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Enriching a Situation Awareness Framework for IoT with Knowledge Base and Reasoning Components

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Modeling and Using Context (CONTEXT 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10257))

Abstract

The importance of system-level context- and situation awareness increases with the growth of the Internet of Things (IoT). This paper proposes an integrated approach to situation awareness by providing a semantically rich situation model together with reliable situation inference based on Context Spaces Theory (CST) and Situation Theory (ST). The paper discusses benefits of integrating the proposed situation awareness framework with knowledge base and efficient reasoning techniques taking into account uncertainty and incomplete knowledge about situations. The paper discusses advantages and impact of proposed context adaptation in dynamic IoT environments. Practical issues of two-way mapping between IoT messaging standards and CST are also discussed.

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Notes

  1. 1.

    Ellen MacArthur Foundation, Report on Intelligent Assets: https://www.ellenmacarthurfoundation.org/publications/intelligent-assets.

  2. 2.

    SAN ontology: https://www.irit.fr/recherches/MELODI/ontologies/SAN.owl.

  3. 3.

    bIoTope project: http://www.biotope-project.eu/.

  4. 4.

    Open-Messaging Interface: https://www2.opengroup.org/ogsys/catalog/C14B.

  5. 5.

    Open-Data Format: https://www2.opengroup.org/ogsys/catalog/C14A.

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Acknowledgment

Part of this work has been carried out in the scope of the project bIoTope which is co-funded by the European Commission under 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. Interdisciplinary Center for Security, Reliability and Trust, University of Luxembourg, 4 Rue Alphonse Weicker, 2721, Luxembourg, Luxembourg

    Niklas Kolbe, Sylvain Kubler, Jérémy Robert & Yves Le Traon

  2. Commonwealth Scientific and Industrial Research Organisation, Data61, Clayton, VIC, 3168, Australia

    Arkady Zaslavsky

  3. Saint Petersburg National Research University of ITMO, 49 Kronverksky Pr., St. Petersburg, 197101, Russia

    Arkady Zaslavsky

Authors
  1. Niklas Kolbe
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  2. Arkady Zaslavsky
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  3. Sylvain Kubler
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  4. Jérémy Robert
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  5. Yves Le Traon
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Corresponding author

Correspondence to Niklas Kolbe .

Editor information

Editors and Affiliations

  1. Pierre and Marie Curie University , Paris, France

    Patrick Brézillon

  2. University of Maine , Orono, Maine, USA

    Roy Turner

  3. University of Genoa , Genoa, Italy

    Carlo Penco

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Kolbe, N., Zaslavsky, A., Kubler, S., Robert, J., Le Traon, Y. (2017). Enriching a Situation Awareness Framework for IoT with Knowledge Base and Reasoning Components. In: Brézillon, P., Turner, R., Penco, C. (eds) Modeling and Using Context. CONTEXT 2017. Lecture Notes in Computer Science(), vol 10257. Springer, Cham. https://doi.org/10.1007/978-3-319-57837-8_4

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  • DOI: https://doi.org/10.1007/978-3-319-57837-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57836-1

  • Online ISBN: 978-3-319-57837-8

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