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Big data architecture for construction waste analytics (CWA): A conceptual framework

  • Muhammad Bilal
  • , Lukumon O. Oyedele*
  • , Olugbenga O. Akinade
  • , Saheed O. Ajayi
  • , Hafiz A. Alaka
  • , Hakeem A. Owolabi
  • , Junaid Qadir
  • , Maruf Pasha
  • , Sururah A. Bello
  • *Corresponding author for this work
    • University of the West of England
    • School of Electrical Engineering and Computer Science
    • Bahauddin Zakariya University
    • Obafemi Awolowo University

    Research output: Contribution to journalArticlepeer-review

    153 Citations (SciVal)
    Original languageEnglish
    Pages (from-to)144-156
    Number of pages13
    JournalJournal of Building Engineering
    Volume6
    DOIs
    Publication statusPublished (VoR) - 1 Jun 2016

    Funding

    The authors would like to express their sincere gratitude to Innovate UK (formerly Technology Strategy Board – TSB) and Balfour Beatty PLC for providing financial support for the research (under “Rethinking the build process”), through application No: 22883–158278 and file reference No: 101346.

    FundersFunder number
    Balfour Beatty PLC101346, 22883–158278
    Innovate UK (formerly Technology Strategy Board

      Keywords

      • Big data analytics
      • Building information modelling (BIM)
      • Construction waste
      • Construction waste analytics
      • Design optimisation
      • Waste prediction and minimisation

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