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A framework of developing a big data platform for construction waste management: a Hong Kong study

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  • معلومة اضافية
    • بيانات النشر:
      Springer.
      Singapore
    • الموضوع:
      2017
    • Collection:
      University of Hong Kong: HKU Scholars Hub
    • نبذة مختصرة :
      Big data has shown great potentials in improving management discretion in many areas. The applications of big data in areas such as finance, computer science, health care and medical science have made continued success. Despite of big data’s potentials, its applications in construction waste management (CWM) are still in infant stage. In order to embrace these prospects, this research proposes a platform to apply big data technologies in CWM, by focusing on the CWM status of Hong Kong. This study first presents a framework of the big data platform by describing the data collection, storage and analysis involved in the roadmap of CWM in Hong Kong. The existing unintentionally generated big dataset in CWM in Hong Kong is used to examine the availability of the proposed platform. It was found that this platform could make government, industry and other CWM stakeholders benefit from proper cooperation. Though this study focused on the CWM of Hong Kong, it may act as a driving force to stimulate the adoption of big data in CWM across countries where construction waste is growing as an urgent issue that concerns government, industry, academia, and all the stakeholders. ; postprint
    • ISBN:
      978-981-10-0854-2
      981-10-0854-X
    • Relation:
      Proceedings of the 20th International Symposium on Advancement of Construction Management and Real Estate; CRIOCM2015 International Symposium on Advancement of Construction Management and Real Estate, Hangzhou, China, 23-25 October 2015. In Wu, Y . (et al) (eds.), Proceedings of the 20th International Symposium on Advancement of Construction Management and Real Estate, p. 1069-1076. Singapore: Springer, 2017; 1076; 257351; 1069; http://hdl.handle.net/10722/223959
    • الرقم المعرف:
      10.1007/978-981-10-0855-9_94
    • الدخول الالكتروني :
      https://doi.org/10.1007/978-981-10-0855-9_94
      http://hdl.handle.net/10722/223959
    • Rights:
      The final publication is available at Springer via http://dx.doi.org/10.1007/978-981-10-0855-9 ; This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
    • الرقم المعرف:
      edsbas.A025E780