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The Efficiency of Building Maintenance Using Digital Twins: A Literature Review

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Advanced Information Networking and Applications (AINA 2024)

Abstract

As buildings severely impact global energy consumption and greenhouse gas emissions, effective maintenance becomes more important for their performance and sustainability. On the other hand, digital twins, as a promising technology, enhance building operation and maintenance by providing near real-time data and insights. To better understand the efficiency of building maintenance using digital twins, we analyzed twelve recent papers, highlighting benefits (such as energy efficiency, reduced costs), challenges (data quality, interoperability), and opportunities (integration with AI, IoT) in residential, commercial, and industrial buildings.

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References

  1. United Nations Environment Programme. 2022 global status report for buildings and construction: Towards a zero-emission, efficient and resilient buildings and construction sector (2022)

    Google Scholar 

  2. Fuller, A., Fan, Z., Day, C., Barlow, C.: Digital twin: enabling technologies, challenges and open research. IEEE Access 8, 108952–108971 (2020)

    Article  Google Scholar 

  3. Chen, Y.: Integrated and intelligent manufacturing: perspectives and enablers. Engineering 3(5), 588–595 (2017)

    Article  Google Scholar 

  4. Moher, D.: Preferred reporting items for systematic reviews and meta-analyses: the Prisma statement. Ann. Intern. Med. 151(4), 264 (2009)

    Article  Google Scholar 

  5. Shea, B.J.: AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ 358, j4008 (2017)

    Article  Google Scholar 

  6. Li, L., et al.: AMSTAR 2 appraisal of systematic reviews and meta-analyses in the field of heart failure from high-impact journals. System. Rev. 11(1), 147 (2022)

    Article  Google Scholar 

  7. Reeves, B.C., Shea, B.J.: AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised and/or non-randomised studies of healthcare interventions (2017)

    Google Scholar 

  8. Whiting, P., et al.: ROBIS: a new tool to assess risk of bias in systematic reviews was developed. J. Clin. Epidemiol. 69, 225–234 (2016)

    Google Scholar 

  9. Catone, M.C., Diana, P., Giordano, G.: Keywords co-occurrence analysis to map new topics and recent trends in social research methods. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds.) AINA 2020. AISC, vol. 1151, pp. 1078–1088. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-44041-1_93

    Chapter  Google Scholar 

  10. Radhakrishnan, S., Erbis, S., Isaacs, J.A., Kamarthi, S.: Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature. PLoS ONE 12(3), e0172778 (2017)

    Article  Google Scholar 

  11. Coupry, C., Noblecourt, S., Richard, P., Baudry, D., Bigaud, D.: BIM-based digital twin and XR devices to improve maintenance procedures in smart buildings: a literature review. Appl. Sci. 11(15), 6810 (2021)

    Article  Google Scholar 

  12. Hosamo, H.H., Imran, A., Cardenas-Cartagena, J., Svennevig, P.R., Svidt, K., Nielsen, H.K.: A review of the digital twin technology in the AEC-FM industry. Adv. Civil Eng. 2022, 1–17 (2022)

    Google Scholar 

  13. Kaewunruen, Sakdirat, Ningfang, Xu.: Digital twin for sustainability evaluation of railway station buildings. Front. Built Env. 4, 77 (2018)

    Article  Google Scholar 

  14. Zhao, J., Feng, H., Chen, Q., de Soto, B.G.: Developing a conceptual framework for the application of digital twin technologies to revamp building operation and maintenance processes. J. Build. Eng. 49, 104028 (2022)

    Article  Google Scholar 

  15. Peng, Y., Zhang, M., Fangqiang, Yu., Jinglin, X., Gao, S.: Digital twin hospital buildings: an exemplary case study through continuous lifecycle integration. Adv. Civil Eng. 2020, 1–13 (2020)

    Google Scholar 

  16. Drobnyi, V., Zhiqi, H., Fathy, Y., Brilakis, I.: Construction and maintenance of building geometric digital twins: state of the art review. Sensors 23(9), 4382 (2023)

    Article  Google Scholar 

  17. Errandonea, I., Beltrán, S., Arrizabalaga, S.: Digital twin for maintenance: a literature review. Comput. Ind. 123, 103316 (2020)

    Article  Google Scholar 

  18. Tahmasebinia, F., Lin, L., Shuo, W., Kang, Y., Sepasgozar, S.: Exploring the benefits and limitations of digital twin technology in building energy. Appl. Sci. 13(15), 8814 (2023)

    Article  Google Scholar 

  19. Bortolini, R., Rodrigues, R., Alavi, H., Vecchia, L.F.D., Forcada, N.: Digital twins’ applications for building energy efficiency: a review. Energies 15(19), 7002 (2022)

    Article  Google Scholar 

  20. Mylonas, G., Kalogeras, A., Kalogeras, G., Anagnostopoulos, C., Alexakos, C., Munoz, L.: Digital twins from smart manufacturing to smart cities: a survey. IEEE Access 9, 143222–143249 (2021)

    Article  Google Scholar 

  21. Agostinelli, S., Cumo, F., Guidi, G., Tomazzoli, C.: Cyber-physical systems improving building energy management: digital twin and artificial intelligence. Energies 14(8), 2338 (2021)

    Article  Google Scholar 

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Acknowledgements

The Romania Competitiveness Operational Programme partially supported this paper under project number SMIS 120725 - SCAMP-ML (Advanced computational statistics for planning and tracking production environments). The research conducted in this paper was partially supported by the UVT 1000 Develop Fund of the West University of Timișoara.

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Correspondence to Ionica-Larisa Puiu .

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Puiu, IL., Fortiș, TF. (2024). The Efficiency of Building Maintenance Using Digital Twins: A Literature Review. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 203. Springer, Cham. https://doi.org/10.1007/978-3-031-57931-8_20

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