IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v16y2024i7p225-d1423718.html
   My bibliography  Save this article

Building Information Modeling and Digital Twins for Functional and Technical Design of Smart Buildings with Distributed IoT Networks—Review and New Challenges Discussion

Author

Listed:
  • Gabriela Walczyk

    (Department of Power Electronics and Energy Control Systems, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Krakow, al. Mickiewicza 30, 30-059 Krakow, Poland)

  • Andrzej Ożadowicz

    (Department of Power Electronics and Energy Control Systems, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Krakow, al. Mickiewicza 30, 30-059 Krakow, Poland)

Abstract

Modern building automation systems implement plenty of advanced control and monitoring functions that consider various parameters like users’ activity, lighting, temperature changes, etc. Moreover, novel solutions based on the Internet of Things and cloud services are also being developed for smart buildings to ensure comfort of use, user safety, energy efficiency improvements, and integration with smart grids and smart city platforms. Such a wide spectrum of technologies and functions requires a novel approach in building automation systems design to provide effective implementation and flexibility during operation. At the same time, in the building design and operation industries, tools based on building information modeling and digital twins are being developed. This paper discusses the development directions and application areas of these solutions, identifying new trends and possibilities of their use in smart homes and buildings. In particular, the focus is on procedures for selecting automation functions, effective integration, and interoperability of building management systems with the Internet of Things, considering the organization of prediction mechanisms and dynamic functional changes in buildings and smart networks. Chosen solutions and functions should consider the requirements set out in the EN ISO 52120 standard and the guidelines defined for the Smart Readiness Indicator.

