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

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 22987

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Special Issue Editors

Dr. Lin Liu

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Guest Editor

School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou 510006, China
Interests: urban climatic modeling; carbon neutrality scenario prediction; environmental suitability assessment; urban smart energy management
Special Issues, Collections and Topics in MDPI journals

Dr. Taotao Shui

E-Mail Website
Guest Editor

School of Environment and Energy Engineering, Anhui Jianzhu University, Hefei 230601, China
Interests: urban microclimate; urban energy budget; urban pollutant dispersion; thermal comfort; carbon emission

Dr. Chun Wang

E-Mail Website
Guest Editor

School of Management, Chongqing University of Science and Technology, Chongqing 401331, China
Interests: building informatization; low-carbon smart buildings; virtual restoration of traditional buildings; information management of engineering projects

Special Issue Information

Dear Colleagues,

The development of intelligent construction is a core driving force to break through industry bottlenecks and accelerate construction industry transformation for the future. Intelligent construction integrates a series of advanced technologies and involves many areas of expertise in civil engineering, computer application, engineering management, mechanical automation, electrical power systems, clean energy, and other fields of knowledge. It should be noted that intelligent construction is inseparable from intelligent operation and maintenance. Reasonable management methods and operational control strategies significantly contribute to the construction industry with efficiency and low-carbon strategies resulting in comprehensive, coordinated, and sustainable development. Therefore, intelligent construction should consider various factors to obtain a balance between economic and environmental comfort. This special issue welcomes all advanced theories and technologies related to intelligent construction, including but not limited to the following topics:

Project management knowledge;
Management decision making;
BIM technology;
HSE evaluation;
Prefabricated building technology;
Green building technology;
Building big data;
Artificial intelligence;
Smart cities;
Intelligent energy use management;
Multi-scale information databases;
Other new technologies in communities, buildings, cities, industry parks, etc.

Dr. Lin Liu
Dr. Taotao Shui
Dr. Chun Wang
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

artificial intelligence
project management
decision-making method
intelligent buildings
building information modeling
smart cities
intelligent management
low-carbon strategy
intelligent power technology
intelligence algorithm

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Published Papers (10 papers)

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Research

20 pages, 2769 KB

Open AccessArticle

Internal and External Landscape Features of 18 Parks in Hangzhou, China That Cool the Park and the Surrounding Urban Areas: Strategies for Other Cities

by Tao Ma, Mengxin Yang, Shaojie Zhang, Xiaofan Jiang and Wenbin Nie

Buildings 2026, 16(3), 630; https://doi.org/10.3390/buildings16030630 - 2 Feb 2026

Viewed by 668

Abstract

As one of China’s “New Four Furnaces”, the city of Hangzhou faces significant heat challenges exacerbated by rapid urbanization. Urban parks offer effective nature-based solutions, but optimizing their multi-dimensional cooling performance—encompassing cooling area (PCA), efficiency (PCE), intensity (PCI), and gradient (PCG)—remains a key challenge. This study quantitatively analyzed the internal and external landscape features of 18 parks in Hangzhou, revealing that park cooling performance is not simply a case of “bigger is better.” We found that parks with more complex shapes and irregular boundaries exhibited higher cooling efficiency per unit area (PCE) compared to larger parks with smooth, simple shapes, though sometimes at the expense of peak PCI. Furthermore, the surrounding built environment is critical: high building density within a 300 m buffer zone was found to significantly impede the spatial extent of the cooling effect (PCA). Based on these findings, we propose that to effectively mitigate urban heat, cities should (1) shift focus away from creating large, isolated parks with smooth boundaries; (2) prioritize a network of smaller, morphologically diverse parks with irregular edges that extend into the community; and (3) enhance each park’s cooling reach through strategies like green streets and tree-lined paths. These approaches offer tangible, actionable guidance for designing high-performance cooling green infrastructure in dense urban environments. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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26 pages, 2649 KB

Open AccessArticle

Energy-Efficient Multi-Objective Scheduling for Modern Construction Projects with Dynamic Resource Constraints

by Mudassar Rauf and Jabir Mumtaz

Buildings 2026, 16(2), 392; https://doi.org/10.3390/buildings16020392 - 17 Jan 2026

