Connecting IoT Sensors to Knowledge-Based Systems by Transforming SenML to RDF

Xiang Su, Hao Zhang, Jukka Riekki, Ari Keränen, Jukka K. Nurminen, Libin Du

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    30 Citations (Scopus)
    116 Downloads (Pure)

    Abstract

    Applying Semantic Web technologies to Internet of Things (IoT) enables smart applications and services in a variety of domains. However, the gap between semantic representations and data formats used in IoT devices introduces a challenge for utilizing semantics in IoT. Sensor Markup Language (SenML) is an emerging solution for representing device parameters and measurements. SenML is replacing proprietary data formats and is being accepted by more and more vendors. In this paper, we suggest a solution to transform SenML data into a standardized semantic model, Resource Description Framework (RDF). Such a transformation facilitates intelligent functions in IoT, including reasoning over sensor data and semantic interoperability among devices. We present a fishery IoT system to illustrate the usability of this approach and compare the resource consumptions of SenML against other alternatives.
    Original languageEnglish
    Title of host publication5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), Hasselt, Belgium, 2-5 June, 2014
    PublisherElsevier
    Pages215–222
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA4 Article in a conference publication
    EventInternational Conference on Ambient Systems, Networks and Technologies - Hasselt, Belgium
    Duration: 2 Jun 20145 Jun 2014
    Conference number: 5

    Publication series

    NameProcedia Computer Science
    PublisherElsevier
    Volume32
    ISSN (Electronic)1877-0509

    Conference

    ConferenceInternational Conference on Ambient Systems, Networks and Technologies
    Abbreviated titleANT
    CountryBelgium
    CityHasselt
    Period02/06/201405/06/2014

    Keywords

    • Media Types for Sensor Markup Language
    • RDF
    • Inference

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