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Air Pollution Monitoring and Mining Based on Sensor Grid in London.

Yajie Ma1, Mark Richards2, Moustafa Ghanem3

  • 1Department of Computing, Imperial College London, 180 Queens Gate, London SW7 2BW, UK. yajie.ma@imperial.ac.uk.

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Summary
This summary is machine-generated.

This study introduces a wireless sensor network and Grid computing infrastructure for real-time urban air pollution monitoring. The system addresses informatics challenges using a P2P e-Science Grid and distributed data mining for effective environmental data analysis.

Keywords:
distributed data mining.gridsensor networkurban air pollution

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Area of Science:

  • Environmental Science
  • Computer Science
  • Information Technology

Background:

  • Urban air pollution monitoring requires real-time, large-scale data collection.
  • Existing infrastructure faces challenges in handling high-throughput sensor data.

Purpose of the Study:

  • To present a distributed infrastructure for air pollution monitoring using wireless sensor networks and Grid computing.
  • To address informatics challenges in constructing high-throughput sensor Grids.

Main Methods:

  • Development of a two-layer network framework and a P2P e-Science Grid architecture.
  • Implementation of a distributed data mining algorithm for environmental data analysis.
  • System simulation using TinyOS to evaluate sensor operation and network performance.

Main Results:

  • Demonstration of a functional distributed infrastructure for air pollution monitoring.
  • Validation of the P2P e-Science Grid architecture and distributed data mining algorithm.
  • Successful simulation of sensor network performance and data mining effectiveness.

Conclusions:

  • The proposed infrastructure offers a low-cost, ubiquitous solution for urban air pollution monitoring.
  • The P2P e-Science Grid and distributed data mining effectively address high-throughput sensor data challenges.
  • The system provides a viable approach for real-time environmental data analysis and air quality assessment.