Viewed by 525

Abstract

The rapidly evolving business landscape, driven by stringent energy conservation policies, compels construction firms to adopt energy-efficient project-centric structures, particularly in modern construction projects. These firms face a complex, multi-mode, resource-constrained, multi-project scheduling problem characterized by dynamic project arrivals and multiple resource constraints, including global, local, and non-renewable capacities. This environment pressures managers to simultaneously optimize the conflicting objectives of minimizing total project duration and total energy consumption. To address this challenge, we propose a novel multi-objective Smart Raccoon Family Optimization (SRFO) algorithm. The SRFO, a hybrid evolutionary approach, is designed to enhance global exploration and local exploitation. Its performance is boosted by integrating a non-dominated sorting mechanism, a dedicated energy-efficient search strategy, and enhanced genetic operators. The SRFO simultaneously optimizes two conflicting objectives: minimizing the total project duration and total energy consumption. This approach effectively integrates the unique constraint of off-site component production and on-site assembly within an intelligent scheduling framework. Empirical validation across benchmark problems and a real-world case study is conducted, comparing the SRFO with existing multi-objective approaches, such as NSGA-III, MOABC, and MOSMO. Performance is assessed using convergence and distribution metrics, augmented by TOPSIS-based multi-criteria decision-making. Results conclusively demonstrate that the proposed SRFO significantly outperforms existing approaches and offers a robust, high-quality solution for project management in energy-constrained environments. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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24 pages, 4033 KB

Open AccessArticle

Integrating PC Splitting Design and Construction Organization Through Multi-Agent Simulation for Prefabricated Buildings

by Yi Shen, Jing Wang and Guan-Hang Jin

Buildings 2025, 15(20), 3773; https://doi.org/10.3390/buildings15203773 - 19 Oct 2025

Viewed by 1490

Abstract

Prefabricated building projects represent industrialized and intelligent construction through factory production, standardized design, and mechanized assembly. This study presents a multi-agent simulation approach to model the prefabricated construction process, allowing for the concurrent optimization of the prefabricated component (PC) splitting design and the construction organization plan through iterative simulation. (1) Employing a questionnaire survey, it identifies critical factors affecting schedule and cost from a design–construction coordination perspective. (2) Based on these findings, an agent-based model was developed incorporating PC installation, crane operations, and storage yard spatial constraints, along with interaction rules governing these agents. (3) Data interoperability was achieved among Revit, NetLogo3D and Navisworks. This integrated environment offers project managers digital management of design and construction plans, simulation support, and visualization tools. Simulation results confirm that a hybrid resource allocation strategy utilizing both tower cranes and mobile cranes enhances resource leveling, accelerates schedule performance, and improves cost efficiency. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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17 pages, 1739 KB

Open AccessArticle

Dynamic Multi-Model Container Framework for Cloud-Based Distributed Digital Twins (dDTws)

by Nidhal Al-Sadoon, Raimar J. Scherer and Christoph F. Strnadl

Buildings 2025, 15(10), 1722; https://doi.org/10.3390/buildings15101722 - 19 May 2025

Cited by 3 | Viewed by 1949

Abstract

The increasing complexity of data management in the Architecture, Engineering, and Construction (AEC) industry, driven by the adoption of distributed digital twins (dDTws) and cloud-based solutions, presents challenges in interoperability, data sovereignty, and scalability. Existing Building Information Modeling (BIM) and Common Data Environment (CDE) frameworks often fall short in addressing these issues due to their reliance on centralized and proprietary systems. This paper introduces a novel framework that transforms the Information Container for Linked Document Delivery (ICDD) into a dynamic, graph-based architecture. Unlike conventional file-based ICDD implementations, this approach enables fine-grained, semantically rich linking and querying across distributed models while maintaining data sovereignty and version control. The framework is designed to enhance real-time collaboration, ensure secure and sovereign data management, and improve interoperability across diverse project stakeholders. The framework leverages graph databases, semantic web technologies, and ISO standards such as ISO 21597 to facilitate seamless data exchange, automated linking, and advanced version control. Key functionalities include federated data storage, compliance with local and international regulations, and support for multidisciplinary workflows in large-scale AEC projects. To demonstrate the feasibility of the proposed framework, a simplified use case scenario is implemented and analyzed. By addressing critical challenges and enabling seamless integration of emerging technologies such as digital twins, this study advances the state of the art in data management for the AEC industry, providing a robust foundation for future innovations. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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35 pages, 3518 KB

Open AccessArticle

Agile Construction Digital Twin Engineering

by Philipp Zech, Alexandra Jäger, Larissa Schneiderbauer, Hans Exenberger, Georg Fröch and Matthias Flora

Buildings 2025, 15(3), 386; https://doi.org/10.3390/buildings15030386 - 26 Jan 2025

