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

doi:10.1016/j.procs.2014.05.417

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

Not published at VTT

Aalto University

Research output: Contribution to journal › Article in a proceedings journal › Scientific › peer-review

39 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 language	English
Pages (from-to)	215-222
Number of pages	8
Journal	Procedia Computer Science
Volume	32
DOIs	https://doi.org/10.1016/j.procs.2014.05.417
Publication status	Published - 2014
MoE publication type	A4 Article in a conference publication

Keywords

Inference
Media Types for Sensor Markup Language
RDF

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10.1016/j.procs.2014.05.417

Cite this

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title = "Connecting IoT sensors to knowledge-based systems by transforming SenML to RDF",

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. {\textcopyright} 2014 Published by Elsevier B.V.",

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author = "Xiang Su and Hao Zhang and Jukka Riekki and Ari Ker{\"a}nen and Nurminen, {Jukka K.} and Libin Du",

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journal = "Procedia Computer Science",

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TY - JOUR

T1 - Connecting IoT sensors to knowledge-based systems by transforming SenML to RDF

AU - Su, Xiang

AU - Zhang, Hao

AU - Riekki, Jukka

AU - Keränen, Ari

AU - Nurminen, Jukka K.

AU - Du, Libin

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Inference

KW - Media Types for Sensor Markup Language

KW - RDF

U2 - 10.1016/j.procs.2014.05.417

DO - 10.1016/j.procs.2014.05.417

M3 - Article in a proceedings journal

VL - 32

SP - 215

EP - 222

JO - Procedia Computer Science

JF - Procedia Computer Science

ER -

Connecting IoT sensors to knowledge-based systems by transforming SenML to RDF

Abstract

Keywords

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