IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i12p4497-d843428.html
   My bibliography  Save this article

Digital Twin and Cloud BIM-XR Platform Development: From Scan-to-BIM-to-DT Process to a 4D Multi-User Live App to Improve Building Comfort, Efficiency and Costs

Author

Listed:
  • Fabrizio Banfi

    (GIcarus ABCLab, Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Ponzio 31, 20133 Milan, Italy)

  • Raffaella Brumana

    (GIcarus ABCLab, Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Ponzio 31, 20133 Milan, Italy)

  • Graziano Salvalai

    (RE3_Lab, Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Ponzio 31, 20133 Milan, Italy)

  • Mattia Previtali

    (GIcarus ABCLab, Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Via Ponzio 31, 20133 Milan, Italy)

Abstract

Digital twins (DTs) and building information modelling (BIM) are proving to be valuable tools for managing the entire life cycle of a building (LCB), from the early design stages to management and maintenance over time. On the other hand, BIM platforms cannot manage the geometric complexities of existing buildings and the large amount of information that sensors can collect. For this reason, this research proposes a scan-to-BIM process capable of managing high levels of detail (LODs) and information (LOIs) during the design, construction site management, and construction phases. Specific grades of generation (GOGs) were applied to create as-found, as-designed, and as-built models that interact with and support the rehabilitation project of a multi-level residential building. Furthermore, thanks to the sharing of specific APIs (Revit and Autodesk Forge APIs), it was possible to switch from static representations to novel levels of interoperability and interactivity for the user and more advanced forms of building management such as a DT, a BIM cloud, and an extended reality (XR) web platform. Finally, the development of a live app shows how different types of users (professionals and non-expert) can interact with the DT, in order to know the characteristics with which the environments have been designed, as well as the environmental parameters, increasing their degree of control, from the point of view of improving comfort, use, costs, behaviour, and good practices. Finally, the overall approach was verified through a real case study where the BIM-XR platform was built for energy improvements to existing buildings and façade renovations.

