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Mobile sensor networks for modelling environmental pollutant distribution

  • John Oyekan
    ,
  • Bowen Lu
    ,
  • Dongbing Gu
    ,
  • Huosheng Hu
    ,
  • Hossein Farid Ghassem Nia
Research Output: Contribution to journal Article Peer-review

Abstract

This article proposes to deploy a group of mobile sensor agents to cover a polluted region so that they are able to retrieve the pollutant distribution. The deployed mobile sensor agents are capable of making point observation in the natural environment. There are two approaches to modelling the pollutant distribution proposed in this article. One is a model-based approach where the sensor agents sample environmental pollutant, build up an environmental pollutant model and move towards the region where high density pollutant exists. The modelling technique used is a distributed support vector regression and the motion control technique used is a distributed locational optimising algorithm (centroidal Voronoi tessellation). The other is a model-free approach where the sensor agents sample environmental pollutant and directly move towards the region where high density pollutant exists without building up a model. The motion control technique used is a bacteria chemotaxis behaviour. By combining this behaviour with a flocking behaviour, it is possible to form a spatial distribution matched to the underlying pollutant distribution. Both approaches are simulated and tested with a group of real robots.

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 1491-1505

Journal (Volume, Issue Number)

International Journal of Systems Science (Volume 42, Issue 9)

Publication milestones

  • Published - 01/01/2011

Publication status

Published - 01/01/2011

ISSN

0020-7721

External Publication IDs

  • handle.net: 10547/276019
  • Scopus: 79960532152

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