Intelligent Parking System Using Cloud


  • R. Kaudilyar Student, Department of Computer Science, Sathyabama University, Chennai, Tamil Nadu, India
  • Kavitha Esther Rajakumari Asst. Professor, Faculty of Computing, Sathyabama University, Chennai, Tamil Nadu, India



Cloud Computing, Clustering, Intelligent Transportation System, Internet of Things, Vehicular Adhoc Networks and Web Services


Cloud computing is one of the most popular technology in recent time which has dynamically changed the
nature of an organization. Application of cloud computing extends in real time scenarios also. Internet of Things is
another technology which has touched the day to day of human being. Advancement in Cloud computing and Internet of things can be combined and applied for solving real time problem. Allocation of parking slot for vehicles in metro cities is one the real time problem, which has been chosen as the problem statement of our research work. In our research work, we have combined the Internt of Things technology and cloud computing to develop an enhanced intelligent parking system. Overview for developing an Intelligent parking system has been narrated in this paper with an architecuture diagram.


A. Iwai and M. Aoyama, “Automotive cloud service systems based on service-oriented architecture and its evaluation,” in Proc. IEEE Int. Conf. Cloud Computer., Washington, DC, USA, 2011, pp. 638–645.

Y. Zhao, “Telematics: Safe and fun driving,” IEEE Intell. System, vol. 17, no. 1, pp. 10–14, Jan-Feb. 2002.

S. Bitam and A. Mellouk, “ITS-cloud: Cloud computing for intelligent transportation system,” in Proc. IEEE Global Communication. Conference, Anaheim, CA, USA, 2012, pp. 2054–2059.

P. Jaworski, T. Edwards, J. Moore, and K. Burnham, “Cloud computing concept for intelligent transportation systems,” in Proc. 14th Int. IEEE Conf. Intell. Transp. Syst., Washington, DC, USA, 2011, pp. 391–936.

Z. Pang, L. Zheng, J. Tian, S. Kao-Walter, E. Dubrova, and Q. Chen, “Design of a terminal solution for integration of in-home health care devices and services towards the internet-of-things,” Enterprise Inf. System, 2014.

L. Xu, “Enterprise systems: State-of-the-art and future trends,” IEEE Trans. Ind. Information, vol. 7, no. 4, pp. 630–640, Nov. 2011.

S. Li, L. Xu, and X. Wang, “Compressed sensing signal and data acquisition in wireless sensor networks and internet of things,” IEEE Trans. Ind. Information, vol. 9, no. 4, pp. 2177– 2186, Nov. 2013.

Y. Li, M. Hou, H. Liu, and Y. Liu, “Towards a theoretical framework of strategic decision, supporting capability and information sharing under the context of internet of things,” Inf. Technol. Manag., vol. 13, no. 4, pp. 205–216, 2012. [9] D. Lowd and P. Domingos, “Naive Bayes models for probability estimation,” in Proc. 22nd International Conference, Mach. Learn., Bonn, Germany: ACM, 2005, pp. 529–536.

G. Qian, Y. Wu, and Q. Shao, “A procedure for estimating the number of clusters in logistic regression clustering,” J. Classification, vol. 26, no. 2, pp. 183–199, 2009.

Praveen Kumar Rajendran et al, “Hybrid Intrusion detection system for private cloud: A systematic Approach”, in the proceedings of International Conference on Intelligent Computing, Communication &Convergence, December 2014

Wu He, et al, “Developing Vehicular Data Cloud Services in the IoT Environment”, IEEE Transactions on Industrial Informatics, Vol 10, No:2, May 2014.




How to Cite

Kaudilyar, R., & Esther Rajakumari, . K. (2015). Intelligent Parking System Using Cloud. Asian Journal of Computer Science and Technology, 4(1), 18–20.