Cited by 5 | Viewed by 3007

Abstract

Digital twins have attracted a lot of attention recently. However, the current manifestations are merely digital shadows, lacking means for bidirectional data exchange, which makes their use for assisting the construction of buildings much more difficult. We argue that this is due to the lack of a systematic process for developing a digital twin during a building’s life cycle. We argue to look for a solution by combining agile engineering with IT change management to establish an agile, change-driven process for engineering digital twins. Such a process, of course, deserves a qualitative assessment of the engineering process and the resulting digital twin. In the future, it should be possible to obtain a digital twin from a BIM-based design process by applying IT change management in an agile manner. This should happen under maximum automation and life cycle orientation. Our proposal is motivated by several years of interdisciplinary collaboration between civil engineering and computer science and evaluated using the Technology Acceptance Model. While the TAM is not specifically designed for digital twin methodologies, its application here aims to assess perceived usefulness and ease of use of DT methodologies from the user’s perspective, without addressing scalability concerns. This aims to provide actionable insights to guide the refinement of the process model, aligning it with user requirements and achieving its intended outcomes. Our evaluation confirms the proposed process’s perceived usefulness and ease of use, with robust correlations indicating strong acceptance potential among stakeholders. These results highlight the feasibility of the proposed approach and its alignment with expectations in real-world applications. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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16 pages, 2247 KB

Open AccessArticle

Semantic Segmentation of Heavy Construction Equipment Based on Point Cloud Data

by Suyeul Park and Seok Kim

Buildings 2024, 14(8), 2393; https://doi.org/10.3390/buildings14082393 - 2 Aug 2024

Cited by 5 | Viewed by 3172

Abstract

Most of the currently developed 3D point cloud data-based object recognition algorithms have been designed for small indoor objects, posing challenges when applied to large-scale 3D point cloud data in outdoor construction sites. To address this issue, this research selected four high-performance deep learning-based semantic segmentation algorithms for large-scale 3D point cloud data: Rand-LA-Net, KPConv Rigid, KPConv Deformable, and SCF-Net. These algorithms were trained and validated using 3D digital maps of earthwork sites to build semantic segmentation models, and their performance was tested and evaluated. The results of this research represent the first application of 3D semantic segmentation algorithms to large-scale 3D digital maps of earthwork sites. It was experimentally confirmed that object recognition technology can be implemented in the construction industry using 3D digital maps composed of large-scale 3D point cloud data. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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18 pages, 3336 KB

Open AccessArticle

Research on Arrangement of Measuring Points for Modal Identification of Spatial Grid Structures

by Chunjuan Zhou, Jinzhi Wu, Guojun Sun, Jie Hu, Qize Xu, Yang Li and Mingliang Liu

Buildings 2024, 14(8), 2338; https://doi.org/10.3390/buildings14082338 - 28 Jul 2024

Cited by 2 | Viewed by 1648

Abstract

In structural health monitoring, because the number of sensors used is far lower than the number of degrees of freedom of the structure being monitored, the optimization problem of the location and number of sensors in the structures is becoming more and more prominent. However, spatial grid structures are complex and diverse, and their dynamic characteristics are complex. It is difficult to accurately measure their vibration information. Therefore, an appropriate optimization method must be used to determine the optimal positioning of sensor placement. Aiming at the problem that spatial grid structures have many degrees of freedom and the fact that it is difficult to obtain complete vibration information, this paper analyzed the typical EI method, MKE method, and EI-MKE method in the arrangement of the measuring points, and it was verified that the EI method was more suitable for the vibration detection of spatial grid structures through the example of a plane truss and spatial grid structures. Measuring points under the assumption of structural damage were explored, and it was proposed that there might have been a stable number of measuring points that could cover the possible vibration mode changes in the structures. At the same time, combined with the three-level improved Guyan recursive technique, in order to obtain better complete modal parameters, the influence of the number of measuring points on the complete vibration mode information was studied. It was concluded that MAC_d was better than MAC_n as the quantitative target. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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16 pages, 8270 KB

Open AccessArticle

Numerical Analysis of Dynamic Characteristics of an Asymmetric Tri-Stable Piezoelectric Energy Harvester under Random Vibrations in Building Structures

by Dawei Man, Qingnan Hu, Qinghu Xu, Liping Tang, Dong Chen, Ziqing Yuan and Tingting Han

Buildings 2024, 14(7), 2210; https://doi.org/10.3390/buildings14072210 - 18 Jul 2024

