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

Language: English

Published by Springer, 2013

1447154533 / 9781447154532

Series: Book 87 of 322 - SpringerBriefs in Computer Science

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Druck auf Anfrage Neuware - Printed after ordering - 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.…

Seller Inventory # 9781447154532

Title
Data Mining Techniques in Sensor Networks : Summarization, Interpolation and Surveillance
Author
Annalisa Appice
Publisher
Springer
Publication year
2013
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
1447154533
ISBN 13
9781447154532
Item weight
195 grams
Dimensions
235x155x7 mm
Series
Book 87 of 322: SpringerBriefs in Computer Science

AHA-BUCH GmbH

Einbeck, Germany

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