Distributed and Heterogeneous Data Analysis for Smart Urban Planning

  • Eduardo A. Oliveira
  • Michael Kirley
  • Tom Kvan
  • Justyna Karakiewicz
  • Carlos Vaz
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 527)

Abstract

Over the past decade, ‘smart’ cities have capitalized on new technologies and insights to transform their systems, operations and services. The rationale behind the use of these technologies is that an evidence-based, analytical approach to decision-making will lead to more robust and sustainable outcomes. However, harvesting high-quality data from the dense network of sensors embedded in the urban infrastructure, and combining this data with social network data, poses many challenges. In this paper, we investigate the use of an intelligent middleware – Device Nimbus – to support data capture and analysis techniques to inform urban planning and design. We report results from a ‘Living Campus’ experiment at the University of Melbourne, Australia focused on a public learning space case study. Local perspectives, collected via crowd sourcing, are combined with distributed and heterogeneous environmental sensor data. Our analysis shows that Device Nimbus’ data integration and intelligent modules provide high-quality support for decision-making and planning.

Keywords

Smart city Smart campus Middleware Data fusion Urban design Urban planning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Eduardo A. Oliveira
    • 1
  • Michael Kirley
    • 1
  • Tom Kvan
    • 1
  • Justyna Karakiewicz
    • 1
  • Carlos Vaz
    • 1
  1. 1.University of MelbourneMelbourneAustralia

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