Assessing the Potential of Machine Learning in Construction Safety: A Systematic Review

Farshid Taherpour, Gabriel Biratu Dadi, Mahsan Keshavarz, Parisa Kheiri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Many fatal and non-fatal occupational incidents have been reported in the construction industry globally. While many effective techniques have been developed in recent years to reduce the number of tragic accidents on the jobsite, there are still high rates of accidents. To improve management's decision-making processes, machine learning (ML) has drawn significant attention due to its ability to analyze large quantities of data to identify potential hazards on construction sites. Compared with traditional techniques, ML is able to handle large datasets and, through the use of different algorithms, can quickly analyze them to produce more accurate interpretations. Although machine learning has been identified as a useful statistical method for improving the decision-making process, little systematic research has been carried out on the correlation between machine learning and construction safety. To address this gap, this study was developed to explore a systematic review of the effect of machine learning on the safety of construction work sites. In examining and reviewing research two databases, it can be identified that ML techniques can be a powerful leverage for discovering useful knowledge from large datasets to perceive relationships, trends, and correlations. This study provides a contribution to the research area of ML applications in enhancing construction safety.

Original languageEnglish
Title of host publicationHealth and Safety, Workforce, and Education
EditorsJennifer S. Shane, Katherine M. Madson, Yunjeong Mo, Cristina Poleacovschi, Roy E. Sturgill
Pages945-955
Number of pages11
ISBN (Electronic)9780784485293
DOIs
StatePublished - 2024
EventConstruction Research Congress 2024, CRC 2024 - Des Moines, United States
Duration: Mar 20 2024Mar 23 2024

Publication series

NameConstruction Research Congress 2024, CRC 2024
Volume4

Conference

ConferenceConstruction Research Congress 2024, CRC 2024
Country/TerritoryUnited States
CityDes Moines
Period3/20/243/23/24

Bibliographical note

Publisher Copyright:
© CRC 2024. All rights reserved.

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

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