Viewlon: Visualizing information on semantic sensor network

Masayuki Furuyama, Jun Mukai, Michita Imai

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

The topic of getting information from sensor networks is becoming more important. Middleware will be required to manage various sensor data in future. We propose the Semantic Sensor Network (SS), which applies an ontology to sensor data and enables such data to be treated more easily. However, users have great difficulty to understand the information on the SS because its semantic data are complicatedly related with each other and the data and their relations evolve in time. The requirements for visualizing such information are; 1) the SS must give users the information appropriately, and 2) the SS must answer the users' queries. To meet these requirements, we propose Viewlon, software for visualizing information on the SS. To give the information appropriately, information display levels and a timeline view are introduced. In addition the functionality of processing queries provides the required information to users interactively. We experimented with Viewlon in a simulation environment, and the results show that Viewlon has the ability to present information to users and to answer their queries correctly.

本文言語English
ホスト出版物のタイトルNew Frontiers in Artificial Intelligence - JSAI 2006 Conference and Workshops, Revised Selected Papers
ページ65-76
ページ数12
出版ステータスPublished - 2007 8 27
イベント20th Annual Conference of the Japanese Society for Artificial Intelligence, JSAI 2006 Conference and Workshops - Tokyo, Japan
継続期間: 2006 6 52006 6 9

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4384 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other20th Annual Conference of the Japanese Society for Artificial Intelligence, JSAI 2006 Conference and Workshops
CountryJapan
CityTokyo
Period06/6/506/6/9

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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