A Context Retrieval Method for Context-awareness Using Ontology-Based Approach in Internet of Things Environments


  • Yoosang Park Soongsil University
  • Yeonseung Yoo Soongsil University
  • Jonghyeok Mun Soongsil University
  • Jongsun Choi Soongsil University
  • Jaeyoung Choi Soongsil University




context-aware, sensor data abstraction, internet of things (IoT), ontology


A context-aware system is required for providing context-aware services to users in the Internet of things (IoT) environment. It consists of three primary tasks: gathering context data, abstracting the collected data, and providing services to users. In IoT environments, context data are generated by a large number of sensors, and this context data are part of the context-awareness services provided to the users. When the context-aware system provides context-aware services with their service descriptions, it is necessary to process the data gathered by abstracting and contextualizing them. Generally, the context-aware system encounters a problem in that the context representations between contextualized sensor data and their related service descriptions do not match well. We herein propose a context retrieval method that facilitates in obtaining context information for the context-aware system in IoT environments. The context-aware system communicates with an ontology module that handles input data described in a set of universal resource identifiers, as a triplet. The ontology module resolves each representation request from the context-aware system. The proposed method provides an ontology-based mapping procedure for the context representation problem described above.

Author Biographies

Yoosang Park, Soongsil University


Yeonseung Yoo, Soongsil University


Jonghyeok Mun, Soongsil University


Jongsun Choi, Soongsil University


Jaeyoung Choi, Soongsil University



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How to Cite

Y. Park, Y. Yoo, J. Mun, J. Choi, and J. Choi, “A Context Retrieval Method for Context-awareness Using Ontology-Based Approach in Internet of Things Environments”, Proc. eng. technol. innov., vol. 10, pp. 36–41, Oct. 2018.