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

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

40 Citations (Scopus)

165 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 language	English
Title of host publication	5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), Hasselt, Belgium, 2-5 June, 2014
Publisher	Elsevier
Pages	215–222
DOIs	https://doi.org/10.1016/j.procs.2014.05.417
Publication status	Published - 2014
MoE publication type	A4 Conference publication
Event	International Conference on Ambient Systems, Networks and Technologies - Hasselt, Belgium Duration: 2 Jun 2014 → 5 Jun 2014 Conference number: 5

Publication series

Name	Procedia Computer Science
Publisher	Elsevier
Volume	32
ISSN (Electronic)	1877-0509

Conference

Conference	International Conference on Ambient Systems, Networks and Technologies
Abbreviated title	ANT
Country/Territory	Belgium
City	Hasselt
Period	02/06/2014 → 05/06/2014

Keywords

Media Types for Sensor Markup Language
RDF
Inference

Access to Document

10.1016/j.procs.2014.05.417

1-s2.0-S1877050914006176-mainFinal published version, 784 KBLicence: CC BY-NC-ND

Cite this

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 (pp. 215–222). (Procedia Computer Science; Vol. 32). Elsevier. https://doi.org/10.1016/j.procs.2014.05.417

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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.",

keywords = "Media Types for Sensor Markup Language, RDF, Inference",

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

year = "2014",

doi = "10.1016/j.procs.2014.05.417",

language = "English",

series = "Procedia Computer Science",

publisher = "Elsevier",

pages = "215–222",

booktitle = "5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), Hasselt, Belgium, 2-5 June, 2014",

address = "Netherlands",

note = "International Conference on Ambient Systems, Networks and Technologies, ANT ; Conference date: 02-06-2014 Through 05-06-2014",

}

Su, X, Zhang, H, Riekki, J, Keränen, A, Nurminen, JK & 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

Connecting IoT Sensors to Knowledge-Based Systems by Transforming SenML to RDF. / Su, Xiang; Zhang, Hao; Riekki, Jukka et al.
5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), Hasselt, Belgium, 2-5 June, 2014. Elsevier, 2014. p. 215–222 (Procedia Computer Science; Vol. 32).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

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

N1 - Conference code: 5

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.

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.

KW - Media Types for Sensor Markup Language

KW - RDF

KW - Inference

U2 - 10.1016/j.procs.2014.05.417

DO - 10.1016/j.procs.2014.05.417

M3 - Conference article in proceedings

T3 - Procedia Computer Science

SP - 215

EP - 222

BT - 5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), Hasselt, Belgium, 2-5 June, 2014

PB - Elsevier

T2 - International Conference on Ambient Systems, Networks and Technologies

Y2 - 2 June 2014 through 5 June 2014

ER -

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

Abstract

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Keywords

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