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: Contribution to journalArticle in a proceedings journalScientificpeer-review

26 Citations (Scopus)

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. © 2014 Published by Elsevier B.V.
Original languageEnglish
Pages (from-to)215-222
Number of pages8
JournalProcedia Computer Science
Volume32
DOIs
Publication statusPublished - 2014
MoE publication typeA4 Article in a conference publication

Keywords

  • Inference
  • Media Types for Sensor Markup Language
  • RDF

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