Contained in:
Book Chapter

A Systematic Review of Digital Twin as a Predictive Maintenance Approach for Existing Buildings in the UK

  • Modupe Sobowale
  • Faris Elghaish
  • Tara Brooks

Digital Twin (DT) developments and applications in the Architectural Engineering Construction (AEC) Industry are emerging. However, insufficient publications synthesised the existing literature on DT of existing buildings, including energy retrofit and challenges as part of Net-zero strategies. When developing DT systems, it is vital to include the existing buildings primarily captured in 2-Dimensions (2-D) static data. To date, the implementation of DT has been minimal in applications in existing buildings in the UK. Despite DT benefits for maintenance (O&M) managers, facilities management (FM) as a comprehensive source of consistent data for predictive maintenance. This study explored the challenges faced by DT adoptions in existing buildings through a systematic review of the extant literature. A systematic approach is adopted to search the Scopus database using relevant keywords such as "Digital Twin.", "Built Environment" and "Existing Buildings.". the study focused on publications from the past five years (2018 to 2023) and prioritised articles in Scopus. The findings of this paper showed that the practitioners, O&M managers, and academics in built environments need more proper knowledge and technical expertise on digital twins as part of Industry 4.0 (I4.0). Evidence from the literature resulted in low empirical case studies and applications. The complexity of real-time data integration and interoperability were highlighted as part of the challenges despite the need for comprehensive knowledge of DT in the built environment. Scarce publication on the study was noted. The directions for comprehensive solutions and future research on digital twin applications in existing buildings towards achieving efficient energy retrofits, cost reductions, and net-zero goals were highlighted

  • Keywords:
  • Digital Twin,
  • BIM,
  • Data,
  • Buildings,
  • Energy,
  • Management,
+ Show More