Suggested Citation

  • Fabrizio Banfi & Raffaella Brumana & Graziano Salvalai & Mattia Previtali, 2022. "Digital Twin and Cloud BIM-XR Platform Development: From Scan-to-BIM-to-DT Process to a 4D Multi-User Live App to Improve Building Comfort, Efficiency and Costs," Energies, MDPI, vol. 15(12), pages 1-26, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4497-:d:843428
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/12/4497/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/12/4497/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rongyue Zheng & Jianlin Jiang & Xiaohan Hao & Wei Ren & Feng Xiong & Yi Ren, 2019. "bcBIM: A Blockchain-Based Big Data Model for BIM Modification Audit and Provenance in Mobile Cloud," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-13, March.
    2. Nawal Abdunasseer Hmidah & Nuzul Azam Haron & Aidi Hizami Alias & Teik Hua Law & Abubaker Basheer Abdalwhab Altohami & Raja Ahmad Azmeer Raja Ahmad Effendi, 2022. "The Role of the Interface and Interface Management in the Optimization of BIM Multi-Model Applications: A Review," Sustainability, MDPI, vol. 14(3), pages 1-29, February.
    3. Kendrik Yan Hong Lim & Pai Zheng & Chun-Hsien Chen, 2020. "A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1313-1337, August.
    4. Abubaker Basheer Abdalwhab Altohami & Nuzul Azam Haron & Aidi Hizami Ales@Alias & Teik Hua Law, 2021. "Investigating Approaches of Integrating BIM, IoT, and Facility Management for Renovating Existing Buildings: A Review," Sustainability, MDPI, vol. 13(7), pages 1-30, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jyrki Savolainen & Michele Urbani, 2021. "Maintenance optimization for a multi-unit system with digital twin simulation," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1953-1973, October.
    2. Jan Růžička & Jakub Veselka & Zdeněk Rudovský & Stanislav Vitásek & Petr Hájek, 2022. "BIM and Automation in Complex Building Assessment," Sustainability, MDPI, vol. 14(4), pages 1-20, February.
    3. Remigiusz Iwańkowicz & Radosław Rutkowski, 2023. "Digital Twin of Shipbuilding Process in Shipyard 4.0," Sustainability, MDPI, vol. 15(12), pages 1-27, June.
    4. Saporiti, Nicolò & Cannas, Violetta Giada & Pozzi, Rossella & Rossi, Tommaso, 2023. "Challenges and countermeasures for digital twin implementation in manufacturing plants: A Delphi study," International Journal of Production Economics, Elsevier, vol. 261(C).
    5. Fromhold-Eisebith, Martina & Marschall, Philip & Peters, Robert & Thomes, Paul, 2021. "Torn between digitized future and context dependent past – How implementing ‘Industry 4.0’ production technologies could transform the German textile industry," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    6. Angelo Corallo & Vito Del Vecchio & Marianna Lezzi & Paola Morciano, 2021. "Shop Floor Digital Twin in Smart Manufacturing: A Systematic Literature Review," Sustainability, MDPI, vol. 13(23), pages 1-24, November.
    7. Weifei Hu & Jinyi Shao & Qing Jiao & Chuxuan Wang & Jin Cheng & Zhenyu Liu & Jianrong Tan, 2023. "A new differentiable architecture search method for optimizing convolutional neural networks in the digital twin of intelligent robotic grasping," Journal of Intelligent Manufacturing, Springer, vol. 34(7), pages 2943-2961, October.
    8. Rong Xie & Muyan Chen & Weihuang Liu & Hongfei Jian & Yanjun Shi, 2021. "Digital Twin Technologies for Turbomachinery in a Life Cycle Perspective: A Review," Sustainability, MDPI, vol. 13(5), pages 1-22, February.
    9. Paula Morella & María Pilar Lambán & Jesús Royo & Juan Carlos Sánchez & Jaime Latapia, 2023. "Technologies Associated with Industry 4.0 in Green Supply Chains: A Systematic Literature Review," Sustainability, MDPI, vol. 15(12), pages 1-24, June.
    10. Haiying Luan & Long Li & Shengxi Zhang, 2022. "Exploring the Impact Mechanism of Interface Management Performance of Sustainable Prefabricated Construction: The Perspective of Stakeholder Engagement," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    11. Abubaker Basheer Abdalwhab Altohami & Nuzul Azam Haron & Aidi Hizami Ales@Alias & Teik Hua Law, 2021. "Investigating Approaches of Integrating BIM, IoT, and Facility Management for Renovating Existing Buildings: A Review," Sustainability, MDPI, vol. 13(7), pages 1-30, April.
    12. Gurtej Singh Saini & AmirHossein Fallah & Pradeepkumar Ashok & Eric van Oort, 2022. "Digital Twins for Real-Time Scenario Analysis during Well Construction Operations," Energies, MDPI, vol. 15(18), pages 1-22, September.
    13. Elisa Negri & Vibhor Pandhare & Laura Cattaneo & Jaskaran Singh & Marco Macchi & Jay Lee, 2021. "Field-synchronized Digital Twin framework for production scheduling with uncertainty," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1207-1228, April.
    14. Fuwen Hu & Xianjin Qiu & Guoye Jing & Jian Tang & Yuanzhi Zhu, 2023. "Digital twin-based decision making paradigm of raise boring method," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2387-2405, June.
    15. Nawal Abdunasseer Hmidah & Nuzul Azam Haron & Aidi Hizami Alias & Teik Hua Law & Abubaker Basheer Abdalwhab Altohami & Raja Ahmad Azmeer Raja Ahmad Effendi, 2022. "The Role of the Interface and Interface Management in the Optimization of BIM Multi-Model Applications: A Review," Sustainability, MDPI, vol. 14(3), pages 1-29, February.
    16. Leung, Eric K.H. & Lee, Carmen Kar Hang & Ouyang, Zhiyuan, 2022. "From traditional warehouses to Physical Internet hubs: A digital twin-based inbound synchronization framework for PI-order management," International Journal of Production Economics, Elsevier, vol. 244(C).
    17. SungKu Kang & Ran Jin & Xinwei Deng & Ron S. Kenett, 2023. "Challenges of modeling and analysis in cybermanufacturing: a review from a machine learning and computation perspective," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 415-428, February.
    18. Tingchen Fang & Yiming Zhao & Jian Gong & Feiliang Wang & Jian Yang, 2021. "Investigation on Maintenance Technology of Large-Scale Public Venues Based on BIM Technology," Sustainability, MDPI, vol. 13(14), pages 1-18, July.
    19. Madalina CUC, 2021. "Improving The Decision-Making Process By Modeling Digital Twins In A Big Data Environment," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(1), pages 138-154, May.
    20. Georgios Falekas & Athanasios Karlis, 2021. "Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects," Energies, MDPI, vol. 14(18), pages 1-26, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4497-:d:843428. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.