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Titlebook: GeoSensor Networks; Second International Silvia Nittel,Alexandros Labrinidis,Anthony Stefan Book 2008 Springer-Verlag Berlin Heidelberg 200

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書目名稱GeoSensor Networks
副標(biāo)題Second International
編輯Silvia Nittel,Alexandros Labrinidis,Anthony Stefan
視頻videohttp://file.papertrans.cn/384/383046/383046.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: GeoSensor Networks; Second International Silvia Nittel,Alexandros Labrinidis,Anthony Stefan Book 2008 Springer-Verlag Berlin Heidelberg 200
描述This volume serves as the post-conference proceedings for the Second GeoSensor Networks Conference that was held in Boston, Massachusetts in October 2006. The conference addressed issues related to the collection, management, processing, ana- sis, and delivery of real-time geospatial data using distributed geosensor networks. This represents an evolution of the traditional static and centralized geocomputational paradigm, to support the collection of both temporally and spatially high-resolution, up-to-date data over a broad geographic area, and to use sensor networks as actuators in geographic space. Sensors in these environments can be static or mobile, and can be used to passively collect information about the environment or, eventually, to actively influence it. The research challenges behind this novel paradigm extend the frontiers of tra- tional GIS research further into computer science, addressing issues like data stream processing, mobile computing, location-based services, temporal-spatial queries over geosensor networks, adaptable middleware, sensor data integration and mining, au- mated updating of geospatial databases, VR modeling, and computer vision. In order to addr
出版日期Book 2008
關(guān)鍵詞GIS; GSN; data analysis; geosensor; geospatial; mobile computing; monitor; ocean sensor network; real-time; s
版次1
doihttps://doi.org/10.1007/978-3-540-79996-2
isbn_softcover978-3-540-79995-5
isbn_ebook978-3-540-79996-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2008
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Efficient Data Collection and Selective Queries in Sensor Networksing on effective algorithms that reduce power consumption with effective in-network aggregation techniques. Up to now, most approaches are based on the assumption that data collection involves all nodes of a network. There is a large number of queries that in fact select only a subset of the nodes i
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Exploiting Spatio-temporal Correlations for Data Processing in Sensor Networksasks the state of the network is evaluated either at regular intervals at a base-station, which constitutes a centralized location where the data collected by the sensor nodes can be collected and processed, or continuously through the use of, potentially multiple, continuous queries. In order to in
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