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Digital Twin and AI in Construction and Urban Sustainability

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A Special Issue of Applied Sciences (ISSN 2076-3417) belonging to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 2209

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Editors

Prof. Dr. Edyta Plebankiewicz

E-Mail Website
Guest Editor

Department of Construction Management, Cracow University of Technology, Warszawska 24 Street, 31-155 Cracow, Poland
Interests: costs in construction; construction investment process; fuzzy sets in civil engineering
Special Issues, Collections and Topics in MDPI journals

Dr. Jolanta Tamošaitienė

E-Mail Website
Guest Editor

Faculty of Civil Engineering, Vilnius Gediminas Technical University, Saulėtekio al. 11, 10223 Vilnius, Lithuania
Interests: construction; risk; MCDM; engineering; management
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Special Issue Information

Dear Colleagues,

The integration of Digital Twin (DT) technology and Artificial Intelligence (AI) is transforming the future of construction and urban sustainability. This Special Issue invites cutting-edge research and practical applications that demonstrate how these technologies can enhance the planning, design, construction, and operation of sustainable buildings, infrastructure, and cities.

Key topics of interest include the following:

Digital Twin frameworks for construction and urban environments;
AI-driven modeling, prediction, and optimization for sustainable design;
Smart construction management, monitoring, and performance assessment;
Integration of IoT, big data, and real-time analytics into DT systems;
Applications in energy efficiency, carbon reduction, and resource management;
Digital Twin and AI use in resilient, adaptive, and smart cities;
Simulation-based approaches for lifecycle assessment and decision making;
Human-centric and participatory design supported by DT and AI;
Decision support tools and MCDM techniques for optimized project planning.

We particularly encourage interdisciplinary contributions that connect engineering, computer science, architecture, and urban planning to address current sustainability challenges.

The goal of this Special Issue is to advance knowledge and practice in leveraging Digital Twin and AI to create more efficient, sustainable, and livable built environments. Original research articles, reviews, and case studies are all welcome.

Prof. Dr. Edyta Plebankiewicz
Dr. Jolanta Tamošaitienė
Guest Editors

Manuscript Submission Information

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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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences 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 2400 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

digital twin (DT)
AI-based management decision-making
construction management
lifecycle assessment (LCA)
circular economy and project management
building information modeling (BIM)
sustainable buildings and cities

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Published Papers (4 papers)

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Research

17 pages, 3788 KB

Open AccessCommunication

Algorithmic Bias and Defensive Placemaking: Implications of Generative AI Co-Creation for Urban Digital Twins

by Takayuki Suzuki and Andrew Dillon

Appl. Sci. 2026, 16(17), 8605; https://doi.org/10.3390/app16178605 (registering DOI) - 29 Aug 2026

Abstract

Urban Digital Twins excel at modeling physical infrastructure but remain structurally limited in capturing the qualitative, experiential dimensions of urban life—particularly sense of place, which empirical research links to civic stewardship and long-term sustainability. This study investigates whether generative AI can serve as a participatory elicitation interface for surfacing these missing human data layers. Through a mixed-methods experimental design, 24 residents of Austin, Texas, each selected a personally meaningful public urban space and created visual representations using both hand-drawn sketching and iterative co-creation with the text-to-image model DALL-E. Pre- and post-experiment surveys and semi-structured interviews captured participants’ perceptions of the outputs and self-reported shifts in place awareness. The findings reveal a dialectical tension: DALL-E consistently defaulted to generic visual archetypes, overriding participants’ localized descriptions. However, this algorithmic homogenization paradoxically deepened participants’ sense of place through a process we term ‘validation by contrast’—residents utilized the AI’s inaccurate outputs as a foil to consciously articulate what made their environments authentically meaningful. These findings suggest that for human-centric Digital Twins, the actionable data lies not in the AI-generated image itself, but in the negotiation process through which residents defend and crystallize their authentic spatial identity. Full empirical validation of this pattern, including systematic comparison across representation modalities, is reserved for future work. Full article

(This article belongs to the Special Issue Digital Twin and AI in Construction and Urban Sustainability)

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34 pages, 9368 KB

Open AccessArticle

Towards a Digital Twin of Heritage Buildings: Scan-to-BIM Documentation and DEMATEL-Based Analysis of LiDAR, IoT and AI Integration Pathways

by Grzegorz Oleniacz, Izabela Skrzypczak, Agnieszka Leśniak, Maria Mrówczyńska, Piotr Ochab and Joanna Figurska-Dudek

