Smart Drivers’ Guidance System Based on IoT Technologies for Smart Cities Application
Finding an available parking place is becoming an exhaustive task due to the increasing amount of cars and vehicles, especially in the metropolitan cities. The search for an available parking place through the roads and parking stations is a major waste of time and efforts, mainly in pic hours when parking places are almost full. This problem can be felt mainly around city centres, hospitals, shopping complexes and many other crowded stations and roads. This can also accentuate the problem of traffic congestion and aggravate the task of the drivers.
In this paper, we propose a smart multi agent parking management system exploring the Internet of Things (IoT) technologies and aiming at providing smart urban service to the citizens. The presented system supplies the drivers with the real time information about the availability of parking spaces through the parking stations, and ensures the task of guidance through the roads. In addition to the parking availability, our system takes into consideration the factor of traffic congestion, while guiding the drivers. We collect the Global Positioning System (GPS) data from the already circulating vehicles through the town and we exploit the real time information to improve our system of guidance.
KeywordsGlobal Position System Traffic Congestion Smart City Global Position System Data Parking Space
The authors would like to acknowledge the financial support of this work by grants from General Direction of Scientific Research (DGRST), Tunisia, under the ARUB program.
The research and innovation are performed in the framework of a thesis MOBIDOC financed by the EU under the program PASRI.
- 1.Ahrnbom, M., Strm, K., Nilsson, M.: Fast classification of empty and occupied parking spaces using integral channel features. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1609–1615, June 2016Google Scholar
- 2.Amato, G., Carrara, F., Falchi, F., Gennaro, C., Vairo, C.: Car parking occupancy detection using smart camera networks and deep learning. In: 2016 IEEE Symposium on Computers and Communication (ISCC), pp. 1212–1217, June 2016Google Scholar
- 3.Elleuch, W., Wali, A., Alimi, A.M.: Mining road map from big database of GPS data. In: 2014 14th International Conference on Hybrid Intelligent Systems, pp. 193–198, December 2014Google Scholar
- 4.Elleuch, W., Wali, A., Alimi, A.M.: Collection and exploration of GPS based vehicle traces database. In: 2015 4th International Conference on Advanced Logistics and Transport (ICALT), pp. 275–280, May 2015Google Scholar
- 5.Grodi, R., Rawat, D.B., Rios-Gutierrez, F.: Smart parking: parking occupancy monitoring and visualization system for smart cities. In: SoutheastCon 2016, pp. 1–5, March 2016Google Scholar
- 6.Khanna, A., Anand, R.: IoT based smart parking system. In: 2016 International Conference on Internet of Things and Applications (IOTA), pp. 266–270, January 2016Google Scholar
- 8.Masmoudi, I., Wali, A., Alimi, A.M.: Parking spaces modelling for inter spaces occlusion handling. In: 22nd International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, pp. 119–124, June 2014Google Scholar
- 9.Masmoudi, I., Wali, A., Jamoussi, A., Alimi, A.M.: Trajectory analysis for parking lots vacancy detection system. IET Intell. Transp. Syst. (2014)Google Scholar
- 10.Masmoudi, I., Wali, A., Jamoussi, A., Alimi, A.M.: Architecture of parking lots management system for drivers’ guidance. In: IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015, pp. 2974–2978, October 2015Google Scholar
- 11.Masmoudi, I., Wali, A., Jamoussi, A., Alimi, A.M.: Vision based parking lot management system with anomalies detection while parking. In: IET Computer Vision (2015)Google Scholar
- 12.Oh, S., Hoogs, A., Perera, A., Cuntoor, N., Chen, C.C., Lee, J.T., Mukherjee, S., Aggarwal, J.K., Lee, H., Davis, L., Swears, E., Wang, X., Ji, Q., Reddy, K., Shah, M., Vondrick, C., Pirsiavash, H., Ramanan, D., Yuen, J., Torralba, A., Song, B., Fong, A., Roy-Chowdhury, A., Desai, M.: A large-scale benchmark dataset for event recognition in surveillance video. In: CVPR (2011)Google Scholar
- 13.Ramaswamy, P.: Iot smart parking system for reducing green house gas emission. In: 2016 International Conference on Recent Trends in Information Technology (ICRTIT), pp. 1–6, April 2016Google Scholar
- 14.Tsai, M.F., Kiong, Y.C., Sinn, A.: Smart service relying on internet of things technology in parking systems. J. Supercomput., 1–24 (2016). http://dx.doi.org/10.1007/s11227-016-1875-8
- 15.Tsaramirsis, G., Karamitsos, I., Apostolopoulos, C.: Smart parking: an IoT application for smart city. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), pp. 1412–1416, March 2016Google Scholar
- 16.Valipour, S., Siam, M., Stroulia, E., Jägersand, M.: Parking stall vacancy indicator system based on deep convolutional neural networks. CoRR abs/1606.09367 (2016)Google Scholar