Large-Scale AI Models Across the Construction Lifecycle

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 945

Special Issue Editors

Faculty of Construction and Environment, Hong Kong Polytechnic University, Kowloon 100872, Hong Kong
Interests: construction informatics; artificial intelligence; building information modeling; automation in construction
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Guest Editor
School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Interests: project Integrated management; value management; urban renewal; large-scale AI models

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Guest Editor Assistant
Department of Architecture and Art, Hebei University of Architecture, Zhangjiakou 075024, China
Interests: urban and rural planning; intelligent building and smart city; urban renewal planning and design; space information technology of urban planning

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Guest Editor Assistant
School of Economics and Management, Hebei University of Technology, Tianjin 300401, China
Interests: project management and risk control; urban renewal; AI in construction industry; real estate operation and management

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Guest Editor Assistant
School of Civil Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
Interests: construction economy; urban renewal; public-private partnership

Special Issue Information

Dear Colleagues,

As the construction industry progressively shifts towards greater intelligence, digitalization, and sustainable development, the application of large-scale AI models, represented by large language models (LLMs), has emerged as a pivotal technological force driving this transformation. These models are capable of processing and analyzing vast amounts of complex data, enabling prediction, optimization, and automated decision-making, which is revolutionizing various stages of building design, construction, operation, and maintenance. The potential of large-scale AI models to enhance productivity, optimize resource allocation, reduce environmental impact, and improve safety is increasingly being recognized and applied across the industry.

This Special Issue aims to explore the contributions of large-scale AI models in areas such as generative design, project management, construction robotics, BIM, digital twins, and urban renewal. The key topics of this Special Issue include, but are not limited to, the following:

  • Large language model;
  • AI-driven urban renewal planning and design;
  • Automation and robotics in construction;
  • Integration of BIM and digital twins;
  • Applications of AI in construction project management;
  • Social impact assessment in urban renewal;
  • AI-driven sustainable development of aging communities;
  • Adoption of digital technologies in the construction industry;
  • Industrialized construction.

Dr. Shuai Han
Dr. Guozong Zhang
Guest Editors

Dr. Yingwei Cui
Dr. Suhong Li
Dr. Yan Zhao
Guest Editor Assistants

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • large AI models
  • deep learning
  • natural language processing
  • BIM
  • digital twin
  • construction project management
  • full lifecycle

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Published Papers (1 paper)

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Research

26 pages, 9932 KiB  
Article
Evolutionary Game Analysis on the Promotion of Green Buildings in China Under the “Dual Carbon” Goals: A Multi-Stakeholder Perspective
by Yongbo Su and Zhichao Zhang
Buildings 2025, 15(8), 1392; https://doi.org/10.3390/buildings15081392 - 21 Apr 2025
Viewed by 152
Abstract
The promotion of green buildings offers an effective solution to climate change and resource scarcity. This study employs game theory to study the evolutionary decision-making processes and stable strategies among three principal stakeholders in the green building sector: the government, construction enterprises, and [...] Read more.
The promotion of green buildings offers an effective solution to climate change and resource scarcity. This study employs game theory to study the evolutionary decision-making processes and stable strategies among three principal stakeholders in the green building sector: the government, construction enterprises, and consumers. By analyzing the primary factors that shape these stakeholders’ strategies, we propose a tripartite evolutionary game model. We utilize MATLAB R2016a to simulate the evolutionary decision-making processes and stable strategies of the three stakeholders, verifying the effectiveness of our approach. Our findings indicate that the government, in its regulatory capacity, plays a critical role in influencing the green building market. Government subsidies and penalties significantly affect the decision-making behavior of enterprises and consumers; in addition, dynamic rewards and punishments can effectively restrain the fluctuation of the game process. The development of the green building market correlates with increased consumer willingness and capacity to purchase green buildings, coupled with significantly reduced construction costs. Throughout this progression, the government gradually withdraws its incentives and shifts toward a more relaxed regulatory stance. Our research also indicates that the cooperative behavior and evolution of the three stakeholders are heavily influenced by key parameters, regardless of their initial states. Full article
(This article belongs to the Special Issue Large-Scale AI Models Across the Construction Lifecycle)
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