Modupe Sobowale

Queen's University Belfast, United Kingdom

Faris Elghaish

Queen's University Belfast, United Kingdom - ORCID: 0000-0002-7558-6291

Tara Brooks

Queen's University Belfast, United Kingdom - ORCID: 0000-0003-3734-4416

  1. Agapaki, E., & Brilakis, I. (2021). Instance Segmentation of Industrial Point Cloud Data. Journal of Computing in Civil Engineering, 35(6). DOI: 10.1061/(ASCE)CP.1943-5487.0000972
  2. Agostinelli, S., Cumo, F., Guidi, G., & Tomazzoli, C. (2021). Cyber-physical systems improving building energy management: Digital twin and artificial intelligence. Energies, 14(8). DOI: 10.3390/en14082338
  3. Agrawal, A., Thiel, R., Jain, P., Singh, V., & Fischer, M. (2023). Digital Twin: Where do humans fit in? Automation in Construction, 148. DOI: 10.1016/j.autcon.2023.104749
  4. Al-Dhlan, K. A. (2021). The Current Merging Principles for Digital Twinning and Connecting Internet. IETE Journal of Research. DOI: 10.1080/03772063.2021.2010609
  5. Ali, K. N., Alhajlah, H. H., & Kassem, M. A. (2022). Collaboration and Risk in Building Information Modelling (BIM): A Systematic Literature Review. Buildings, 12(5). DOI: 10.3390/buildings12050571
  6. Aromataris, E., & Pearson, A. (2014). The Systematic Review: An Overview. AJN The American Journal of Nursing, 114(3), 53-58. DOI: 10.1097/01.NAJ.0000444496.24228.2c
  7. Arsiwala, A., Elghaish, F., & Zoher, M. (2023). Digital twin with Machine learning for predictive monitoring of CO2 equivalent from existing buildings. Energy and Buildings, 284. DOI: 10.1016/j.enbuild.2023.112851
  8. Badenko, V. L., Bolshakov, N. S., Tishchenko, E. B., Fedotov, A. A., Celani, A. C., & Yadykin, V. K. (2021). Integration of digital twin and BIM technologies within factories of the future. Magazine of Civil Engineering, 101(1). DOI: 10.34910/MCE.101.14
  9. Banfi, F., Brumana, R., Landi, A. G., Previtali, M., Roncoroni, F., & Stanga, C. (2022). BUILDING ARCHAEOLOGY INFORMATIVE MODELLING TURNED INTO 3D VOLUME STRATIGRAPHY AND EXTENDED REALITY TIME-LAPSE COMMUNICATION. Virtual Archaeology Review, 13(26), 1-21. DOI: 10.4995/VAR.2022.15313
  10. Banfi, F., Brumana, R., Salvalai, G., & Previtali, M. (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, 15(12). DOI: 10.3390/en15124497
  11. Borja-Conde, J. A., Witheephanich, K., Coronel, J. F., & Limon, D. (2023). Thermal modeling of existing buildings in high-fidelity simulators: A novel, practical methodology. Energy and Buildings, 292. DOI: 10.1016/j.enbuild.2023.113127
  12. Camposano, J. C., Smolander, K., & Ruippo, T. (2021). Seven Metaphors to Understand Digital Twins of Built Assets. IEEE Access, 9, 27167-27181. DOI: 10.1109/ACCESS.2021.3058009
  13. Cardinali, V., Ciuffreda, A. L., Coli, M., De Stefano, M., Meli, F., Tanganelli, M., & Trovatelli, F. (2023). An Oriented H-BIM Approach for the Seismic Assessment of Cultural Heritage Buildings: Palazzo Vecchio in Florence. Buildings, 13(4). DOI: 10.3390/buildings13040913
  14. Çetin, S., Gruis, V., & Straub, A. (2022). Digitalization for a circular economy in the building industry: Multiple-case study of Dutch social housing organizations. Resources, Conservation and Recycling Advances, 15. DOI: 10.1016/j.rcradv.2022.200110
  15. Chacón, R., Casas, J. R., Ramonell, C., Posada, H., Stipanovic, I., & Škarić, S. (2023). Requirements and challenges for infusion of SHM systems within Digital Twin platforms. Structure and Infrastructure Engineering. DOI: 10.1080/15732479.2023.2225486
  16. Chen, L., Xie, X., Lu, Q., Parlikad, A. K., Pitt, M., & Yang, J. (2021). Gemini principles-based digital twin maturity model for asset management. Sustainability (Switzerland), 13(15). DOI: 10.3390/su13158224
  17. Corrado, C. R., DeLong, S. M., Holt, E. G., Hua, E. Y., & Tolk, A. (2022). Combining Green Metrics and Digital Twins for Sustainability Planning and Governance of Smart Buildings and Cities. Sustainability (Switzerland), 14(20). DOI: 10.3390/su142012988
