A semantic sensor mashup platform for Internet of Things

Sungkwang Eom, Wonwoo Ro, Kyong Ho Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the rapid advancement of the Internet of Things (IoT), a number of sensors are constantly deployed and connected to the Web, generating a large amount of real-time streaming data. Such sensor streams may include contextual events, which indicate meaningful information on our environment. For this reason, Web applications which are developed for IoT should embrace sensor streams. Hence, there is a need for a sensor mashup tool to compose multiple sensors for effectively processing sensor streams. However, existing models for sensor mashup do not support complex events included in sensor streams. In this paper, we propose a virtual complex sensor (VCS) model that enables users to combine various existing sensors and formula-based knowledge. In addition, we propose a method of automatically generating multiple VCSs according to a user's configuration. We also provide a graphical user interface for building a VCS mashup and processing complex events. Experimental results on the proposed semantic sensor mashup show that the proposed approach is reasonable and applicable to various IoT application domains.

Original languageEnglish
Title of host publicationIEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages427-432
Number of pages6
Volume2018-January
ISBN (Electronic)9781467399449
DOIs
Publication statusPublished - 2018 May 4
Event4th IEEE World Forum on Internet of Things, WF-IoT 2018 - Singapore, Singapore
Duration: 2018 Feb 52018 Feb 8

Other

Other4th IEEE World Forum on Internet of Things, WF-IoT 2018
CountrySingapore
CitySingapore
Period18/2/518/2/8

Fingerprint

Semantics
Sensors
Internet of things
Sensor
Mashup
Graphical user interfaces
Processing

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

Cite this

Eom, S., Ro, W., & Lee, K. H. (2018). A semantic sensor mashup platform for Internet of Things. In IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings (Vol. 2018-January, pp. 427-432). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WF-IoT.2018.8355108
Eom, Sungkwang ; Ro, Wonwoo ; Lee, Kyong Ho. / A semantic sensor mashup platform for Internet of Things. IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 427-432
@inproceedings{d969c9b348a54d9b844be8d211ab8e5a,
title = "A semantic sensor mashup platform for Internet of Things",
abstract = "With the rapid advancement of the Internet of Things (IoT), a number of sensors are constantly deployed and connected to the Web, generating a large amount of real-time streaming data. Such sensor streams may include contextual events, which indicate meaningful information on our environment. For this reason, Web applications which are developed for IoT should embrace sensor streams. Hence, there is a need for a sensor mashup tool to compose multiple sensors for effectively processing sensor streams. However, existing models for sensor mashup do not support complex events included in sensor streams. In this paper, we propose a virtual complex sensor (VCS) model that enables users to combine various existing sensors and formula-based knowledge. In addition, we propose a method of automatically generating multiple VCSs according to a user's configuration. We also provide a graphical user interface for building a VCS mashup and processing complex events. Experimental results on the proposed semantic sensor mashup show that the proposed approach is reasonable and applicable to various IoT application domains.",
author = "Sungkwang Eom and Wonwoo Ro and Lee, {Kyong Ho}",
year = "2018",
month = "5",
day = "4",
doi = "10.1109/WF-IoT.2018.8355108",
language = "English",
volume = "2018-January",
pages = "427--432",
booktitle = "IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

Eom, S, Ro, W & Lee, KH 2018, A semantic sensor mashup platform for Internet of Things. in IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 427-432, 4th IEEE World Forum on Internet of Things, WF-IoT 2018, Singapore, Singapore, 18/2/5. https://doi.org/10.1109/WF-IoT.2018.8355108

A semantic sensor mashup platform for Internet of Things. / Eom, Sungkwang; Ro, Wonwoo; Lee, Kyong Ho.

IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 427-432.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A semantic sensor mashup platform for Internet of Things

AU - Eom, Sungkwang

AU - Ro, Wonwoo

AU - Lee, Kyong Ho

PY - 2018/5/4

Y1 - 2018/5/4

N2 - With the rapid advancement of the Internet of Things (IoT), a number of sensors are constantly deployed and connected to the Web, generating a large amount of real-time streaming data. Such sensor streams may include contextual events, which indicate meaningful information on our environment. For this reason, Web applications which are developed for IoT should embrace sensor streams. Hence, there is a need for a sensor mashup tool to compose multiple sensors for effectively processing sensor streams. However, existing models for sensor mashup do not support complex events included in sensor streams. In this paper, we propose a virtual complex sensor (VCS) model that enables users to combine various existing sensors and formula-based knowledge. In addition, we propose a method of automatically generating multiple VCSs according to a user's configuration. We also provide a graphical user interface for building a VCS mashup and processing complex events. Experimental results on the proposed semantic sensor mashup show that the proposed approach is reasonable and applicable to various IoT application domains.

AB - With the rapid advancement of the Internet of Things (IoT), a number of sensors are constantly deployed and connected to the Web, generating a large amount of real-time streaming data. Such sensor streams may include contextual events, which indicate meaningful information on our environment. For this reason, Web applications which are developed for IoT should embrace sensor streams. Hence, there is a need for a sensor mashup tool to compose multiple sensors for effectively processing sensor streams. However, existing models for sensor mashup do not support complex events included in sensor streams. In this paper, we propose a virtual complex sensor (VCS) model that enables users to combine various existing sensors and formula-based knowledge. In addition, we propose a method of automatically generating multiple VCSs according to a user's configuration. We also provide a graphical user interface for building a VCS mashup and processing complex events. Experimental results on the proposed semantic sensor mashup show that the proposed approach is reasonable and applicable to various IoT application domains.

UR - http://www.scopus.com/inward/record.url?scp=85050407811&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85050407811&partnerID=8YFLogxK

U2 - 10.1109/WF-IoT.2018.8355108

DO - 10.1109/WF-IoT.2018.8355108

M3 - Conference contribution

VL - 2018-January

SP - 427

EP - 432

BT - IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Eom S, Ro W, Lee KH. A semantic sensor mashup platform for Internet of Things. In IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 427-432 https://doi.org/10.1109/WF-IoT.2018.8355108