TY - GEN
T1 - A phenomena-of-interest approach for the interconnection of sensor data and spatiotemporal web contents
AU - Kim, Kyoung Sook
AU - Nakanishi, Takafumi
AU - Homma, Hidenori
AU - Zettsu, Koji
AU - Kidawara, Yutaka
AU - Kiyoki, Yasushi
N1 - Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - events
KW - geo-observation
KW - phenomena
KW - sensing measurements
KW - spatiotemporal proximity
KW - thematic relevance
KW - user-generated contents
UR - http://www.scopus.com/inward/record.url?scp=79951606295&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79951606295&partnerID=8YFLogxK
U2 - 10.3233/978-1-60750-690-4-288
DO - 10.3233/978-1-60750-690-4-288
M3 - Conference contribution
AN - SCOPUS:79951606295
SN - 9781607506898
T3 - Frontiers in Artificial Intelligence and Applications
SP - 288
EP - 300
BT - Information Modelling and Knowledge Bases XXII
PB - IOS Press
ER -