Digital Transformation in the Architecture, Engineering and Construction (AEC) Industry

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 January 2026 | Viewed by 626

Special Issue Editors


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Guest Editor
Department of Construction and Real Estate, School of Civil Engineering, Southeast University, Nanjing 211189, China
Interests: blockchain technology applications; circular economy and waste recycling; green economy and low-carbon development; construction market and economy; international construction management

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Guest Editor
Department of Construction Management, School of Civil Engineering, Tsinghua University, Beijing 100084, China
Interests: occupational health and safety; cognitive/behavior science; risk analysis; data/visual analytics
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Civil Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 807618, Taiwan
Interests: BIM; AR/VR; artificial intelligence; computer vision; generative design
Special Issues, Collections and Topics in MDPI journals
Department of Civil Engineering, Southeast University, Nanjing 211189, China
Interests: intelligent construction; BIM; smart cities
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will focus on the digital transformation of the Architecture, Engineering, and Construction (AEC) industry, highlighting how emerging technologies are reshaping project planning, design, construction, and facility management. The integration of Building Information Modeling (BIM), artificial intelligence, big data, the Internet of Things (IoT), and blockchain technology is accelerating the shift toward smart construction and sustainable development.

We welcome original contributions from both academia and industry that explore the application of digital tools, cross-disciplinary collaboration, data integration, and innovative business models. This Special Issue aims to enhance efficiency, quality, and innovation across the AEC sector by addressing the opportunities and challenges of digitalization.

We expect that our collective efforts will help pave the way for an AEC industry that is not only technologically advanced but also sustainable and resilient in the face of the uncertainties of the 21st century. The suggested topics include, but are not limited to, the following:

  • Blockchain technology applications;
  • The Internet of Things (IoT);
  • Occupational health and safety;
  • Cognitive science;
  • Data and visual analytics;
  • Cutting-edge technologies;
  • Computer vision;
  • Generative design;
  • Intelligent risk assessment;
  • AR-enhanced structural engineering;
  • The use of advanced automated decision-making systems in quality inspection;
  • The use of computer vision and ontology in construction quality control;
  • Smart construction;
  • Building and City Information Modeling (BIM/CIM);
  • Intelligent information processing;
  • Building information technologies;
  • Infrastructure health monitoring;
  • Disaster early warning systems;
  • Resilient city development. 

More examples of Special Issues of Buildings can be found at https://www.mdpi.com/journal/buildings/special_issues.

Original research articles, case studies, and review papers are all welcome for this Special Issue.

Dr. Yi-Hsin Lin
Dr. Pin-Chao Liao
Dr. Ting-Kwei Wang
Dr. Zhao Xu
Guest Editors

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

  • BIM
  • blockchain technology applications
  • AR-enhanced structural engineering
  • data and visual analytics
  • smart construction
  • infrastructure health monitoring
  • resilient city development

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Published Papers (1 paper)

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Research

28 pages, 4359 KB  
Article
Application of Integration of Transfer Learning and BIM Technology in Prefabricated Building Design Optimization
by Ting Ouyang, Fengtao Liu, Lingling Chen, Dongyue Qin and Sining Li
Buildings 2025, 15(17), 3029; https://doi.org/10.3390/buildings15173029 - 25 Aug 2025
Viewed by 257
Abstract
With the continuous maturation of prefabricated buildings, the errors and efficiency issues in the design of prefabricated buildings have gradually drawn the attention of architectural designers. The characteristics of standardized design for prefabricated buildings also provide a foundation for the application of computer-learning [...] Read more.
With the continuous maturation of prefabricated buildings, the errors and efficiency issues in the design of prefabricated buildings have gradually drawn the attention of architectural designers. The characteristics of standardized design for prefabricated buildings also provide a foundation for the application of computer-learning methods in the field of architectural design, thereby improving design quality and efficiency. This study combined BIM technology to construct the information data on prefabricated buildings, applied the transfer-learning method to build the training model, and utilized the traditional architectural design collision concept to construct a prediction model applicable to the collision detection of prefabricated building design. The training set and test set were constructed in a 9:1 ratio, and the loss function and accuracy function were calculated. The error rate of the model was verified to be within 10% through trial calculations based on engineering cases. The results show that, in the selected engineering cases, the collision detection accuracy of the model reached 90.3%, with an average absolute error (MAE) of 0.199 and a root mean square error (RMSE) of 0.245. The prediction error rate was controlled within 10%, representing an approximately 65% improvement in efficiency compared to traditional manual inspections. This method significantly improves the efficiency and accuracy of collision detection, providing reliable technical support for the optimization of prefabricated building design. Full article
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