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Data Mining Techniques in Sensor Networks - Summarization, Interpolation and Surveillance

Englisch · Taschenbuch

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Beschreibung

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Sensor networks comprise of a number of sensors installed across a spatially distributed network, which gather information and periodically feed a central server with the measured data. The server monitors the data, issues possible alarms and computes fast aggregates. As data analysis requests may concern both present and past data, the server is forced to store the entire stream. But the limited storage capacity of a server may reduce the amount of data stored on the disk. One solution is to compute summaries of the data as it arrives, and to use these summaries to interpolate the real data. This work introduces a recently defined spatio-temporal pattern, called trend cluster, to summarize, interpolate and identify anomalies in a sensor network. As an example, the application of trend cluster discovery to monitor the efficiency of photovoltaic power plants is discussed. The work closes with remarks on new possibilities for surveillance enabled by recent developments in sensing technology.

Inhaltsverzeichnis

Introduction.- Sensor Networks and Data Streams: Basics.- Geodata Stream Summarization.- Missing Sensor Data Interpolation.- Sensor Data Surveillance.- Sensor Data Analysis Applications.

Zusammenfassung

Sensor networks comprise of a number of sensors installed across a spatially distributed network, which gather information and periodically feed a central server with the measured data. The server monitors the data, issues possible alarms and computes fast aggregates. As data analysis requests may concern both present and past data, the server is forced to store the entire stream. But the limited storage capacity of a server may reduce the amount of data stored on the disk. One solution is to compute summaries of the data as it arrives, and to use these summaries to interpolate the real data. This work introduces a recently defined spatio-temporal pattern, called trend cluster, to summarize, interpolate and identify anomalies in a sensor network. As an example, the application of trend cluster discovery to monitor the efficiency of photovoltaic power plants is discussed. The work closes with remarks on new possibilities for surveillance enabled by recent developments in sensing technology.

Produktdetails

Autoren Annalis Appice, Annalisa Appice, Ann Ciampi, Anna Ciampi, Fabio Fumarola, Fabio et a Fumarola, Donato Malerba
Verlag Springer, Berlin
 
Sprache Englisch
Produktform Taschenbuch
Erschienen 20.08.2013
 
EAN 9781447154532
ISBN 978-1-4471-5453-2
Seiten 105
Abmessung 156 mm x 239 mm x 8 mm
Gewicht 195 g
Illustration XIII, 105 p. 39 illus., 37 illus. in color.
Serien SpringerBriefs in Computer Science
Springerbriefs in Computer Sci
SpringerBriefs in Computer Science
Thema Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Informatik

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