From blueprint to reality: how digital twins are shaping the architecture, engineering, and construction landscape

Year 2025, Volume: 5 Issue: 1, 399 - 435, 31.01.2025

Aslıhan Şenel Solmaz

https://doi.org/10.61112/jiens.1572660

Abstract

Digital Twin (DT) technologies are reshaping the Architecture, Engineering, and Construction (AEC) industry by bridging physical and digital domains to enable real-time data integration, advanced simulations, and predictive analytics. This study systematically investigates the role of DT technologies in addressing persistent industry challenges such as inefficiencies, cost overruns, and sustainability goals. Through a detailed literature review of 95 publications spanning 2019 to 2024, the research identifies key contributions, barriers, and gaps in DT applications across lifecycle phases and scales, ranging from individual buildings to urban infrastructure. The findings emphasize DT's transformative potential in enhancing operational efficiency, predictive maintenance, energy optimization, and sustainability. A comprehensive framework is proposed to guide the integration of DTs, addressing technical, economic, and knowledge-based challenges while highlighting opportunities to leverage complementary technologies such as IoT, BIM, AI, and blockchain. The study concludes with actionable recommendations for advancing DT adoption in the AEC industry, paving the way for smarter, more sustainable built environments.

Keywords

Keywords: Digital Twin (DT), Building Information Modelling (BIM), Energy Optimization, Architecture-Engineering-Construction (AEC)

Planlamadan gerçeğe: dijital ikizler, mimarlık, mühendislik ve inşaat sektörünü nasıl şekillendiriyor

Abstract

Mimarlık, Mühendislik ve İnşaat (MMİ) sektörü maliyet, proje yönetimi, sürdürülebilirlik ve veri yönetimi ile ilgili zorluklarla karşı karşıyadır. Yapı Bilgi Modellemesi (YBM) gibi teknolojiler iş akışlarını iyileştirirken, gerçek zamanlı veri entegrasyonu konusunda sıkıntılar yaşamaktadır. Binaların gelişen sanal modellerini oluşturan Dijital İkiz teknolojileri, bir binanın yaşam döngüsü boyunca karar verme sürecini geliştirerek potansiyel çözümler sunmaktadır. Bu potansiyeline rağmen Dijital İkizler, sistemlerin birlikte işlerliği ve veri yönetimine ilişkin eksikliklerle birlikte henüz erken kullanım aşamasındadır. Bu araştırma, Dijital İkizlerin öngörülebilir bakımı iyileştirmek, bina operasyonlarını optimize etmek ve proje teslimini kolaylaştırmak için MMİ endüstrisine nasıl entegre edilebileceğini araştırmaktadır. Çalışma, dijital ikizlerin verimlilik, maliyet ve sürdürülebilirlik üzerindeki etkilerini değerlendirmeyi ve inşaatta daha geniş çapta benimsenmesi için bir çerçeve sağlamayı amaçlamaktadır.

Keywords

Dijital İkiz, Yapı Bilgi Modelleme (YBM), Enerji Optimizasyonu, Mimarlık, Mühendislik ve İnşaat (MMİ), Akıllı Bina Sistemleri

