Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks 2012th Edition

Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks 2012th Edition book cover

Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks 2012th Edition

Author(s): Ahmed Abdelgawad (Author), Magdy Bayoumi (Author)

  • Publisher: Springer
  • Publication Date: February 15, 2012
  • Edition: 2012th
  • Language: English
  • Print length: 124 pages
  • ISBN-10: 1461413494
  • ISBN-13: 9781461413493

Book 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.

Editorial Reviews

From the Back Cover

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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