  18. Costa, G., Arroyo, O., Rueda, P., & Briones, A. (2023). A ventilation early warning system (VEWS) for diaphanous workspaces considering COVID-19 and future pandemics scenarios. Heliyon, 9(3). DOI: 10.1016/j.heliyon.2023.e14640
  19. Daniotti, B., Masera, G., Bolognesi, C. M., Spagnolo, S. L., Pavan, A., Iannaccone, G., . . . Cucuzza, M. (2022). The Development of a BIM-Based Interoperable Toolkit for Efficient Renovation in Buildings: From BIM to Digital Twin. Buildings, 12(2). DOI: 10.3390/buildings12020231
  20. Delgado, J. M. P. Q., Guimarães, A. S., Poças Martins, J., Parracho, D. F. R., Freitas, S. S., Lima, A. G. B., & Rodrigues, L. (2023). BIM and BEM Interoperability–Evaluation of a Case Study in Modular Wooden Housing. Energies, 16(4). DOI: 10.3390/en16041579
  21. Deng, M., Menassa, C. C., & Kamat, V. R. (2021). From BIM to digital twins: A systematic review of the evolution of intelligent building representations in the AEC-FM industry. Journal of Information Technology in Construction, 26, 58-83. DOI: 10.36680/J.ITCON.2021.005
  22. Eneyew, D. D., Capretz, M. A. M., & Bitsuamlak, G. T. (2022). Toward Smart-Building Digital Twins: BIM and IoT Data Integration. IEEE Access, 10, 130487-130506. DOI: 10.1109/ACCESS.2022.3229370
  23. Fialho, B. C., Codinhoto, R., Fabricio, M. M., Estrella, J. C., Neves Ribeiro, C. M., Dos Santos Bueno, J. M., & Doimo Torrezan, J. P. (2022). Development of a BIM and IoT-Based Smart Lighting Maintenance System Prototype for Universities’ FM Sector. Buildings, 12(2). DOI: 10.3390/buildings12020099
  24. Francisco, A., Mohammadi, N., & Taylor, J. E. (2020). Smart City Digital Twin-Enabled Energy Management: Toward Real-Time Urban Building Energy Benchmarking. Journal of Management in Engineering, 36(2). DOI: 10.1061/(ASCE)ME.1943-5479.0000741
  25. Godager, B., Onstein, E., & Huang, L. (2021). The Concept of Enterprise BIM: Current Research Practice and Future Trends. IEEE Access, 9, 42265-42290. DOI: 10.1109/ACCESS.2021.3065116
  26. Harode, A., Thabet, W., Jamerson, W. E., & Dongre, P. (2023). A TOOL-BASED SYSTEM ARCHITECTURE FOR A DIGITAL TWIN: A CASE STUDY IN A HEALTHCARE FACILITY. Journal of Information Technology in Construction, 28, 107-137. DOI: 10.36680/J.ITCON.2023.006
  27. Hassani, H., Huang, X., & MacFeely, S. (2022). Enabling Digital Twins to Support the UN SDGs. Big Data and Cognitive Computing, 6(4). DOI: 10.3390/bdcc6040115
  28. Hosamo, H., Hosamo, M. H., Nielsen, H. K., Svennevig, P. R., & Svidt, K. (2023). Digital Twin of HVAC system (HVACDT) for multiobjective optimization of energy consumption and thermal comfort based on BIM framework with ANN-MOGA. Advances in building energy research, 17(2), 125-171. DOI: 10.1080/17512549.2022.2136240
  29. Hosamo, H. H., Nielsen, H. K., Kraniotis, D., Svennevig, P. R., & Svidt, K. (2023a). Digital Twin framework for automated fault source detection and prediction for comfort performance evaluation of existing non-residential Norwegian buildings. Energy and Buildings, 281. DOI: 10.1016/j.enbuild.2022.112732
  30. Hosamo, H. H., Nielsen, H. K., Kraniotis, D., Svennevig, P. R., & Svidt, K. (2023b). Improving building occupant comfort through a digital twin approach: A Bayesian network model and predictive maintenance method. Energy and Buildings, 288. DOI: 10.1016/j.enbuild.2023.112992
  31. Hosseinihaghighi, S., Panchabikesan, K., Dabirian, S., Webster, J., Ouf, M., & Eicker, U. (2022). Discovering, processing and consolidating housing stock and smart thermostat data in support of energy end-use mapping and housing retrofit program planning. Sustainable Cities and Society, 78. DOI: 10.1016/j.scs.2021.103640
  32. Jiang, F., Ma, L., Broyd, T., Chen, W., & Luo, H. (2022). Building digital twins of existing highways using map data based on engineering expertise. Automation in Construction, 134. DOI: 10.1016/j.autcon.2021.104081
  33. Jiao, Z., Du, X., Liu, Z., Liu, L., Sun, Z., & Shi, G. (2023). Sustainable Operation and Maintenance Modeling and Application of Building Infrastructures Combined with Digital Twin Framework. Sensors, 23(9). DOI: 10.3390/s23094182
