Implementation of Vehicle Detection System Using WSN

Article Preview

Abstract:

Vehicle Detection System plays a basic role in the field of intelligent transportation, and is the cornerstone of constructing modern intelligent transportation system. This paper presents a new vehicle detection algorithm using WSN that called the adaptive state machine. The algorithm can adaptively update the threshold and baseline; use the state machine to achieve the aim of the accurate and efficient vehicle detection. It can be used for the detection of road traffic flow, and can be used in large parking vehicle guidance system. On the road, we have deployed 76 Sensor Nodes to evaluate the performance. We observe the accurate of the road vehicle detection rate of vehicle detection system is nearly 98%.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1459-1464

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] A. Haoui, R. Kavaler, and P. Varaiya: submitted to Emerging Technologies (2008).

Google Scholar

[2] L. M. Sun, J. Z. Li: Wireless Sensor Network (Tsinghua University Press, China 2005).

Google Scholar

[3] C. J. Caruso, L. S. Withamwasam: Sens Expo Proc. Vol. 477-488 (1999).

Google Scholar

[4] S. S. Jiang in: Research and Design of WSN-based Vehicle Detection System, edited by Graduate School of National University of Defense Technology (2009) in Chinese.

Google Scholar

[5] J. Ding, S. Y. Cheung, C. W. Tan, in: Signal processing of sensor node data for vehicle detection, edited by the 7th IEEE ITSC (2004).

Google Scholar

[6] G. Padmavathi, D. Shanmugapriya, M. Kalaivani, in: Wireless Sensor Network (2010).

Google Scholar

[7] S. Y. Cheung, S. C. Ergen, P. Varaiya: University of California, Berkeley. Vol. 1917 (2005), p.4779.

Google Scholar

[8] J. J. Yoo, D. H. Kim, J. H. Park, in: Design and implementation of magnetic sensor network for detecting automobiles, edited by the 35th IEEE LCN (2010).

DOI: 10.1109/lcn.2010.5735835

Google Scholar