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Map as a Service: A Framework for Visualising and Maximising Information Return from Multi-ModalWireless Sensor

Mohammad Hammoudeh1, Robert Newman2, Christopher Dennett3

  • 1School of Computing, Mathematics & Digital Technology, Manchester Metropolitan University, Manchester, M1 5GD, UK. M.Hammoudeh@mmu.ac.uk.

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Summary

This study introduces a mapping service for wireless sensor networks, enhancing data extraction and visualization. It improves information accuracy and reduces power consumption for better field data representation.

Keywords:
Wireless Sensor Networksdomain-modelinformation extractioninformation fusioninformation visualisationmapping servicesservice-oriented networks

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Data Visualization

Background:

  • Large-scale wireless sensor networks generate vast amounts of data.
  • Extracting and visualizing this data effectively is challenging.
  • Existing methods struggle with accuracy and efficiency.

Purpose of the Study:

  • To present a novel distributed information extraction and visualization service.
  • To maximize information return from wireless sensor networks.
  • To simplify the creation of information-rich representations and field visualizations.

Main Methods:

  • Utilizes a blend of inductive and deductive models for accurate sense data mapping.
  • Employs application domain characteristics for realistic map-based visualizations.
  • Integrates a distributed self-adaptation function for power saving and accuracy.
  • Dynamically updates the application domain model to adapt to environmental changes.

Main Results:

  • Achieves low communication overhead.
  • Produces high-fidelity maps.
  • Minimizes mapping predictive error dynamically.
  • Demonstrates suitability for visualizing multiple sense modalities.

Conclusions:

  • The mapping service effectively enhances information extraction and visualization in wireless sensor networks.
  • The service offers dynamic adaptation, power efficiency, and improved data accuracy.
  • It overcomes limitations of single-modality visualization and provides realistic field information representations.