research-article

Implementing A Semantic-based loT Mashup Service

Authors:

Hyunseung Seok,

Yongju LeeAuthors Info & Claims

AICCC '19: Proceedings of the 2019 2nd Artificial Intelligence and Cloud Computing Conference

Pages 162 - 167

https://doi.org/10.1145/3375959.3375975

Published: 16 February 2020 Publication History

Abstract

The semantic information provided through the semantic-based IoT system will produce new high value-added products that are completely different from what we have known and experienced. From this point of view, a key issue of current IoT technology and applications is the development of an intelligent IoT platform architecture. Our proposed system collects the IoT data of the sensors from the cloud computer, converts them into RDF, and annotates them with semantics. The converted semantic data are shared and utilized through the ontology repository. We use KT's IoTMakers as a cloud computing environment, and the ontology repository uses Jena's Fuseki server to express SPARQL query results on the Web using Daum Map API and HighCharts API. This gives people the opportunity to access the semantic IoT mash-up service easily and has various application possibilities.

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S. Heo, S. Woo, J. Im, and D. Kim. 2015. IoT-MAP: IoT Mashup Application Platform for the Flexible IoT Ecosystem. 5th Int. Conf. on the Internet of Things. Seoul, South Korea. 163--170. DOI= https://doi.org/10.1109/iot.2015.7356561

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Agarwal, R., Farnandez, D., Elsaleh, T., Gyrard, A., Lanza, J., Sanchez, L., Georgantas, N., and Issarny, V. 2016. Unified IoT ontology to enable interoperability and federation of testbeds. In Proceedings of 2016 3rd IEEE World Forum on Internet of Things. Reston, VA, USA. DOI= https://doi.org/10.1109/wf-iot.2016.7845470

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Jang, G. 2014. Database Utilization Perspective Appendix: Data Utilization New Technology Guide 1: RDF. National Information Society Agency.

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KT. 2015. IoTMakers. http://iotmakers.kt.com

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Cited By

Lee YDuan HSun Y(2023)Semantically Enabled Content Convergence System for Large Scale RDF Big Data2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC57700.2023.00155(1019-1020)Online publication date: Jun-2023
https://doi.org/10.1109/COMPSAC57700.2023.00155

Index Terms

Implementing A Semantic-based loT Mashup Service
1. Information systems
  1. Information storage systems
    1. Storage architectures
      1. Distributed storage
  2. World Wide Web
    1. Web data description languages
      1. Semantic web description languages
        Web Ontology Language (OWL)
    2. Web searching and information discovery
      1. Web search engines
        Web indexing

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AICCC '19: Proceedings of the 2019 2nd Artificial Intelligence and Cloud Computing Conference

December 2019

216 pages

ISBN:9781450372633

DOI:10.1145/3375959

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Kobe University: Kobe University

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Association for Computing Machinery

New York, NY, United States

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Published: 16 February 2020

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AICCC 2019

AICCC 2019: 2019 2nd Artificial Intelligence and Cloud Computing Conference

December 21 - 23, 2019

Kobe, Japan

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Cited By

Lee YDuan HSun Y(2023)Semantically Enabled Content Convergence System for Large Scale RDF Big Data2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC57700.2023.00155(1019-1020)Online publication date: Jun-2023
https://doi.org/10.1109/COMPSAC57700.2023.00155

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