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Digital Technologies for Promoting Construction and Demolition Waste Management: A Systematic Review

Author(s): ORCID

ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 10, v. 14
Page(s): 3234
DOI: 10.3390/buildings14103234
Abstract:

The increasing concern about the environment has led to the necessity of ensuring efficient Construction and Demolition Waste Management (C&DWM) in the built environment. Despite the extensive research on C&DWM, the industry still faces significant challenges, including inefficiencies, high costs, and environmental impacts. Meanwhile, incorporating digital technologies (DTs) has emerged as a way to eradicate the challenges of C&DW. In response to the knowledge gap, in this research, we conducted a systematic literature review (SLR), incorporating bibliometric, text-mining, and content analysis to meet the research objectives. In total, 126 papers were retrieved from the Scopus database and transferred into VOSviewer to conduct the bibliometric analysis. The findings identified seven specific DTs, namely, blockchain, Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Robotics, Computer Vision (CV), and Building Information modeling (BIM). This study demonstrates that these technologies play a significant role in promoting efficient C&DWM in the construction industry. The study’s implication lies in its potential to guide industry stakeholders and policymakers in promoting the use of DTs and overcoming the barriers to their adoption, thereby facilitating more efficient and sustainable C&DWM practices. Finally, the findings of our research indicate possible future research directions for promoting DTs for C&DWM and eradicating the barriers to efficient implementation.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10804820
  • Published on:
    10/11/2024
  • Last updated on:
    10/11/2024
 
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