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Buildings
Special Issues
Digital Transformation in the Architecture, Engineering and Construction (AEC) Industry
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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: 1 September 2026 | Viewed by 3685

Special Issue Editors

Dr. Yi-Hsin Lin

E-Mail Website
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
Dr. Pin-Chao Liao

E-Mail Website
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
Dr. Ting-Kwei Wang

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
Dr. Zhao Xu

E-Mail Website
Guest Editor
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 250 words) can be sent to the Editorial Office for assessment.

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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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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40 pages, 4042 KB  
Article
Review of Information Completeness in As-Built Building Information Models for Project Delivery
by Xuefeng Zhao, Wenkai Yan, Huafei He, Yixin Lin, Jinsheng Li, Xiongtao Fan, Xiangjie Meng, Li Jiang and Yao Wang
Buildings 2026, 16(7), 1388; https://doi.org/10.3390/buildings16071388 - 1 Apr 2026
Viewed by 458
Abstract
The As-built Building Information Model (BIM) serves as a carrier of lifecycle information for the physical building and is a critical component of project handover. Despite the issuance of numerous delivery standards globally, efficient methods for reviewing information completeness remain insufficient, hindering the [...] Read more.
The As-built Building Information Model (BIM) serves as a carrier of lifecycle information for the physical building and is a critical component of project handover. Despite the issuance of numerous delivery standards globally, efficient methods for reviewing information completeness remain insufficient, hindering the timely and effective delivery of project information. To address this gap, this research employs ontology technology as its core to develop a method for reviewing information completeness in as-built architectural engineering BIMs. An ontological model is constructed using Protégé, Semantic Web Rule Language (SWRL) rules for Completeness Review are defined, and a Revit data extraction add-in is developed to store model data in a database and map it to an ontological knowledge base. An integrated review system for As-built BIM information completeness is subsequently built. This system automates the entire review workflow, encompassing data import, semantic conversion, rule-based reasoning, and result output. Validated through a teaching building case study, the system successfully and accurately identified missing attributes and documents within the model, demonstrating high accuracy and review efficiency. The proposed method and its accompanying review system provide a scalable, rule-driven solution for ensuring BIM integrity, effectively supporting digital delivery in the architecture, engineering, and construction (AEC) industry. Full article
(This article belongs to the Special Issue Digital Transformation in the Architecture, Engineering and Construction (AEC) Industry)
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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 1415
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
(This article belongs to the Special Issue Digital Transformation in the Architecture, Engineering and Construction (AEC) Industry)
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Review

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41 pages, 7381 KB  
Review
A Review of Construction and Demolition Waste Management: Resource Coordination and Multidimensional Interaction
by Yi-Hsin Lin, Weidong Yuan and Ting Wang
Buildings 2026, 16(7), 1437; https://doi.org/10.3390/buildings16071437 - 5 Apr 2026
Cited by 2 | Viewed by 744
Abstract
Accelerated urbanization and continuous infrastructure renewal have led to a rapid increase in construction and demolition waste (CDW), which accounts for approximately 20–50% of municipal solid waste in many developed countries. Consequently, effective management and resource utilization of CDW have become critical challenges [...] Read more.
Accelerated urbanization and continuous infrastructure renewal have led to a rapid increase in construction and demolition waste (CDW), which accounts for approximately 20–50% of municipal solid waste in many developed countries. Consequently, effective management and resource utilization of CDW have become critical challenges for sustainable urban development. To address these challenges, this study develops an integrated analytical framework for CDW recycling systems. Specifically, it constructs a “cloud-edge-terminal” collaborative recycling system and clarifies the interactions among material, information, and value flows. A three-dimensional coupling framework is further established to reconceptualize CDW management as a multivariate decision-making problem, alongside a multidimensional evaluation structure to support practical implementation and system optimization. Methodologically, the study adopts an integrative review approach supported by knowledge mapping analysis. A structured literature search and screening process was conducted using the Web of Science Core Collection (2015–2026) to ensure transparency and reproducibility in the literature identification and sample construction. The results propose a multidimensional coupling framework integrating resource coordination, information communication, and market trading into a unified decision system. The framework contributes an engineering-oriented analytical paradigm that promotes hierarchical decision coordination, dynamic multi-objective regulation, and integrated management of CDW recycling systems. Full article
(This article belongs to the Special Issue Digital Transformation in the Architecture, Engineering and Construction (AEC) Industry)
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