Data Management for Intelligent Transport System Using Pervasive Sensing

  1. Lookup NU author(s)
  2. Visalakshmi Suresh
  3. Professor Paul Watson
  4. Jeffrey Neasham
  5. Michael Bell
  6. Dr Fabio Galatioto
  7. Dr Graeme Hill
Author(s)Suresh V, Watson P, Neasham J, Bell M, Pearson D, Oliver D, Galatioto F, Hill G, Parmar J
Publication type Conference Proceedings (inc. Abstract)
Conference NameeScience All Hands Meeting
Conference LocationOxford, UK
Year of Conference2009
Source Publication Date7-9 December 2009
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In this paper we address the information management framework to deliver the design and implementation of a static and mobile, detector system for monitoring traffic and pollution in existing road networks. The measured data comes from networks of low cost, pervasive sensors referred to as motes or smart dust, as well as legacy monitoring stations installed by city councils to monitor traffic and pollution. The framework provides real-time information on traffic, pollution and meteorological conditions. The streaming data from the heterogeneous data sources is collected, processed, analyzed and disseminated so that it can be used to drive applications in real-time and collect historic information in a data warehouse. The real time and historic data is integrated to monitor network status, manage traffic to reduce congestion, improve air quality and manage noise impacts.