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EAI International Conference on IoT Technologies for HealthCare

HealthyIoT 2018: 5th EAI International Conference on IoT Technologies for HealthCare pp 39–54Cite as

Identification of IoT Medical Devices APIs Through Ontology Mapping Techniques

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Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

The Internet of Things (IoT) is being hailed as the next industrial revolution, dealing with billions of heterogeneous devices that are connected over the Internet. In this context, both devices’ integration and their derived data integration are among the most complicated tasks that need to be addressed, especially in the healthcare domain. Despite the critical importance, the current approaches for confronting heterogeneity of IoT medical devices have not been sufficiently effective. For that reason, in this paper a generic mechanism is presented for managing the huge amounts of heterogeneous IoT medical devices that exist in combination with their derived data, by understanding the nature and the meaning of the Application Programming Interfaces (API) methods of these devices that are responsible for gathering data out of them. In order to achieve the latter, the mechanism understands the nature and the meaning of these API methods by translating them into ontologies, while identifying and mapping the syntactic and semantic similarities among them, so as to recognize and use the ones that are responsible for gathering the devices’ data, and finally integrate it into different platforms. The proposed mechanism is evaluated through a specific use case, producing reliable results, thus being considered as a reference value of high quality and accuracy.

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Acknowledgements

The CrowdHEALTH project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 727560.

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Authors and Affiliations

  1. Department of Digital Systems, University of Piraeus, Piraeus, Greece

    Argyro Mavrogiorgou, Athanasios Kiourtis & Dimosthenis Kyriazis

Authors
  1. Argyro Mavrogiorgou
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  2. Athanasios Kiourtis
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  3. Dimosthenis Kyriazis
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Corresponding author

Correspondence to Argyro Mavrogiorgou .

Editor information

Editors and Affiliations

  1. Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal

    Pedro R. M. Inácio

  2. Department of Health Sciences, Universidade da Beira Interior, Covilhã, Portugal

    Ana Duarte

  3. Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal

    Paulo Fazendeiro

  4. Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal

    Nuno Pombo

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Mavrogiorgou, A., Kiourtis, A., Kyriazis, D. (2020). Identification of IoT Medical Devices APIs Through Ontology Mapping Techniques. In: Inácio, P., Duarte, A., Fazendeiro, P., Pombo, N. (eds) 5th EAI International Conference on IoT Technologies for HealthCare. HealthyIoT 2018. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-30335-8_4

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  • DOI: https://doi.org/10.1007/978-3-030-30335-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30334-1

  • Online ISBN: 978-3-030-30335-8

  • eBook Packages: EngineeringEngineering (R0)

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