The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
권호 표지
DOI QR코드

DOI QR Code

Ontology-based IoT Context Information Modeling and Semantic-based IoT Mashup Services Implementation

온톨로지 기반의 IoT 상황 정보 모델링 및 시맨틱 기반 IoT 매쉬업 서비스 구현

  • 석현승 (경북대학교 IT대학 컴퓨터학부) ;
  • 이용주 (경북대학교 IT대학 컴퓨터학부)
  • Received : 2019.07.19
  • Accepted : 2019.08.15
  • Published : 2019.08.31
Download PDF
⟨ Previous Next ⟩

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, the key issue of current IoT technology and applications is the development of an intelligent IoT platform architecture. The 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 is 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.

시맨틱 기반 IoT 시스템을 통하여 제공되는 시맨틱 정보는 우리가 지금까지 알고 경험해 왔던 것과는 전혀 다른 새로운 고부가가치 결과물을 만들 수 있을 것이다. 이러한 관점에서 현재 IoT 기술 및 응용에 대한 핵심이슈는 지능적 IoT 플랫폼 아키텍쳐의 개발이다. 본 논문에서 제안된 시스템은 클라우드 컴퓨터에서 센서들의 IoT 데이터를 취합하고, 이들을 RDF로 변환한 후 시맨틱 주석 처리한다. 변환된 시맨틱 데이터는 온톨로지 레포지토리를 통해 공유되고 활용된다. 클라우드 컴퓨팅 환경으로써 KT의 IoTMakers를 이용하고, 온톨로지 레포지토리는 Jena의 Fuseki 서버를 사용하여 SPARQL 질의 결과를 Daum Map API와 Highcharts API를 사용하여 웹으로 표현하였다. 이를 통해 사람들이 시맨틱 IoT 매쉬업 서비스를 쉽게 접근할 기회를 제공하여 다양한 응용 가능성을 가진다.

Keywords

KCTSAD_2019_v14n4_671_f0001.png 이미지

그림 1. IoT 온톨로지 모델링 Fig. 1 IoT ontology modeling

KCTSAD_2019_v14n4_671_f0002.png 이미지

그림 2. 클래스, 오브젝트, 그리고 데이터 속성 Fig. 2 Class, object, and data attributes

KCTSAD_2019_v14n4_671_f0003.png 이미지

그림 3. 시맨틱 기반 IoT 시스템 아키텍쳐 Fig. 3 Semantic-based IoT system architecture

KCTSAD_2019_v14n4_671_f0004.png 이미지

그림 4. PC 환경의 시맨틱 IoT 매쉬업 서비스 Fig. 4 Semantic IoT mashup service for PC environment

KCTSAD_2019_v14n4_671_f0005.png 이미지

그림 5. 모바일 환경의 시맨틱 IoT 매쉬업 서비스 Fig. 5 Semantic IoT mashup service for mobile environment

KCTSAD_2019_v14n4_671_f0006.png 이미지

그림 6. 디바이스 위치와 센서 로그 검색 알고리즘 Fig. 6 Device location and sensor log retrieval algorithm

KCTSAD_2019_v14n4_671_f0007.png 이미지

그림 7. 위치기반의 디바이스와 센서 정보 Fig. 7 Location-based device and sensor information

KCTSAD_2019_v14n4_671_f0008.png 이미지

그림 8. 디바이스와 센서 대쉬보드 Fig. 8 Device and sensor dashboard

KCTSAD_2019_v14n4_671_f0009.png 이미지

그림 9. 센서 로그 그래프 Fig. 9 Sensor log graph

표 1. 유사 시스템 간 기능 및 구현기술 비교 Table 1. Comparison of functions and implementation technologies between similar systems

KCTSAD_2019_v14n4_671_t0001.png 이미지

References

  1. NCTA, "Behind The Numbers: Growth in the Internet of Things," Technical report, Aug. 2015.
  2. MSS, TIPA, and NICE Information Service, "SME Strategy Technology Roadmap 2019-2021 Internet of Things," Technical report, 2019.
  3. D. Park, "A Study on Semantic Technology in Internet of Things," J. of Electrical Engineering, vol. 42, no. 3, June 2018, pp. 25-32.
  4. S. Moon and C. Hong, "Development of a Semantic Analysis System for Contextual Fault Awareness in IoT Networks," Korean Institute of Information Scientists and Engineers Trans. on Computing Practices, vol. 24, no. 6, June 2018, pp. 263-273.
  5. E. Kim and Y. Suh, "A Situation Information Model based on Ontology in IoT Environment," J. of Korea Institute of Information, Electronics, and Communication Technology, vol. 10, no. 5, Oct. 2017, pp. 380-388. https://doi.org/10.17661/jkiiect.2017.10.5.380
  6. D. Woo, M. Yoo, and Y. Kim, "A Study on Ontology for Semantic-Based Service Exploiting the Context Information in IoT Environment," J. of Society for e-Business Studies, vol. 21, no. 3, Aug. 2016, pp. 1-13.
  7. F. Shi, Q. Li, T. Zhu, and H. Ning, "A Survey of Data Semantization in Internet of Things," J. of Sensors, vol. 18, no. 1, Jan. 2018, pp. 313-333. https://doi.org/10.3390/s18010313
  8. F. Liu, P. Li, and D. Deng, "Device-Oriented Automatic Semantic Annotation in IoT," J. of Sensors, vol. 5, June 2017, pp. 1-14.
  9. X. Zhang, Y. Zhao, and Y. Liu, "A Method for Mapping Sensor Data to SNN Ontology," International J. of u- and e-Service, Science and Technology, vol. 8, no. 6, 2015, pp. 303-316.
  10. S. Heo, S. Woo, J. Im, and D. Kim, "IoT-MAP: IoT Mashup Application Platform for the Flexible IoT Ecosystem," 5th Int. Conf. on the Internet of Things, Seoul, South Korea, Oct. 2015, pp. 163-170.
  11. R. Agarwal, D. Farnandez, T. Elsaleh, A. Gyrard, J. Lanza, L. Sanchez, N. Georgantas, and V. Issarny, "Unified IoT Ontology to Enable Interoperability and Federation of Testbeds," 3rd IEEE WF-IoT, Reston, VA, USA, Dec. 2016.
  12. KT, IoTMakers, 2015.
  13. Apache Software Foundation, Jena, 2017.
  14. S. Jang, "Responsive Web of Prototype based on Implementation Structure," J. of the Korea Institute of Electronic Communication Sciences, vol. 13, no. 3, 2018, pp. 609-616. https://doi.org/10.13067/JKIECS.2018.13.3.609
  15. J. Park, "Design of Department Curriculum Manangement System based on Ontology," J. of the Korea Institute of Electronic Communication Sciences, vol. 7, no. 6, 2012, pp. 1363-1368. https://doi.org/10.13067/JKIECS.2012.7.6.1363
  16. Highsoft, HighCharts, 2009.
  17. S. Lee, D. Jeong, H. Jung, and D. Baik, "Design and Implementation of Sensor Registry Data Model for IoT Environment," J. of Korea Information Processing Society, vol. 5, May 2016, pp. 221-230.
  18. KAIST Auto-ID Labs, Oliot, 2014.