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An Artificial Intelligence Based Forecasting in Smart Parking with IoT

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2018, ruSMART 2018)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11118))

Abstract

Internet of Things (IoT) enables Smart Cities (SC) with novel services for the citizens’ well-being. A Smart Parking (SP) system is an important part of the SC infrastructure, which enables the efficient handling of the demanding SC traffic congestion conditions. Such a system also protects the urban environment towards a green ecosystem. In this paper, we consider Artificial Intelligence (AI) algorithms towards processing of data produced by parking lots and disseminated by IoT technology in the SC of St. Petersburg in Russia. Such algorithms enhance the proposed SP system to predict the number of unoccupied parking lots within the SC parking places. In addition, the SP system uses vehicle navigation to decide the optimal parking place according the current vehicle location and the availability of parking lots in the SC.

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Acknowledgments

Part of this work has been carried out in the scope of the project bIoTope which is co-funded by the European Commission under the Horizon-2020 program, contract number H2020-ICT-2015/688203 – bIoTope. The research has been carried out with the financial support of the Ministry of Education and Science of the Russian Federation under grant agreement RFMEFI58716X0031.

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Authors and Affiliations

  1. Department of Infocommunication Technologies, ITMO University, 197101, Saint Petersburg, Russia

    Petr Fedchenkov, Theodoros Anagnostopoulos, Arkady Zaslavsky, Inna Sosunova & Oleg Sadov

  2. CSIRO Computational Informatics, CSIRO, Box 312, Perth, VIC, 3169, Australia

    Arkady Zaslavsky

  3. Department of Business and Marketing, University of West Attica, Athens, Greece

    Theodoros Anagnostopoulos & Klimis Ntalianis

Authors
  1. Petr Fedchenkov
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  2. Theodoros Anagnostopoulos
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  3. Arkady Zaslavsky
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  4. Klimis Ntalianis
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  5. Inna Sosunova
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  6. Oleg Sadov
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Corresponding author

Correspondence to Petr Fedchenkov .

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Editors and Affiliations

  1. Tampere University of Technology, Tampere, Finland

    Olga Galinina

  2. Tampere University of Technology, Tampere, Finland

    Sergey Andreev

  3. FRUCT Oy, Helsinki, Finland

    Sergey Balandin

  4. Tampere University of Technology, Tampere, Finland

    Yevgeni Koucheryavy

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Fedchenkov, P., Anagnostopoulos, T., Zaslavsky, A., Ntalianis, K., Sosunova, I., Sadov, O. (2018). An Artificial Intelligence Based Forecasting in Smart Parking with IoT. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2018 2018. Lecture Notes in Computer Science(), vol 11118. Springer, Cham. https://doi.org/10.1007/978-3-030-01168-0_4

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  • DOI: https://doi.org/10.1007/978-3-030-01168-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01167-3

  • Online ISBN: 978-3-030-01168-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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