. Pontikakis, L. Takayama, and C. Nass, (2011). “Facial-Expression Analysis for Predicting Unsafe Driving Behavior,” Per vasive Computing, 10(4), 84-95.
[12]. Boon-Giin Lee and Wan-Young Chung, (2012). “Driver Alertness Monitoring Using Fusion of Facial Features and Bio- Signals”, Member, IEEE Sensors Journal, Vol. 12, No. 7.
[13]. B. Hariri, S. Abtahi, S. Shirmohammadi, and L. Martel, (2012). “A Yawning Measurement method to Detect Driver Drowsiness,” Technical Papers, 2012.
[14]. A. Sahyadehas, K. Sundaraj and M. Murugappan, (2013). “Detecting Driver Drowsiness based on Sensors: A Review,” Sensors, 12(12), 16937-16953.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Online 15 15

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.