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Research Progress of Automation Ergonomic Risk Assessment in Building Construction: Visual Analysis and Review

Auteur(s):
ORCID

Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 12, v. 14
Page(s): 3789
DOI: 10.3390/buildings14123789
Abstrait:

In recent years, the increasing demand for worker safety and workflow efficiency in the construction industry has drawn considerable attention to the application of automated ergonomic technologies. To gain a comprehensive understanding of the current research landscape in this field, this study conducts an in-depth visual analysis of the literature on automated ergonomic risk assessment published between 2001 and 2024 in the Web of Science database using CiteSpace and VOSviewer. The analysis systematically reviews key research themes, collaboration networks, keywords, and citation patterns. Building on this, an SWOT analysis is employed to evaluate the core technologies currently widely adopted in the construction sector. By focusing on the integrated application of wearable sensors, artificial intelligence (AI), big data analytics, virtual reality (VR), and computer vision, this research highlights the significant advantages of these technologies in enhancing worker safety and optimizing construction processes. It also delves into potential challenges related to the complexity of these technologies, high implementation costs, and concerns regarding data privacy and worker health. While these technologies hold immense potential to transform the construction industry, future efforts will need to address these challenges through technological optimization and policy support to ensure broader adoption.

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

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10810163
  • Publié(e) le:
    17.01.2025
  • Modifié(e) le:
    25.01.2025
 
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