References

• Opoku DGJ, Perera S, Osei-Kyei R, Rashidi M (2021) Digital twin application in the construction industry: A literature review. J Build Eng 40:102726. https://doi.org/10.1016/j.jobe.2021.102726
• Su S, Zhong RY, Jiang Y, Song J, Fu Y, Cao H (2023) Digital twin and its potential applications in construction industry: State-of-art review and a conceptual framework. Adv Eng Inform 57:102030. https://doi.org/10.1016/j.aei.2023.102030
• Piras G, Agostinelli S, Muzi F (2024) Digital twin framework for built environment: A review of key enablers. Energies 17:436. https://doi.org/10.3390/en17020436
• Bortolini R, Rodrigues R, Alavi H, Vecchia LFD, Forcada N (2022) Digital twins’ applications for building energy efficiency: A review. Energies 15:7002. https://doi.org/10.3390/en15197002
• Grieves M (2016) Origins of the digital twin concept. https://www.researchgate.net/publication/307509727_Origins_of_the_Digital_Twin_Concept. Accessed 13 March 2003
• Glaessgen EH, Stargel D (2012) The digital twin paradigm for future NASA and U.S. air force vehicles. 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference: Special Session on the Digital Twin, Honolulu, Hawaii, US, Apr 23–26.
• Tao F, Qi Q, Wang L, Nee AYC (2019) Digital twins and cyber-physical systems toward smart manufacturing and industry 4.0: Correlation and comparison. Eng 5:653–661. https://doi.org/10.1016/j.eng.2019.01.014
• Singh M, Srivastava R, Fuenmayor E, Kuts V, Qiao Y, Murray N, Devine D (2022) Applications of digital twin across industries: A review. Appl Sci 12:5727. https://doi.org/10.3390/app12115727
• Enders MR, Hoßbach N (2019) Dimensions of digital twin applications - A literature review. In: Proceedings of the Americas Conference on Information Systems, Cancun, Mexico, Aug 15–17.
• Lehtola VV, Koeva M, Elberink SO, Raposo P, Virtanen JP, Vahdatikhaki F, Borsci S (2022) Digital twin of a city: Review of technology serving city needs. Int J Appl Earth Obs Geoinf 114:102915. https://doi.org/10.1016/j.jag.2022.102915
• Madubuike OC, Anumba CJ, Khallaf R (2022) A review of digital twin applications in construction. IT Con 27:145–172. https://doi.org/10.36680/j.itcon.2022.008
• Zhang A, Yang J, Wang F (2023) Application and enabling technologies of digital twin in operation and maintenance stage of the AEC industry: A literature review. J Build Eng 107859. https://doi.org/10.1016/j.jobe.2023.107859
• Singh M, Fuenmayor E, Hinchy EP, Qiao Y, Murray N, Devine D (2021) Digital twin: Origin to future. Appl Syst Innov 4:36. https://doi.org/10.3390/asi4020036
• Tao F, Zhang H, Liu A, Nee AYC (2019) Digital twin in industry: State-of-the-art. IEEE Trans Ind Inform 15:2405–2415. https://doi.org/10.1109/TII.2018.2873186
• Lauria M, Azzalin M (2024) Digital transformation in the construction sector: A digital twin for seismic safety in the lifecycle of buildings. Sustainability 16:8245. https://doi.org/10.3390/su16188245
• Boje C, Guerriero A, Kubicki S, Rezgui Y (2020) Towards a semantic construction digital twin: Directions for future research. Autom Constr 114:103179. https://doi.org/10.1016/j.autcon.2020.103179
• Wang W, Zaheer Q, Qiu S, Wang W, Ai C, Wang J, Wang S, Hu W (2024) Digital twins in design and construction. In: Digital twin technologies in transportation infrastructure management. Springer Nature Singapore, pp 147–178. https://doi.org/10.1007/978-981-99-5804-7_5
• Khajavi SH, Motlagh NH, Jaribion A, Werner LC, Holmström J (2019) Digital Twin: Vision, benefits, boundaries, and creation for buildings. IEEE Access 7:147406–147419. https://doi.org/10.1109/ACCESS.2019.2946515
• Liu M, Fang S, Dong H, Xu C (2021) Review of digital twin about concepts, technologies, and industrial applications. J Manuf Syst 58:346–361. https://doi.org/10.1016/j.jmsy.2020.06.017
