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Architecture for Internet of Things Analytical Ecosystem

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Dependability Engineering and Complex Systems (DepCoS-RELCOMEX 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 470))

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Abstract

Data analysis is a crucial part of Internet of Things concept. Smart objects generate significant amount of data that should be processed in order to utilize full potential of IoT. The paper presents proposed architecture that enables creating data analysis ecosystem for Internet of Things (IoT). The purpose of that architecture is to separate data analysis problem from orchestration of smart objects. Another important benefit of the ecosystem is to share analysis logic for IoT without revealing analytical algorithms.

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Author information

Authors and Affiliations

  1. Institute of Control and Computation Engineering, Warsaw University of Technology, Warsaw, Poland

    Andrzej Ratkowski

Authors
  1. Andrzej Ratkowski
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Correspondence to Andrzej Ratkowski .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Wojciech Zamojski

  2. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Jacek Mazurkiewicz

  3. Department of Computer Engineering, Wrocław University of Technology, Wroclaw, Poland

    Jarosław Sugier

  4. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Tomasz Walkowiak

  5. Polish Academy of Sciences, Systems Research Institute, Warszawa, Poland

    Janusz Kacprzyk

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© 2016 Springer International Publishing Switzerland

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Ratkowski, A. (2016). Architecture for Internet of Things Analytical Ecosystem. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds) Dependability Engineering and Complex Systems. DepCoS-RELCOMEX 2016. Advances in Intelligent Systems and Computing, vol 470. Springer, Cham. https://doi.org/10.1007/978-3-319-39639-2_34

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  • DOI: https://doi.org/10.1007/978-3-319-39639-2_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39638-5

  • Online ISBN: 978-3-319-39639-2

  • eBook Packages: EngineeringEngineering (R0)

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