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.

Rese�a del editor:

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.

��ber diesen Titel� kann sich auf eine andere Ausgabe dieses Titels beziehen.

Anbieterinformationen

Hello! Ria Christie Collections is an online venture that was initially set up in 2012 to sell books. We do not have a physical high street store. We are professional online booksellers. We only sell brand new books in perfect condition that we source from various suppliers and the publishers. Primarily, our aim is to provide an excellent service to all our customers. We always work as a team to achieve this. Our other objectives are to: 1. Ensure that all our products reach their destination quickly in a safe and secure manner 2. Answer to all our customer queries within 24 hours 3. Ensure that our customers are happy with their purchases 4. Provide all the items at a competitive price 5. Always listen to our customers Ria Christie Collections is not a registered company. It is a Sole Trader venture. Other key information is shown below: Contact Person Name: Rakesh Luchmun (Mr) Storefront Name: Ria Christie Collections Place of Establishment Address: Suite B; ARUN House; ARUN Building Arundel Road Uxbridge UB8 2RR United Kingdom E-Mail Address: riachristie@hotmail.co.uk VAT Number: GB 160 5650 25 We always work hard and aim to comply with all of Abebooks Policies. If you have any issues, please do not hesitate to write to us whether before or after a purchase. We promise to reply to you promptly and, in any case, within 24 hours. Thank you kindly! Yours sincerely Mr Rakesh Luchmun (Founder) and the Ria Christie Collections Team

Zur Homepage des Verk�ufers

Unternehmensdaten des Verk�ufers

Ryefield Investments Limited
175 Pield Heath Road, Uxbridge, UB8 3NL, United Kingdom

Gesch�ftsbedingungen:

All Returns and Refund are as per Abebooks policies.

Versandinformationen:

Orders usually ship within 2 business days. If your book order is heavy or oversized, we may contact you to let you know extra shipping is required. Thank you!

Zahlungsarten
akzeptiert von diesem Verk�ufer

Zu Kaufgesuchen hinzuf�gen

Verwandte Artikel zu Data Mining Techniques in Sensor Networks: Summarization,...

Data Mining Techniques in Sensor Networks: Summarization, Interpolation and Surveillance (SpringerBriefs in Computer Science)

Appice, Annalisa; Ciampi, Anna; Fumarola, Fabio; Malerba, Donato

Neu - Softcover

Unternehmensdaten des Verk�ufers