Data Mining Techniques Sensor by Appice Annalisa (12 results)
Data Mining Techniques in Sensor Networks: Summarization, Interpolation and Surveillance (SpringerBriefs in Computer Science)
Appice, Annalisa; Ciampi, Anna; Fumarola, Fabio; Malerba, Donato
Language: English
Published by Springer, 2013
- Softcover
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Language: English
Published by Springer, 2013
- Softcover
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Condition: New. pp. 120.
Data Mining Techniques in Sensor Networks: Summarization, Interpolation and Surveillance
Appice, Annalisa/ Ciampi, Anna/ Fumarola, Fabio/ Malerba, Donato
Language: English
Published by Springer-Verlag New York Inc, 2013
- Softcover
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Paperback. Condition: Brand New. 2014 edition. 123 pages. 9.00x6.00x0.25 inches. In Stock.
Language: English
Published by Springer, 2013
- Softcover
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Taschenbuch. Condition: Neu. 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 compu…tes 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.
Language: English
Published by Springer, 2013
- Softcover
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Taschenbuch. Condition: Neu. Data Mining Techniques in Sensor Networks | Summarization, Interpolation and Surveillance | Annalisa Appice (u. a.) | Taschenbuch | SpringerBriefs in Computer Science | xiii | Englisch | 2013 | Springer | EAN 9781447154532 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17,…69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Data Mining Techniques in Sensor Networks : Summarization, Interpolation and Surveillance
Annalisa Appice, Donato Malerba, Fabio Fumarola, Anna Ciampi
Language: English
Published by Springer London, 2013
- Softcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | 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 compu…tes 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.
Language: English
Published by Springer, 2013
- Softcover
- Print on Demand
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer London Sep 2013, 2013
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 120 pp. Englisch.
Language: English
Published by Springer, 2013
- Softcover
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Condition: New. Print on Demand pp. 120 39 Illus. (37 Col.).
Language: English
Published by Springer, 2013
- Softcover
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Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Condition: New. PRINT ON DEMAND pp. 120.
Language: English
Published by Springer London, 2013
- Softcover
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Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces the trend cluster, a recently defined spatio-temporal pattern, and its use in summarizing, interpolating and identifying anomalies in sensor networksIllustrates the application of trend cluster discovery to… monitor the efficiency of pho.
Language: English
Published by Springer, Springer Sep 2013, 2013
- Softcover
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 alar…ms 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 120 pp. Englisch.