Appl. Sci. 2026, 16(16), 8305; https://doi.org/10.3390/app16168305 - 20 Aug 2026

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Abstract

This study proposes an integrated approach to the digital documentation and system-level analysis of heritage buildings, combining LiDAR-based data acquisition, H-BIM modelling and DEMATEL analysis. The novelty of the study lies in combining a Scan-to-BIM workflow with DEMATEL-based system analysis in order to identify causal and dependent stages in the heritage building digitisation process. The research was carried out on two heritage buildings in south-eastern Poland: the Church of St Onuphrius in Posada Rybotycka and a wooden manor house from Brzeziny preserved in the ethnographic park in Kolbuszowa. Terrestrial laser scanning was used to acquire high-resolution point clouds of the buildings, which then provided the basis for developing parametric H-BIM models within a Scan-to-BIM workflow. For the church case study, the geometric accuracy of the Scan-to-BIM output was verified by comparing measurements derived from the point cloud with traditional surveying data. The results confirmed the suitability of Scan-to-BIM for heritage documentation, with an average absolute deviation of approximately 7 mm and a maximum deviation not exceeding 31 mm. DEMATEL analysis was used to examine cause–effect relationships between seven stages of the digitisation process and to determine which stages have the greatest influence on subsequent activities. Preliminary assessment, LiDAR scanning and H-BIM modelling were identified as causal stages, while validation, IoT integration, AI-based predictive analysis and digital twin development were classified as effect stages. The study also outlines how H-BIM models may be extended through IoT sensors and AI-based analytics as a basis for future digital twin development. Full article

(This article belongs to the Special Issue Digital Twin and AI in Construction and Urban Sustainability)

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21 pages, 2661 KB

Open AccessArticle

Polynomial Interpolation Model for Gamma Radiation Dose-Rate Screening at Radiation-Hazardous Industrial Sites: A 2021 Case Study of the Base-S Tailings Facility

by Nabi Ibadov, Oleksandr Pylypenko, Anatoly Zelensky, Kostiantyn Dikarev, Ruslan Papirnyk and Vadym Seletskyi

Appl. Sci. 2026, 16(13), 6833; https://doi.org/10.3390/app16136833 - 7 Jul 2026

Viewed by 426

Abstract

Radiation monitoring at contaminated industrial sites is often restricted by safety, access, and operational constraints. Under such conditions, a modelling approach that can use a limited number of field measurements is useful for preliminary screening, route planning, and prioritization of verification surveys. This study presents a sparse spatiotemporal polynomial interpolation model for estimating the gamma radiation equivalent dose rate (EDR) along the perimeter of the Base-S radiation-hazardous industrial site. The model represents EDR as a function of spatial coordinates and time, and uses a reduced measurement structure consisting of four seasonal temporal nodes and five representative spatial nodes. The reduced structure is intended to support conservative preliminary assessment under the ALARA principle, not to replace field measurements. A 2021 case study is presented for 61 numbered perimeter points. The article presents one of the universal mathematical models developed by the authors to determine the impact of gamma radiation on the personnel of tailings facilities and industrial sites through the calculation of the equivalent dose rate during personnel residence stays, depending on time. The proposed polynomial interpolation model for rapid radiation dose assessment at radiation-hazardous industrial sites estimates equivalent dose-rate values for a specific planning case. The model represents the EDR field as a spatiotemporal polynomial f(x, y, t), where x and y are planar coordinates, and t is the day of the year. A conservative reduced scheme uses four seasonal maximum values and five representative spatial points to decrease the number of required field measurements and personnel residence time. For the 2021 case study, the model-estimated EDR at 61 numbered perimeter points ranged from 0.118 to 0.415 µSv/hour, with a mean of 0.242 µSv/hour. This model provides initial data for building a 2D model and, if necessary, a 3D model of radiation contamination within the research-object territory. The resulting 2D and 3D maps are interpreted as model-estimated visualization products. The proposed method, the model form of which is described as a cubic polynomial in t and a quadratic in x,y, allows for effective interpolation of complex multidimensional dependencies of observed data. Full article

(This article belongs to the Special Issue Digital Twin and AI in Construction and Urban Sustainability)

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24 pages, 924 KB

Open AccessArticle

Model to Assess the Intelligence Level of Buildings in the Hotel Industry by Applying Integrated Fuzzy Shannon Entropy and Fuzzy Multi-Objective Optimization on the Basis of Ratio Analysis

by Seyed Morteza Hatefi, Jolanta Tamošaitienė, Pardis Roshanayee and Ulrike Quapp

Appl. Sci. 2026, 16(6), 2652; https://doi.org/10.3390/app16062652 - 10 Mar 2026

Viewed by 514

Abstract

The rapid evolution of smart building technologies has transformed the hotel industry, necessitating structured methodologies for evaluating building intelligence. This research, dedicated to engineering problems, proposes an integrated decision-making model that combines fuzzy Shannon entropy and fuzzy multi-objective optimization on the basis of ratio analysis (MOORA) to assess the intelligence level of buildings within the hospitality sector. The model systematically determines the relative importance of intelligence criteria, including engineering, environmental, economic, social and cultural, technological, and energy conservation criteria. By leveraging fuzzy Shannon entropy, the framework objectively assigns weights to criteria based on information distribution, minimizing subjective biases in evaluation. Fuzzy MOORA is then applied to rank alternative intelligent buildings in hotels, ensuring an accurate comparative assessment. The proposed model is tested on real-world hotel data, demonstrating its effectiveness in identifying optimal intelligent building configurations. The results of applying fuzzy Shannon entropy reveal that human comfort, the emission of greenhouse gases (pollution), and system integration are the most important sub-criteria. Finally, by applying the importance of the criteria in the fuzzy MOORA model, the intelligence levels of hotels are evaluated. The results show that the Parsian Kowsar, Piroozy and Sepahan Hotels are the best hotels based on the intelligent building criteria. Full article

(This article belongs to the Special Issue Digital Twin and AI in Construction and Urban Sustainability)

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