Academic Journal

A Bibliometrics-Based Systematic Review of Safety Risk Assessment for IBS Hoisting Construction.

Bibliographic Details
Title: A Bibliometrics-Based Systematic Review of Safety Risk Assessment for IBS Hoisting Construction.
Authors: Junjia, Yin, Alias, Aidi Hizami, Haron, Nuzul Azam, Abu Bakar, Nabilah
Source: Buildings (2075-5309); Jul2023, Vol. 13 Issue 7, p1853, 24p
Subject Terms: Risk assessment, Artificial neural networks, Bibliometrics, Digital twin, Industrialism
Abstract: Construction faces many safety accidents with urbanization, particularly in hoisting. However, there is a lack of systematic review studies in this area. This paper explored the factors and methods of risk assessment in hoisting for industrial building system (IBS) construction. Firstly, bibliometric analysis revealed that future research will focus on "ergonomics", "machine learning", "computer simulation", and "wearable sensors". Secondly, the previous 80 factors contributing to hoisting risks were summarized from a "human–equipment–management–material–environment" perspective, which can serve as a reference point for managers. Finally, we discussed, in-depth, the application of artificial neural networks (ANNs) and digital twins (DT). ANNs have improved the efficiency and accuracy of risk assessment. Still, they require high-quality and significant data, which traditional methods do not provide, resulting in the low accuracy of risk simulation results. DT data are emerging as an alternative, enabling stakeholders to visualize and analyze the construction process. However, DT's interactivity, high cost, and information security need further improvement. Based on the discussion and analysis, the risk control model created in this paper guides the direction for future research. [ABSTRACT FROM AUTHOR]
Copyright of Buildings (2075-5309) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
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  Data: A Bibliometrics-Based Systematic Review of Safety Risk Assessment for IBS Hoisting Construction.
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  Data: <searchLink fieldCode="AR" term="%22Junjia%2C+Yin%22">Junjia, Yin</searchLink><br /><searchLink fieldCode="AR" term="%22Alias%2C+Aidi+Hizami%22">Alias, Aidi Hizami</searchLink><br /><searchLink fieldCode="AR" term="%22Haron%2C+Nuzul+Azam%22">Haron, Nuzul Azam</searchLink><br /><searchLink fieldCode="AR" term="%22Abu+Bakar%2C+Nabilah%22">Abu Bakar, Nabilah</searchLink>
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  Data: Buildings (2075-5309); Jul2023, Vol. 13 Issue 7, p1853, 24p
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  Data: <searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Bibliometrics%22">Bibliometrics</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br /><searchLink fieldCode="DE" term="%22Industrialism%22">Industrialism</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Construction faces many safety accidents with urbanization, particularly in hoisting. However, there is a lack of systematic review studies in this area. This paper explored the factors and methods of risk assessment in hoisting for industrial building system (IBS) construction. Firstly, bibliometric analysis revealed that future research will focus on "ergonomics", "machine learning", "computer simulation", and "wearable sensors". Secondly, the previous 80 factors contributing to hoisting risks were summarized from a "human–equipment–management–material–environment" perspective, which can serve as a reference point for managers. Finally, we discussed, in-depth, the application of artificial neural networks (ANNs) and digital twins (DT). ANNs have improved the efficiency and accuracy of risk assessment. Still, they require high-quality and significant data, which traditional methods do not provide, resulting in the low accuracy of risk simulation results. DT data are emerging as an alternative, enabling stakeholders to visualize and analyze the construction process. However, DT's interactivity, high cost, and information security need further improvement. Based on the discussion and analysis, the risk control model created in this paper guides the direction for future research. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Buildings (2075-5309) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3390/buildings13071853
    Languages:
      – Code: eng
        Text: English
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        PageCount: 24
        StartPage: 1853
    Subjects:
      – SubjectFull: Risk assessment
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: Bibliometrics
        Type: general
      – SubjectFull: Digital twin
        Type: general
      – SubjectFull: Industrialism
        Type: general
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      – TitleFull: A Bibliometrics-Based Systematic Review of Safety Risk Assessment for IBS Hoisting Construction.
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            NameFull: Junjia, Yin
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            NameFull: Alias, Aidi Hizami
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            NameFull: Haron, Nuzul Azam
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            – D: 01
              M: 07
              Text: Jul2023
              Type: published
              Y: 2023
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              Value: 13
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