  34. Jowett, B., Edwards, D. J., & Kassem, M. (2023). Field BIM and mobile BIM technologies: a requirements taxonomy and its interactions with construction management functions. Construction Innovation. DOI: 10.1108/CI-07-2022-0160
  35. Kaewunruen, S., & Lian, Q. (2019). Digital twin aided sustainability-based lifecycle management for railway turnout systems. Journal of Cleaner Production, 228, 1537-1551. DOI: 10.1016/j.jclepro.2019.04.156
  36. Kaewunruen, S., Peng, S., & Phil-Ebosie, O. (2020). Digital twin aided sustainability and vulnerability audit for subway stations. Sustainability (Switzerland), 12(19). DOI: 10.3390/SU12197873
  37. Kaewunruen, S., Rungskunroch, P., & Welsh, J. (2019). A digital-twin evaluation of Net Zero Energy Building for existing buildings. Sustainability (Switzerland), 11(1). DOI: 10.3390/su11010159
  38. Kaewunruen, S., Sresakoolchai, J., & Kerinnonta, L. (2019). Potential reconstruction design of an existing townhouse in Washington DC for approaching net zero energy building goal. Sustainability (Switzerland), 11(23). DOI: 10.3390/su11236631
  39. Kaewunruen, S., Sresakoolchai, J., Ma, W., & Phil-Ebosie, O. (2021). Digital twin aided vulnerability assessment and risk-based maintenance planning of bridge infrastructures exposed to extreme conditions. Sustainability (Switzerland), 13(4), 1-19. DOI: 10.3390/su13042051
  40. Kaewunruen, S., & Xu, N. (2018). Digital twin for sustainability evaluation of railway station buildings. Frontiers in Built Environment, 4. DOI: 10.3389/fbuil.2018.00077
  41. Khajavi, S. H., Tetik, M., Liu, Z., Korhonen, P., & Holmstrom, J. (2023). Digital Twin for Safety and Security: Perspectives on Building Lifecycle. IEEE Access, 11, 52339-52356. DOI: 10.1109/ACCESS.2023.3278267
  42. Khalil, A., Stravoravdis, S., & Backes, D. (2021). Categorisation of building data in the digital documentation of heritage buildings. Applied Geomatics, 13(1), 29-54. DOI: 10.1007/s12518-020-00322-7
  43. Khallaf, R., Khallaf, L., Anumba, C. J., & Madubuike, O. C. (2022). Review of Digital Twins for Constructed Facilities. Buildings, 12(11). DOI: 10.3390/buildings12112029
  44. Kitchenham, B., Pretorius, R., Budgen, D., Pearl Brereton, O., Turner, M., Niazi, M., & Linkman, S. (2010). Systematic literature reviews in software engineering – A tertiary study. Information and Software Technology, 52(8), 792-805. DOI: 10.1016/j.infsof.2010.03.006
  45. Lamagna, M., Groppi, D., Nezhad, M. M., & Piras, G. (2021). A COMPREHENSIVE REVIEW on DIGITAL TWINS for SMART ENERGY MANAGEMENT SYSTEM. International Journal of Energy Production and Management, 6(4), 323-334. DOI: 10.2495/EQ-V6-N4-323-334
  46. Levine, N. M., & Spencer, B. F., Jr. (2022). Post-Earthquake Building Evaluation Using UAVs: A BIM-Based Digital Twin Framework. Sensors, 22(3). DOI: 10.3390/s22030873
  47. Liu, M., Fang, S., Dong, H., & Xu, C. (2021). Review of digital twin about concepts, technologies, and industrial applications. Journal of Manufacturing Systems, 58, 346-361. DOI: 10.1016/j.jmsy.2020.06.017
  48. Liu, Z., Yuan, C., Sun, Z., & Cao, C. (2022). Digital Twins-Based Impact Response Prediction of Prestressed Steel Structure. Sensors, 22(4). DOI: 10.3390/s22041647
  49. Longman, R. P., Xu, Y., Sun, Q., Turkan, Y., & Riggio, M. (2023). Digital Twin for Monitoring In-Service Performance of Post-Tensioned Self-Centering Cross-Laminated Timber Shear Walls. Journal of Computing in Civil Engineering, 37(2). DOI: 10.1061/(ASCE)CP.1943-5487.0001050
  50. Lu, Q., Xie, X., Parlikad, A. K., & Schooling, J. M. (2020). Digital twin-enabled anomaly detection for built asset monitoring in operation and maintenance. Automation in Construction, 118. DOI: 10.1016/j.autcon.2020.103277
  51. Lu, Q., Xie, X., Parlikad, A. K., Schooling, J. M., & Konstantinou, E. (2020). Moving from building information models to digital twins for operation and maintenance. Proceedings of the Institution of Civil Engineers: Smart Infrastructure and Construction, 174(2), 46-56. DOI: 10.1680/jsmic.19.00011
