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Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges

  • Sofiat O. Abioye
  • , Lukumon O. Oyedele
  • , Lukman Akanbi
  • , Anuoluwapo Ajayi
  • , Juan Manuel Davila Delgado
  • , Muhammad Bilal
  • , Olugbenga O. Akinade
  • , Ashraf Ahmed

Research output: Contribution to journalReview articlepeer-review

Abstract

The growth of the construction industry is severely limited by the myriad complex challenges it faces such as cost and time overruns, health and safety, productivity and labour shortages. Also, construction industry is one the least digitized industries in the world, which has made it difficult for it to tackle the problems it currently faces. An advanced digital technology, Artificial Intelligence (AI), is currently revolutionising industries such as manufacturing, retail, and telecommunications. The subfields of AI such as machine learning, knowledge-based systems, computer vision, robotics and optimisation have successfully been applied in other industries to achieve increased profitability, efficiency, safety and security. While acknowledging the benefits of AI applications, numerous challenges which are relevant to AI still exist in the construction industry. This study aims to unravel AI applications, examine AI techniques being used and identify opportunites and challenges for AI applications in the construction industry. A critical review of available literature on AI applications in the construction industry such as activity monitoring, risk management, resource and waste optimisation was conducted. Furthermore, the opportunities and challenges of AI applications in construction were identified and presented in this study. This study provides insights into key AI applications as it applies to construction-specific challenges, as well as the pathway to realise the acrueable benefits of AI in the construction industry.

Original languageEnglish
Article number103299
Number of pages13
JournalJournal of Building Engineering
Volume44
Early online date5 Oct 2021
DOIs
Publication statusPublished - 1 Dec 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 The Authors

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