Research Article
Open access
Published on 20 December 2023
Download pdf
Liu,Q. (2023). Application and research of artificial intelligence in civil engineering intelligent construction. Theoretical and Natural Science,26,30-36.
Export citation

Application and research of artificial intelligence in civil engineering intelligent construction

Qingyang Liu *,1,
  • 1 Henan University of Science and Technology

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2753-8818/26/20241005

Abstract

When artificial intelligence (AI) begins to intervene, the production and lifestyles of various industries have also undergone great changes. The civil engineering construction industry has taken this opportunity to carry out the industry transformation, from traditional civil engineering construction to the intelligent construction of civil engineering with the participation of AI. Through the dynamic tracking and data analysis of construction sites and buildings through AI, the life safety of construction workers can be ensured by improving efficiency and ensuring quality. This paper analyzes the feature of intelligent construction, and discusses the current situation of intelligent construction and the application progress of intelligent construction in civil engineering construction, including Building information modeling (BIM) technology, Internet of Things and big data technology, AI technology, virtual reality technology, three-dimensional scanning technology, intelligent equipment and construction robots. At the same time, the problems and disadvantages of AI in the construction field are analyzed, and the application prospect of intelligent construction technology in future engineering construction is forecasted.

Keywords

Artificial Intelligence, Civil Engineering, Intelligent Design, Intelligent Operation and Maintenance.

[1]. Magaña Martínez D and Fernandez-Rodriguez J C 2015 Artificial intelligence applied to project success: a literature review Int. J. Interact. Multi. 3(5) 77-85

[2]. Wetzstein G, Ozcan A and Gigan S et al. 2020 Inference in artificial intelligence with deep optics and photonics Nature 588(7836) 39-47

[3]. Muthukrishnan N, Maleki F and Ovens K et al. 2020 Brief history of artificial intelligence Neuroimaging Cl. of N. USA. 30(4) 393-399

[4]. Liu H B, Zhang F and Chen Z H et al. 2022 Application research status and prospect of artificial intelligence in civil engineering J. Civil Envir. Eng. 3 1-20

[5]. Hu W, Sun C Y and Zhang D D 2023 Architectural design framework with the participation of artificial intelligence New Arch. 3 50-56

[6]. Schütze M, Sachse P and Römer A 2003 Support value of sketching in the design process RES. in Eng. Desg. 14(2) 89-97

[7]. Qian W, Xv Y and LI H 2022 A self-sparse generative adversarial network for autonomous early-stage design of architectural sketches Computer-Aided Civil Infra. Eng. 37(5) 612-628

[8]. Oliveira V and Ponho P 2010 Evaluation in urban planning: Advances and prospects J. Planning Lit. 24(4) 343-361

[9]. Lin B, Diao R D and Wu Y W 2019 Urban space generative design based on artificial intelligence: Northern extension of central green axis, Wenzhou Planners 35 (17) 44-50

[10]. Lyu J and Chen M N 2009 Automated visual inspection expert system for multivariate statistical process control chart Expert Sys. with App. 36(3) 5113-5118

[11]. Zhu F S, Li X B and WANG S Q et al. 2000 An expert system application to the selection and design of retaining structures J. Ne. Univ. (Natural Sci.) 21(3) 298-300

[12]. Nie Z G, Lin T, Jiang H L et al. 2021 TopologyGAN: Topology optimization using generative adversarial networks based on physical fields over the initial domain J. Mech. Desg. 143(3) 1-18

[13]. Chinese Academy of Architecture 2017 The unified standard for building information model application: GB/T 51212—2016 Beijing: China Construction Industry Press

[14]. Chen S M Griffs F H and Chen P H et al. 2021 Simulation and analytical techniques for construction resource planning and scheduling Auto. in CONST. 21 99-113

[15]. Li H and Bao Y Q 2021 Machine learning paradigm for structural health monitoring Struct. Health. Monit. 20(4) 1353-1372

Cite this article

Liu,Q. (2023). Application and research of artificial intelligence in civil engineering intelligent construction. Theoretical and Natural Science,26,30-36.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics

Conference website: https://www.confciap.org/
ISBN:978-1-83558-235-0(Print) / 978-1-83558-236-7(Online)
Conference date: 27 January 2024
Editor:Yazeed Ghadi
Series: Theoretical and Natural Science
Volume number: Vol.26
ISSN:2753-8818(Print) / 2753-8826(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).