  52. Masoumi, H., Shirowzhan, S., Eskandarpour, P., & Pettit, C. J. (2023). City Digital Twins: their maturity level and differentiation from 3D city models. Big Earth Data, 7(1), 1-46. DOI: 10.1080/20964471.2022.2160156
  53. Mastan, I. A., Sensuse, D. I., Suryono, R. R., & Kautsarina, K. (2022). Evaluation of distance learning system (e-learning): a systematic literature review. Jurnal Teknoinfo, 16(1), 132-137. DOI: 10.33365/jti.v16i1.1736
  54. Moretti, N., Ellul, C., Re Cecconi, F., Papapesios, N., & Dejaco, M. C. (2021). GeoBIM for built environment condition assessment supporting asset management decision making. Automation in Construction, 130. DOI: 10.1016/j.autcon.2021.103859
  55. Moyano, J., Carreño, E., Nieto-Julián, J. E., Gil-Arizón, I., & Bruno, S. (2022). Systematic approach to generate Historical Building Information Modelling (HBIM) in architectural restoration project. Automation in Construction, 143. DOI: 10.1016/j.autcon.2022.104551
  56. Noronha Pinto de Oliveira e Sousa, M., & Correa, F. R. (2023). Towards digital twins for heritage buildings: A workflow proposal. International Journal of Architectural Computing. DOI: 10.1177/14780771231168226
  57. Nour El-Din, M., Pereira, P. F., Poças Martins, J., & Ramos, N. M. M. (2022). Digital Twins for Construction Assets Using BIM Standard Specifications. Buildings, 12(12). DOI: 10.3390/buildings12122155
  58. Ochs, F., Franzoi, N., Dermentzis, G., Monteleone, W., & Magni, M. (2023). Monitoring and simulation-based optimization of two multi-apartment NZEBs with heat pump, solar thermal and PV. Journal of Building Performance Simulation. DOI: 10.1080/19401493.2023.2227605
  59. Pan, Y., Braun, A., Borrmann, A., & Brilakis, I. (2022). 3D deep-learning-enhanced void-growing approach in creating geometric digital twins of buildings. Proceedings of the Institution of Civil Engineers: Smart Infrastructure and Construction, 176(1), 24-40. DOI: 10.1680/jsmic.21.00035
  60. Pan, Y., Braun, A., Brilakis, I., & Borrmann, A. (2022). Enriching geometric digital twins of buildings with small objects by fusing laser scanning and AI-based image recognition. Automation in Construction, 140. DOI: 10.1016/j.autcon.2022.104375
  61. Pauwels, P., de Koning, R., Hendrikx, B., & Torta, E. (2023). Live semantic data from building digital twins for robot navigation: Overview of data transfer methods. Advanced Engineering Informatics, 56. DOI: 10.1016/j.aei.2023.101959
  62. Porsani, G. B., de Lersundi, K. D. V., Gutiérrez, A. S. O., & Bandera, C. F. (2021). Interoperability between building information modelling (Bim) and building energy model (bem). Applied Sciences (Switzerland), 11(5), 1-20. DOI: 10.3390/app11052167
  63. Pour Rahimian, F., Dawood, N., Ghaffarianhoseini, A., & Ghaffarianhoseini, A. (2022). Guest editorial: Enabling the development and implementation of digital twins. Construction Innovation, 22(3), 405-411. DOI: 10.1108/CI-07-2022-247
  64. Pregnolato, M., Gunner, S., Voyagaki, E., De Risi, R., Carhart, N., Gavriel, G., . . . Taylor, C. (2022). Towards Civil Engineering 4.0: Concept, workflow and application of Digital Twins for existing infrastructure. Automation in Construction, 141. DOI: 10.1016/j.autcon.2022.104421
  65. Rafsanjani, H. N., & Nabizadeh, A. H. (2023). Towards digital architecture, engineering, and construction (AEC) industry through virtual design and construction (VDC) and digital twin. Energy and Built Environment, 4(2), 169-178. DOI: 10.1016/j.enbenv.2021.10.004
  66. Rampini, L., & Re Cecconi, F. (2022). ARTIFICIAL INTELLIGENCE IN CONSTRUCTION ASSET MANAGEMENT: A REVIEW OF PRESENT STATUS, CHALLENGES AND FUTURE OPPORTUNITIES. Journal of Information Technology in Construction, 27, 884-913. DOI: 10.36680/j.itcon.2022.043
  67. Sacks, R., Brilakis, I., Pikas, E., Xie, H. S., & Girolami, M. (2020). Construction with digital twin information systems. Data-Centric Engineering, 1, e14. DOI: 10.1017/dce.2020.16
