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An Intelligent Sensor Network for Oceanographic Data Acquisition

  • Chris Roadknight
  • Antonio Gonzalez
  • Laura Parrot
  • Steve Boult
  • Ian Marshall
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3738)

Abstract

In this paper we describe the deployment of an offshore wireless sensor network and the lightweight intelligence that was integrated into the data acquisition and forwarding software. Although the conditions were harsh and the hardware readily available, the deployment managed to characterise an extended period due the some unique algorithms. In-situ adaptation to differences in data types, hardware condition and user requirements are demonstrated and analysis of performance carried out. Statistical tests, local feedback and global genetic style material exchange ensure limited resources such as battery and bandwidth are used efficiently by manipulating data at the source.

Keywords

Sensor Network Wireless Sensor Network Battery Power Bandwidth Usage Hardware Condition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Chris Roadknight
    • 1
  • Antonio Gonzalez
    • 2
  • Laura Parrot
    • 3
  • Steve Boult
    • 4
  • Ian Marshall
    • 3
  1. 1.BTSuffolkUK
  2. 2.UCL
  3. 3.The University of KentUK
  4. 4.Intelisys LtdManchester

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