Data Mining Techniques in Sensor Networks
Summarization, Interpolation and Surveillance
1st Edition
Published on 12. September 2013
XIII, 105 pages
978-1-4471-5454-9 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Springer London
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XIII, 105 p. 39 illus., 37 illus. in color.
File size
4,71 MB
ISBN-13
978-1-4471-5454-9 (9781447154549)
DOI
10.1007/978-1-4471-5454-9
Schweitzer Classification
Other editions
Additional editions
Annalisa Appice | Anna Ciampi | Fabio Fumarola
Data Mining Techniques in Sensor Networks
Summarization, Interpolation and Surveillance
Book
09/2013
Springer
€53.49
Shipment within 15-20 days
Content
Introduction.- Sensor Networks and Data Streams: Basics.- Geodata Stream Summarization.- Missing Sensor Data Interpolation.- Sensor Data Surveillance.- Sensor Data Analysis Applications.
