Research of Intelligent Transportation System Based on the Internet of Things Frame


According to city public transit problem characteristic, the main body of a paper has been submitted and has worked out one kind of based on the Internet of things frame Intelligent transportation system. That system collects data by vehicle terminal and uploads data to the server through the network and makes data visible to the consumer passing an algorithm in the server. One aspect, the consumer may inquire about public transit vehicle information by Web. On another aspect, the consumer can know public transit vehicle information by station terminal. The experiments have tested that the Intelligent transportation system can offer public transit vehicle information to many consumers with convenient way thereby this system can solve the city mass transit problem.

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Y. Wang and H. Qi, "Research of Intelligent Transportation System Based on the Internet of Things Frame," Wireless Engineering and Technology, Vol. 3 No. 3, 2012, pp. 160-166. doi: 10.4236/wet.2012.33023.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Q. Qian, “Google Earth/Maps/KML Kernel Development Technology,” Proceedings of Google Earth/Google Maps the Use of Basic, Public House of Electronics Industry, Beijing, 2010, pp. 23-57.
[2] Y. C. Chen, “Google Maps API Development Guinness,” Proceedings of Development of Google Maps API, China Machine Press, Beijing, 2010, pp. 274-327.
[3] P. Wilton and J. McPeak, “Beginning JavaScript Fourth Edition,” Proceeding of Ajax, Tsinghua University Press, Beijing, 2011, pp. 441-473.
[4] Z. Z. Liu, “ASP.NET Development Guinness,” Proceeding of ASP.NET Operation of the Database, Tsinghua University Press, Beijing, 2011, pp. 270-297.
[5] M. Lee and G. Bieker, “Mastering SQL Server 2008,” Proceeding of SQL Server and .NET Client, Tsinghua University Press, Beijing, 2011, pp. 421-449.
[6] A. Calderon and J. Rumerman, “Advanced ASP. NET AJAX Server Controls For .NET Framework 3.5,” Proceeding of AJAX Control Toolbox, China Machine Press, Beijing, 2009, pp. 334-377.
[7] Z. Y. Li, “LINQ From the Foundation to the Project Deelopment,” Proceeding of LINQ to SQL, Chemical Industry Press, Beijing, 2010, pp. 174-263.
[8] Z. J. Zhu, “Smarter Cloud Computing: The Basic of Internet of Things,” Proceeding of Cloud Computing and Wisdom of the World of Intelligence Operation, Electronics Industry Press, Beijing, 2010, pp. 23-35.
[9] K. Jung, “Beginning Linux Programming,” Proceeding of Extending Linux with Functions, John Wiley & Sons, New York, 2007, pp. 134-342.
[10] P. Bardwell and S. Marr, “Making the Most of Collaboration an International Survey of Public Service Co-Design, DEMOS Report 23,” DEMOS, Price Waterhouse Coopers (PWC) Public Sector Research Centre, London, 2008.
[11] Z. Wall and D. J. Dailey, “An Algorithm for Predicting the Arrival Time of Mass Transit Vehicle Using Automatic Vehicle Location Data,” The 78th Annual Meeting of the Transportation Research Board, Washington, DC, 12 January 1999.
[12] Google Maps API, 2012.
[13] Wikipedia, 2012.
[14] R. Jeong and L. R. Rilett, “Bus Arrival Time Prediction Using Artificial Neural Network Model,” IEEE 7th Intelligent Transportation Systems Conference, Washington DC, 11-15 January 2004, pp. 988-993
[15] W. Li, M. W. Koendjbiharie, R. C. Juca, Y. Yamashita, and A. Maciver, “Algorithms for Estimating Bus Arrival Times Using GPS Data,” IEEE 5th International Conference on Intelligent Transportation Systems, Singapore City, 3-6 September 2002, pp. 868-873.

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