iMuseum: A scalable context-aware intelligent museum system

  • Authors:

  • Zhiyong Yu;Xingshe Zhou;Zhiwen Yu;Jong Hyuk Park;Jianhua Ma

  • Affiliations:

  • School of Computer Science, Northwestern Polytechnical University, PR China;School of Computer Science, Northwestern Polytechnical University, PR China;School of Computer Science, Northwestern Polytechnical University, PR China and Academic Center for Computing and Media Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan;Department of Computer Science and Engineering, Kyungnam University, Korea;Faculty of Computer and Information Sciences, Hosei University, Japan

  • Venue:
  • Computer Communications
  • Year:
  • 2008

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Abstract

A context-aware intelligent museum system can capture the information of the visitor and surroundings, recognize the visitor's purpose, and then assist visiting in the museum. It is noted that not only the devices in the museum cannot be easily predicted, but the available applications may change over time. Therefore infinite entities and dynamic context knowledge are necessarily managed by a system with good scalability. This paper proposes a scalable context-aware intelligent museum system called iMuseum. The system is based on a new context model, 2*3CM (2 Sets and 3 Layers Context Model) that integrates the advantages of ontology-based model and hierarchical model. The iMuseum system has two novel features: distributed acquisition of context knowledge on demand and centralized sharing of context knowledge with double-repository. With the two mechanisms, the system is able to support defining new concepts, synthesizing high-level context, and querying application-oriented context at run-time. As a result, the third parties can independently develop their own applications or context providers, and also add or end them optionally. The preliminary experimental results have demonstrated the scalability and acceptance of the system.