Cited by 3 | Viewed by 1595

Abstract

This study presents a novel design for a tri-stable piezoelectric vibration energy harvester with an asymmetric structure, which is enhanced with an elastic base (TPVEH + EB), meticulously designed to enhance energy extraction from irregular vibrations in architectural structures. The cornerstone of this design is the asymmetric tri-stable piezoelectric cantilever beam, distinctively arranged within a U-shaped block and fortified with an elastic foundation. A carefully positioned spring (kf)-mass (Mf) system between the U-shaped block and the beam’s fixed end significantly boosts the vertical displacement of the beam during oscillations. Utilizing Lagrange’s equations, we formulated a dynamic model for the asymmetric TPVEH + EB, examining the effects of potential well asymmetry, the stiffness of the elastic base and spring-mass system, the mass of the spring-mass system, and the tip magnet mass on the system’s nonlinear dynamic responses. Our results demonstrate that the asymmetric TPVEH + EB significantly enhances energy harvesting from low-amplitude random vibrations (1.5 g), with the output voltage of the asymmetric TPVEH + EB increasing by 30% and the output power by 25%. Extensive numerical and theoretical analyses verify that the asymmetric TPVEH + EB provides a highly efficient solution for scenarios typically hindered by low energy conversion rates. Its reliable performance under varied and unpredictable excitation conditions highlights its excellence in advanced energy harvesting applications. The improvements detailed in this research underscore the potential of the asymmetric TPVEH + EB to boost energy harvesting efficiency, particularly in powering wireless sensor nodes for structural health monitoring in buildings. By overcoming the limitations of traditional harvesters, the asymmetric TPVEH + EB ensures enhanced efficiency and reliability, making it an ideal solution for a wide range of practical applications in diverse environmental conditions within buildings. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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24 pages, 8737 KB

Open AccessArticle

Adaptability Analysis of Integrated Project Delivery Method in Large- and Medium-Sized Engineering Projects: A FAHP-Based Modeling Solution

by Huiyu He, Xiwei Gan, Lin Liu and Xing Zhang

Buildings 2024, 14(7), 1999; https://doi.org/10.3390/buildings14071999 - 2 Jul 2024

Viewed by 5089

Abstract

With the emerging large- and medium-sized engineering projects, prominent project delivery methods make sense in terms of cost, risk, management, and schedule. Among these, the Integrated Project Delivery (IPD) method stands out due to its adaptability for growing scale and complexity projects. This study compares the IPD method with other methods, emphasizing its benefits in large- and medium-sized projects and introducing the Fuzzy Analytic Hierarchy Process (FAHP) model to analyze IPD’s adaptability quantitatively. By conducting a matrix calculation of eighteen second-level indicators, this study derived weight values for four first-level indicators: Cost control, Risk control, Management control, and Schedule control. These first-level indicators were then used to formulate the total evaluation index calculation. Based on this foundation, we verified the calculations using a case study in Fujian. Implementing the IPD method led to a lower cost than the Owner’s Representative method and a one-year schedule acceleration. The FAHP model introduced in this study offers a novel and objective approach for adaptability analysis of the IPD method in large- and medium-sized engineering projects, coupling decision theory into project management. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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17 pages, 11688 KB

Open AccessArticle

Analysis of Progressive Collapse Resistance in Precast Concrete Frame with a Novel Connection Method

by Qinghu Xu, Junjie Qian, Yu Zhang, Liping Tang, Dawei Man, Xuezhi Zhen and Tingting Han

Buildings 2024, 14(6), 1814; https://doi.org/10.3390/buildings14061814 - 14 Jun 2024

Cited by 7 | Viewed by 2316

Abstract

The configuration of beam–column joints in precast concrete (PC) building structures varies widely, and different connection methods significantly affect the progressive collapse resistance of the structure. This study investigates the progressive collapse resistance of an innovative beam–column connection node frame. Finite element models of four-story, two-span space frame structures made of reinforced concrete (RC) and PC were developed using ANSYS 14.0/LS-DYNA R5.x software, employing nonlinear dynamic and static analysis to examine structural collapse behavior under bottom middle or corner column damage. Numerical results indicate that following the failure of the middle or corner column due to explosion loading, the vertical displacement and collapse rate of the PC structure with the novel connection method are less than those of the RC structure during collapse progression. Furthermore, upon removal of the middle or corner column, the residual load-carrying capacity of the PC structure with the innovative connection increased by 7% and 3.7%, respectively, compared to the RC structure. This suggests that PC structures with this type of connection demonstrate superior performance in resisting progressive collapse, offering valuable insights for future engineering applications. Full article

(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)

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