  68. Sagarna, M., Otaduy, J. P., Mora, F., & Leon, I. (2022). Analysis of the State of Building Conservation through Study of Damage and Its Evolution with the State of Conservation Assessment BIM Model (SCABIM). Applied Sciences (Switzerland), 12(14). DOI: 10.3390/app12147259
  69. Sepasgozar, S. M. E., Khan, A. A., Smith, K., Romero, J. G., Shen, X., Shirowzhan, S., . . . Tahmasebinia, F. (2023). BIM and Digital Twin for Developing Convergence Technologies as Future of Digital Construction. Buildings, 13(2). DOI: 10.3390/buildings13020441
  70. Shahinmoghadam, M., Natephra, W., & Motamedi, A. (2021). BIM- and IoT-based virtual reality tool for real-time thermal comfort assessment in building enclosures. Building and Environment, 199. DOI: 10.1016/j.buildenv.2021.107905
  71. Shen, K., Ding, L., & Wang, C. C. (2022). Development of a Framework to Support Whole-Life-Cycle Net-Zero-Carbon Buildings through Integration of Building Information Modelling and Digital Twins. Buildings, 12(10). DOI: 10.3390/buildings12101747
  72. Spudys, P., Afxentiou, N., Georgali, P. Z., Klumbyte, E., Jurelionis, A., & Fokaides, P. (2023). Classifying the operational energy performance of buildings with the use of digital twins. Energy and Buildings, 290. DOI: 10.1016/j.enbuild.2023.113106
  73. Tagliabue, L. C., Cecconi, F. R., Maltese, S., Rinaldi, S., Ciribini, A. L. C., & Flammini, A. (2021). Leveraging digital twin for sustainability assessment of an educational building. Sustainability (Switzerland), 13(2), 1-16. DOI: 10.3390/su13020480
  74. Tan, J., Leng, J., Zeng, X., Feng, D., & Yu, P. (2022). Digital Twin for Xiegong’s Architectural Archaeological Research: A Case Study of Xuanluo Hall, Sichuan, China. Buildings, 12(7). DOI: 10.3390/buildings12071053
  75. Tang, Y., Gao, F., Wang, C., Huang, M. M., Wu, M., Li, H., & Li, Z. (2023). Vertical Greenery System (VGS) Renovation for Sustainable Arcade-Housing: Building Energy Efficiency Analysis Based on Digital Twin. Sustainability, 15(3), 2310. DOI: 10.3390/su15032310
  76. Xie, X., Lu, Q., Rodenas-Herraiz, D., Parlikad, A. K., & Schooling, J. M. (2020). Visualised inspection system for monitoring environmental anomalies during daily operation and maintenance. Engineering, Construction and Architectural Management, 27(8), 1835-1852. DOI: 10.1108/ECAM-11-2019-0640
  77. Xu, F., Xia, P., You, H., & Du, J. (2022). Robotic Cross-Platform Sensor Fusion and Augmented Visualization for Large Indoor Space Reality Capture. Journal of Computing in Civil Engineering, 36(6). DOI: 10.1061/(ASCE)CP.1943-5487.0001047
  78. Zhao, L., Zhang, H., Wang, Q., Sun, B., Liu, W., Qu, K., & Shen, X. (2022). Digital Twin Evaluation of Environment and Health of Public Toilet Ventilation Design Based on Building Information Modeling. Buildings, 12(4). doi:10.3390/buildings12040470 DOI: 10.3390/buildings12040470
  79. Zhou, J., Zhang, S., & Gu, M. (2022). Revisiting digital twins: Origins, fundamentals, and practices. Frontiers of Engineering Management, 9(4), 668-676. doi:10.1007/s42524-022-0216-2 DOI: 10.1007/s42524-022-0216-2
PDF
  • Publication Year: 2023
  • Pages: 1206-1218

XML
  • Publication Year: 2023

Chapter Information

Chapter Title

A Systematic Review of Digital Twin as a Predictive Maintenance Approach for Existing Buildings in the UK

Authors

Modupe Sobowale, Faris Elghaish, Tara Brooks

DOI

10.36253/979-12-215-0289-3.119

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality

Book Subtitle

Managing the Digital Transformation of Construction Industry

Editors

Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/979-12-215-0289-3

eISBN (pdf)

979-12-215-0289-3

eISBN (xml)

979-12-215-0257-2

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

115

Fulltext
downloads

167

Views

Export Citation

1,331

Open Access Books

in the Catalogue

2,094

Book Chapters

3,709,757

Fulltext
downloads

4,300

Authors

from 904 Research Institutions

of 65 Nations

65

scientific boards

from 347 Research Institutions

of 43 Nations

1,246

Referees

from 379 Research Institutions

of 38 Nations