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Towards Big Data Analytics in Large-Scale Federations of Semantically Heterogeneous IoT Platforms

  • Ilias Kalamaras
  • Nikolaos Kaklanis
  • Kostantinos Votis
  • Dimitrios Tzovaras
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 520)

Abstract

The technological advances in the Internet-of-Things (IoT) have led to the generation of large amounts of data and the production of a large number of IoT platforms for their management. The abundance of raw data necessitates the use of data analytics in order to extract useful patterns for decision making. Current architectures for big data analytics in the IoT domain address the large volume and velocity of the produced data. However, they do not address the semantic heterogeneity in the data models used by diverse IoT platforms, which emerges when large-scale deployments, spanning across multiple deployment sites, are considered. This paper proposes an architecture for big data analytics in the context of large-scale IoT systems consisting of multiple IoT platforms. A Semantic Interoperability Layer (SIL) handles the interoperability among the data models of the individual platforms, using semantic mappings between them and a unified ontology. Data queries to the SIL and result collection is handled by a cloud-based data management layer, namely the Data Lake, along with storage of metadata needed by data analytics methods. Based on this infrastructure, web-based data analytics and visual analytics methods are used to analyze the collected data, while being agnostic of platform-specific details. The proposed architecture is developed in the context of healthcare provision for older people, although it can be applied to any IoT domain.

Keywords

Internet-of-Things Big data analytics Semantic interoperability Healthy ageing 

Notes

Acknowledgments

This work is supported by the EU funded projects ACTIVAGE (H2020-IOT-2016, grant agreement no. 732679) and FrailSafe (H2020-PHC-2015-single-stage, grant agreement no. 690140).

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Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  • Ilias Kalamaras
    • 1
  • Nikolaos Kaklanis
    • 1
  • Kostantinos Votis
    • 1
  • Dimitrios Tzovaras
    • 1
  1. 1.Information Technologies InstituteCentre for Research and Technology HellasThessalonikiGreece

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