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Smart Cities and Infrastructure Systems by Digital Twins (DT) and...
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Smart Cities and Infrastructure Systems by Digital Twins (DT) and Building Information Modeling (BIM)

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 (20 September 2023) | Viewed by 2465

Special Issue Editors

Dr. Mingzhu Wang

E-Mail Website
Guest Editor
School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough LE11 3TU, UK
Interests: intelligent infrastructure monitoring and maintenance; smart construction; BIM; human-centric digital twin; computer vision; blockchain
Special Issues, Collections and Topics in MDPI journals
Dr. Long Chen

E-Mail Website
Guest Editor
School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough LE11 3TU, UK
Interests: common data environments from BIM to digital twin; digital twin for construction sites and O&M management; construction schedule monitoring and prediction (for complex projects); digital sustainability and resilience
Special Issues, Collections and Topics in MDPI journals
Dr. Vincent Gan

E-Mail Website
Guest Editor
Department of the Built Environment, National University of Singapore, Singapore 119243, Singapore
Interests: robot-assisted sensing; building information modelling; digital twins; digital construction
Special Issues, Collections and Topics in MDPI journals
Dr. Jun Ma

E-Mail Website
Guest Editor
Department of Urban Planning and Design, Faculty of Architecture, The University of Hong Kong, Hong Kong 999077, China
Interests: urban big data and urban computing; geographical artificial intelligence; spatiotemporal analysis

Special Issue Information

Dear Colleagues,

Smart cities address the challenges of urbanisation by monitoring and integrating critical infrastructures with Internet of Things (IoT) and providing smart services. Due to the complex characteristics and varied sizes of systems in smart cities and the inter-relations among them, the development of smart cities faces several challenges, e.g., real-time data collection and heterogenous data integration and management, etc. In recent years, new technologies, e.g., building information modelling (BIM), digital twin (DT), artificial intelligence (AI), blockchain, etc., have been explored in manufacturing, health care, and construction. Among them, DT has great potential for infrastructure and smart cities, with the capability to create a virtual duplicate of the physical world, simulate different scenarios, and support decision making. Nevertheless, applying DT to smart cities remains challenging because of their characteristics, e.g., ‘system of systems’ and the uncertainty of the stochastic data. This Special Issue aims to collect different research studies (e.g., technical papers, literature review, case studies, etc.) related to infrastructure and smart city development with emerging digital technologies. Potential topics include, but are not limited to:

  • Construction and management of infrastructure and smart cities;
  • DT or BIM for infrastructure and smart cities;
  • Cognitive digital technologies for infrastructure and smart cities (e.g., digital twin, AI, and blockchain)
  • Strategies for management and development of smart cities and infrastructure;
  • Methods and technologies for resilient and sustainable infrastructure and cities;
  • Uncertainty of smart city data.

Dr. Mingzhu Wang
Dr. Long Chen
Dr. Vincent Gan
Dr. Jun Ma
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 monthly 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

  • smart city
  • infrastructure construction and management
  • urban resilience and sustainability
  • digital twin
  • Building Information Modelling (BIM)
  • digital technologies
  • Artificial Intelligence (AI)
  • blockchain
  • system of systems
  • uncertainty

Published Papers (1 paper)

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Research

22 pages, 5433 KiB  
Article
Parametric BIM-Based Lifecycle Performance Prediction and Optimisation for Residential Buildings Using Alternative Materials and Designs
by Jielong Gan, Kexin Li, Xiuqi Li, Emil Mok, Patrick Ho, Jenny Law, Joey Lau, Raymond Kwok and Raymond Yau
Buildings 2023, 13(4), 904; https://doi.org/10.3390/buildings13040904 - 29 Mar 2023
Cited by 2 | Viewed by 2088
Abstract
Residential building construction is resource-intensive and significantly impacts the environment by embodied and operational carbon emissions. This study has adopted a parametric building information modelling (BIM)-based approach for a residential building to analyse its lifecycle carbon performance and to evaluate the optimisation potential [...] Read more.
Residential building construction is resource-intensive and significantly impacts the environment by embodied and operational carbon emissions. This study has adopted a parametric building information modelling (BIM)-based approach for a residential building to analyse its lifecycle carbon performance and to evaluate the optimisation potential through alternative material use and design. The study looks at a residential development project, applying an automatic calculation and analysis tool of upfront embodied carbon and BIM-based lifecycle energy simulation to predict carbon emissions from operating the built spaces. A parametric BIM model has been established to aid energy simulation and operational carbon assessment across a 50-year building lifetime, considering 1.5 °C Net-Zero World and 3 °C Hot House World climate scenarios. Various improvement opportunities for future residential development projects, from material selection to operational efficiencies, are explored. This includes quantitative analysis on architectural-structure design, low-carbon construction materials (e.g., cement substitutes, steel scraps, and green hydrogen steel), and novel design for construction approaches (such as modular integrated construction), with discussion around their impacts on optimising the building lifecycle carbon performance. This study provides a deeper understanding and insights into the lifecycle performance of residential buildings to facilitate further exploration of achieving a more sustainable and low-carbon built environment. Full article
(This article belongs to the Special Issue Smart Cities and Infrastructure Systems by Digital Twins (DT) and Building Information Modeling (BIM))
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