Suggested Citation

  • Gabriela Walczyk & Andrzej Ożadowicz, 2024. "Building Information Modeling and Digital Twins for Functional and Technical Design of Smart Buildings with Distributed IoT Networks—Review and New Challenges Discussion," Future Internet, MDPI, vol. 16(7), pages 1-28, June.
    • Handle: RePEc:gam:jftint:v:16:y:2024:i:7:p:225-:d:1423718
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/16/7/225/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/16/7/225/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bartlomiej Kawa & Piotr Borkowski, 2023. "Integration of Machine Learning Solutions in the Building Automation System," Energies, MDPI, vol. 16(11), pages 1-18, June.
    2. Pinto, Maria Cristina & Crespi, Giulia & Dell'Anna, Federico & Becchio, Cristina, 2023. "Combining energy dynamic simulation and multi-criteria analysis for supporting investment decisions on smart shading devices in office buildings," Applied Energy, Elsevier, vol. 332(C).
    3. Ilaria Vigna & Roberta Pernetti & Giovanni Pernigotto & Andrea Gasparella, 2020. "Analysis of the Building Smart Readiness Indicator Calculation: A Comparative Case-Study with Two Panels of Experts," Energies, MDPI, vol. 13(11), pages 1-18, June.
    4. Li, Wenzhuo & Wang, Shengwei, 2022. "A fully distributed optimal control approach for multi-zone dedicated outdoor air systems to be implemented in IoT-enabled building automation networks," Applied Energy, Elsevier, vol. 308(C).
    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. Andrzej Ożadowicz, 2023. "Technical, Qualitative and Energy Analysis of Wireless Control Modules for Distributed Smart Home Systems," Future Internet, MDPI, vol. 15(9), pages 1-21, September.
    2. Andrzej Ożadowicz & Gabriela Walczyk, 2023. "Energy Performance and Control Strategy for Dynamic Façade with Perovskite PV Panels—Technical Analysis and Case Study," Energies, MDPI, vol. 16(9), pages 1-23, April.
    3. Laura Canale & Marianna De Monaco & Biagio Di Pietra & Giovanni Puglisi & Giorgio Ficco & Ilaria Bertini & Marco Dell’Isola, 2021. "Estimating the Smart Readiness Indicator in the Italian Residential Building Stock in Different Scenarios," Energies, MDPI, vol. 14(20), pages 1-19, October.
    4. Ilaria Vigna & Jessica Balest & Wilmer Pasut & Roberta Pernetti, 2020. "Office Occupants’ Perspective Dealing with Energy Flexibility: A Large-Scale Survey in the Province of Bolzano," Energies, MDPI, vol. 13(17), pages 1-20, August.
    5. Paweł Kut & Katarzyna Pietrucha-Urbanik, 2024. "Bibliometric Analysis of Multi-Criteria Decision-Making (MCDM) Methods in Environmental and Energy Engineering Using CiteSpace Software: Identification of Key Research Trends and Patterns of Internati," Energies, MDPI, vol. 17(16), pages 1-27, August.
    6. Paris A. Fokaides & Christiana Panteli & Andri Panayidou, 2020. "How Are the Smart Readiness Indicators Expected to Affect the Energy Performance of Buildings: First Evidence and Perspectives," Sustainability, MDPI, vol. 12(22), pages 1-12, November.
    7. Li, Wenzhuo & Tang, Rui & Wang, Shengwei & Zheng, Zhuang, 2023. "An optimal design method for communication topology of wireless sensor networks to implement fully distributed optimal control in IoT-enabled smart buildings," Applied Energy, Elsevier, vol. 349(C).
    8. Li, Han & Johra, Hicham & de Andrade Pereira, Flavia & Hong, Tianzhen & Le Dréau, Jérôme & Maturo, Anthony & Wei, Mingjun & Liu, Yapan & Saberi-Derakhtenjani, Ali & Nagy, Zoltan & Marszal-Pomianowska,, 2023. "Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives," Applied Energy, Elsevier, vol. 343(C).
    9. Krzysztof Zagrajek & Mariusz Kłos & Desire D. Rasolomampionona & Mirosław Lewandowski & Karol Pawlak & Łukasz Baran & Tomasz Barcz & Przemysław Kołaczyński & Wojciech Suchecki, 2023. "Investing in Distributed Generation Technologies at Polish University Campuses during the Energy Transition Era," Energies, MDPI, vol. 16(12), pages 1-24, June.
    10. Majid Baseer & Christian Ghiaus & Roxane Viala & Ninon Gauthier & Souleymane Daniel, 2023. "pELECTRE-Tri: Probabilistic ELECTRE-Tri Method—Application for the Energy Renovation of Buildings," Energies, MDPI, vol. 16(14), pages 1-25, July.
    11. Esmaeilzadeh, Ahmad & Deal, Brian & Yousefi-Koma, Aghil & Zakerzadeh, Mohammad Reza, 2023. "How combination of control methods and renewable energies leads a large commercial building to a zero-emission zone – A case study in U.S," Energy, Elsevier, vol. 263(PD).
    12. Hernández, José L. & de Miguel, Ignacio & Vélez, Fredy & Vasallo, Ali, 2024. "Challenges and opportunities in European smart buildings energy management: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    13. Angeliki Kitsopoulou & Evangelos Bellos & Christos Tzivanidis, 2024. "An Up-to-Date Review of Passive Building Envelope Technologies for Sustainable Design," Energies, MDPI, vol. 17(16), pages 1-55, August.
    14. Thomas Märzinger & Doris Österreicher, 2020. "Extending the Application of the Smart Readiness Indicator—A Methodology for the Quantitative Assessment of the Load Shifting Potential of Smart Districts," Energies, MDPI, vol. 13(13), pages 1-24, July.
    15. Jiang, Yuliang & Zhu, Shanying & Xu, Qimin & Yang, Bo & Guan, Xinping, 2023. "Hybrid modeling-based temperature and humidity adaptive control for a multi-zone HVAC system," Applied Energy, Elsevier, vol. 334(C).
    16. Song, Siao & Sun, Hongfa & Long, Jibo & Tan, Xin & Li, Jinhua, 2024. "Light-thermal environment of vertical translucent enclosure structures under solar radiation and method of internal shading adjustment," Energy, Elsevier, vol. 289(C).
    17. Van Thillo, L. & Verbeke, S. & Audenaert, A., 2022. "The potential of building automation and control systems to lower the energy demand in residential buildings: A review of their performance and influencing parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).

    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:jftint:v:16:y:2024:i:7:p:225-:d:1423718. 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.