The week's pick
Reseach Article
WSN based Cost Effective Intelligent Traffic Light Control System based on Image Processing
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 132 - Number 7 |
| Year of Publication: 2015 |
| Authors: Anuradha G. Suratekar, Uttam L. Bombale |
10.5120/ijca2015907583
|
Anuradha G. Suratekar, Uttam L. Bombale . WSN based Cost Effective Intelligent Traffic Light Control System based on Image Processing. International Journal of Computer Applications. 132, 7 ( December 2015), 47-50. DOI=10.5120/ijca2015907583
Abstract
In this paper image processing based intelligent traffic light control system is designed. Inductive loop method is mostly used for traffic detection. But it is physically large, hard to install and maintain. Present system has fixed timing for traffic control so the present traffic system is not much efficient to manage or control the traffic. Also inductive loops cannot communicate with each other. The wireless sensor network (WSN) has features like fault tolerance, scalability, real-time, and coordination. So the traffic light control system as per the traffic density with WSN has been designed in this paper. C++ programming language is used for simulation.
References
- L. A. Klein, M. R. Kelley, M. K. Mills, “Evaluation of overhead and in-ground vehicle detector technologies for traffic flow measurement,” Journal of Testing and Evaluation, 25(2): pp.205- 214, 1997.
- K. Tavladakis, N. C. Voulgaris, “Development of an autonomous adative traffic control system,” in Proc. European Symposium on Intelligent Techniques, 1999.
- A. Albagul, M. Hrairi, Wahyudi, M. F. Hidayathullah, “Design and development of sensor based traffic light system,” American Journal of Applied Sciences, 3(3): pp.1745-1749, 2006.
- Shwe Yi Aye, “Design and construction of LAN based car traffic control system,” in Proc. WASET, 2008.
- Khalid A. S. Al-Khateeb, Jaiz A. Y. Johari, Wajdi F. Al-Khateeb, “Dynamic traffic light sequence algorithm using RFID,” Journal of Computer Science, 4(7): pp.517-524, 2008.
- Li JianZhong, Li JinBao, Shi ShengFei, “Concepts, Issues and Advance of Sensor Networks and Data Management of Sensor Networks,” Journal of Software, vol. 14, no. 10, pp. 1717-1727, 2003
- D. Abbott, S. Cunningham, G. Daniels, B. Doyle, J. Dumlop, D. Economo, T. Farmer, D. Farrant, C. Foley, B. Fox, M. Hedley, J. Herrmann, C. Jacka, “Development and Evaluation of Sensor Concepts for Ageless Aerospace Vehicles – Threats and Measurands,” NASA, vo. 2, no. 11, pp. 68-77, 2002.
- S. Deshpand, "Adaptative low-bitrate streaming over IEEE 802.15.4 low rate wireless personal area networks (LR-WPAN) based on link quality indication", International Conference on Communication and Mobile Computing, pp. 863-868, 2006.
- G. Pekhterverv et. al "Image Transmission over IEEE 802.15.4 and ZigBee Networks" IEEE International Symposium on Circuits and Systems, Vol.4, pp.3539-3543, 2005
- Uichin Lee, Mario Gerla. “A survey of urban vehicular sensing platforms” Computer Networks 54 (2010) 527–544.
- Abhijit Sharma, Rituparna Chaki, Uma Bhattacharya. “Applications of WSN in ITS: A Review”. ICECT11.
- CANNY, J. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 6 (1986), 679-686.
- NIXON, M. S., AND AGUADO, A. S. Feature Extraction and Image Processing, second ed. Elsevier, New York, 2008.
- The OpenCV Reference Manual.
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