A phenomena-of-interest approach for the interconnection of sensor data and spatiotemporal web contents

Kyoung Sook Kim, Takafumi Nakanishi, Hidenori Homma, Koji Zettsu, Yutaka Kidawara, Yasushi Kiyoki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the advance of ubiquitous computing and mobile environments, we have begun to continuously monitor changes in real-world condition and environment through wireless sensor networks. Opportunities also exist for people to create information related to the world around them by using mobile phones equipped with sensing devices, and share that information online with others. In this paper, we propose a novel approach for the interconnection of earth observation data and spatiotemporal web contents on the basis of spatiotemporal and thematic relationships. In particular, we use the concept of moving phenomena of interests to link between measurement sensing data and people-centric contents on the basis of spatiotemporal proximity and thematic relevance. This paper also shows a simple application that automatically generates semantic tags with respect to natural geographic phenomena, such as typhoons, climate changes, and air pollution, on the basis of our interconnection approach. We are able to easily understand qualitative meanings with respect to a certain phenomenon expressed by quantitative numeric conditions.

Original languageEnglish
Title of host publicationInformation Modelling and Knowledge Bases XXII
PublisherIOS Press
Pages288-300
Number of pages13
ISBN (Print)9781607506898
DOIs
Publication statusPublished - 2011
Externally publishedYes

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume225
ISSN (Print)0922-6389

Keywords

  • events
  • geo-observation
  • phenomena
  • sensing measurements
  • spatiotemporal proximity
  • thematic relevance
  • user-generated contents

ASJC Scopus subject areas

  • Artificial Intelligence

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