Smart Drivers’ Guidance System Based on IoT Technologies for Smart Cities Application

  • Imen Masmoudi
  • Wiam Elleuch
  • Ali Wali
  • Adel M. Alimi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10334)


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.


Global Position System Traffic Congestion Smart City Global Position System Data Parking Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



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.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Imen Masmoudi
    • 1
  • Wiam Elleuch
    • 1
  • Ali Wali
    • 1
  • Adel M. Alimi
    • 1
  1. 1.REGIM-Lab: Research Groups in Intelligent Machines, National Engineering School of SfaxUniversity of SfaxSfaxTunisia

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