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

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openAccess

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Journal Title

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Volume Title

A4 Artikkeli konferenssijulkaisussa

Date

2014

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Mcode

Degree programme

Language

en

Pages

215–222

Series

5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), Hasselt, Belgium, 2-5 June, 2014, Procedia Computer Science, Volume 32

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.

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Keywords

Media Types for Sensor Markup Language, RDF, Inference

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Citation

Su, X, Zhang, H, Riekki, J, Keränen, A, Nurminen, J K & Du, L 2014, Connecting IoT Sensors to Knowledge-Based Systems by Transforming SenML to RDF . in 5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), Hasselt, Belgium, 2-5 June, 2014 . Procedia Computer Science, vol. 32, Elsevier, pp. 215–222, International Conference on Ambient Systems, Networks and Technologies, Hasselt, Belgium, 02/06/2014 . https://doi.org/10.1016/j.procs.2014.05.417