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Cited by 162BIM and Construction IntegrationArtificial Intelligence ApplicationsAI in Service Interactions

The DOI matches its Crossref record; 138 of the 140 references it cites were found in a registry or an index.

Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities

Open access
Saka, Abdullahi B., Oyedele, Lukumon O., Akanbi, Lukman A., Ganiyu, Sikiru A., Chan, Daniel W.M., Bello, Sururah A.·2023·Advanced Engineering Informatics
DOI 10.1016/j.aei.2022.101869
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Abstract

The idea of developing a system that can converse and understand human languages has been around since the 1200 s. With the advancement in artificial intelligence (AI), Conversational AI came of age in 2010 with the launch of Apple’s Siri. Conversational AI systems leveraged Natural Language Processing (NLP) to understand and converse with humans via speech and text. These systems have been deployed in sectors such as aviation, tourism, and healthcare. However, the application of Conversational AI in the architecture engineering and construction (AEC) industry is lagging, and little is known about the state of research on Conversational AI. Thus, this study presents a systematic review of Conversational AI in the AEC industry to provide insights into the current development and conducted a Focus Group Discussion to highlight challenges and validate areas of opportunities. The findings reveal that Conversational AI applications hold immense benefits for the AEC industry, but it is currently underexplored. The major challenges for the under exploration were highlighted and discusses for intervention. Lastly, opportunities and future research directions of Conversational AI are projected and validated which would improve the productivity and efficiency of the industry. This study presents the status quo of a fast-emerging research area and serves as the first attempt in the AEC field. Its findings would provide insights into the new field which be of benefit to researchers and stakeholders in the AEC industry.

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Show all 140 references

Research works printed but not linked: 6

  1. Olawumi, 2021, Scientometric review and analysis: A case example of smart buildings and smart cities, 147
  2. Wang, N., R.R. Issa, and C.J. Anumba, A Framework for Intelligent Building Information Spoken Dialogue System (iBISDS), in EG-ICE 2021 Workshop on Intelligent Computing in Engineering. 2021.
  3. Sheldon, A., T. Dobbs, A. Fabbri, N. Gardner, M.H. Haeusler, C. Ramos, and Y. Zavoleas, Putting the AR In (AR)chitecture, in International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA). 2019, Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong. p. 475-484. · DOI
  4. Zhoui, H., M.O. Wong, H. Ying, and S.H. Lee, A Framework of a Multi-User Voice-Driven BIM-Based Navigation System for Fire Emergency Response, in 26th International Workshop on Intelligent Computing in Engineering (EG-ICE 2019). 2019.
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  6. Davila Delgado, 2019, Robotics and automated systems in construction: Understanding industry-specific challenges for adoption. Journal of Building, Engineering, 26

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Metadata

Authors
Saka, A. B., Oyedele, L. O., Akanbi, L. A., Ganiyu, S. A., Chan, D. W. M., & Bello, S. A.
Affiliations
  • Leeds Beckett University (GB)
  • University of the West of England (GB)
  • Teesside University (GB)
  • Hong Kong Polytechnic University (HK)
Corresponding author
Oyedele, Lukumon O.
ORCID
Venue
Advanced Engineering Informatics
Publisher
Elsevier BV
Published
2023-01
Volume
55
Pages
101869
ISSN
1474-0346 (ISSN-L)
DOI
10.1016/j.aei.2022.101869
OpenAlex
W4313457971
Cited by
161
References
140
Citations by year
2026: 39 · 2025: 50 · 2024: 50 · 2023: 22
FWCI
19.33
Type
journal article
Language
en
Open access
Licence
Locations
  • Advanced Engineering Informatics (publishedVersion, cc-by)
  • PolyU Institutional Research Archive (Hong Kong Polytechnic University) (submittedVersion, cc-by)
  • Leeds Beckett Repository (Leeds Beckett University) (submittedVersion)
  • Teesside University Research Portal (Teesside University) (submittedVersion, cc-by)
  • UWE Research Repository (UWE Bristol) (submittedVersion, cc-by)
  • WestminsterResearch (University of Westminster) (submittedVersion, cc-by)
Funders
Engineering and Physical Sciences Research Council (EP/S031480/1)
Topics
  • Physical Sciences › Engineering › Building and Construction › BIM and Construction Integration
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
Keywords
conversational AI, architecture, engineering and construction, natural language processing, speech recognition, chatbots, construction productivity, implementation barriers, future research directions

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