Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks (Hardcover, 2012)

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This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative.

Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines. "


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Product Description

This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative.

Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines. "

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Product Details

General

Imprint

Springer-Verlag New York

Country of origin

United States

Series

Lecture Notes in Electrical Engineering, 118

Release date

February 2012

Availability

Expected to ship within 10 - 15 working days

First published

2012

Authors

,

Dimensions

235 x 155 x 7mm (L x W x T)

Format

Hardcover

Pages

108

Edition

2012

ISBN-13

978-1-4614-1349-3

Barcode

9781461413493

Categories

LSN

1-4614-1349-4



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