• Anderl R, Haag S, Schützer K, Zancul E (2018) Digital twin technology – An approach for Industrie 4.0 vertical and horizontal lifecycle integration. IT 60:125–132. https://doi.org/10.1515/itit-2017-0038
• Schlenger J, Yeung T, Vilgertshofer S, Martinez J, Sacks R, Borrmann A (2022) Comprehensive data schema for digital twin construction. 29th International Workshop on Intelligent Computing in Engineering (EG-ICE), Aarhus, Denmark. https://doi.org/10.7146/aul.455.c194
• Lin YC (2020) Developing WSN/BIM-based environmental monitoring management system for parking garages in smart cities. Eng Manag J 36:04020012. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000760
• Radzi AR, Azmi NF, Kamaruzzaman SN, Rahman RA, Papadonikolaki E (2024) Relationship between digital twin and building information modeling: A systematic review and future directions. Constr Innov 24:811–824. https://doi.org/10.1108/CI-07-2022-0183
• Autodesk, Autodesk Revit. https://www.autodesk.com/products/revit/architecture, Accessed 15 September 2024
• Graphisoft, ArchiCAD. https://graphisoft.com/solutions/archicad/, Accessed 15 September 2024
• Autodesk, Autodesk Insight. https://www.autodesk.com/products/insight/overview Accessed 15 September 2024
• ESRI, ArcGIS. https://www.esri.com/en-us, Accessed 15 September 2024
• QGIS. https://qgis.org/, Accessed 15 September 2024
• Mapbox. https://www.mapbox.com/, Accessed 15 September 2024
• Siemens (2018) MindSphere The cloud-based, open IoT operating system. https://assets.new.siemens.com/siemens/assets/api/uuid:0005a2a6-14f8-41b6-918d78eabb14211b/mindsphere-brochure.pdf, Accessed 15 September 2024
• IBM, Watson IoT Platform. https://internetofthings.ibmcloud.com/, Accessed 13 March 2024
• Enscape GmbH, Enscape. https://enscape3d.com/, Accessed 13 October 2024
• Unity Reflect, Unity Cloud. https://unity.com/, Accessed 15 September 2024
• Microsoft, Microsoft HoloLens. https://learn.microsoft.com/tr-tr/hololens/, Accessed 13 October 2024
• TensorFlow. https://www.tensorflow.org/, Accessed 15 September 2024
• PyTorch Foundation, PyTorch. https://pytorch.org/, Accessed 15 September 2024
• Bentley, Synchro. https://www.bentley.com/software/synchro/, Accessed 15 September 2024
• Autodesk, Autodesk Navisworks. https://www.autodesk.com/products/navisworks/3d-viewers, Accessed 15 September 2024
• Oracle, Oracle Aconex. https://www.oracle.com/uk/construction-engineering/aconex/, Accessed 13 October 2024
• Procore. https://www.procore.com/en-gb, Accessed 13 October 2024
• Trimble Connect. https://developer.tekla.com/trimble-connect, Accessed 13 October 2024
• Verizon, Verizon 5G Network. https://www.verizon.com/5g/, Accessed 13 October 2024
• NVIDIA, NVIDIA EGX Platform. https://www.nvidia.com/en-us/data-center/products/egx/, Accessed 15 September 2024
• Microsoft, Azure. https://azure.microsoft.com, Accessed 15 September 2024
• Amazon, AWS. https://aws.amazon.com/, Accessed 15 September 2024
• Google, Google Cloud Platform. https://cloud.google.com/, Accessed 15 September 2024
• Google, Looker Studio (formerly Google Data Studio). https://lookerstudio.google.com/u/0/navigation/reporting, Accessed 15 September 2024
• Autodesk, Autodesk CFD. https://www.autodesk.com/products/cfd/overview?term=1-YEAR&tab=subscription, Accessed 15 September 2024
• U.S. Department of Energy, EnergyPlus. https://energyplus.net/, Accessed 15 September 2024
• Matterport Inc., Matterport. https://matterport.com/, Accessed 15 September 2024
• Ansys, Inc., Ansys. https://www.ansys.com/, Accessed 15 September 2024
• Lehner H, Dorffner L (2020) Digital geoTwin Vienna: Towards a Digital Twin City as Geodata Hub. PFG 88:63–75. https://doi.org/10.1007/s41064-020-00101-4
• Camposano JC, Smolander K, Ruippo T (2021) Seven metaphors to understand digital twins of built assets. IEEE Access 9:27167–27181. https://doi.org/10.1109/ACCESS.2021.3058009
• Coupry C, Noblecourt S, Richard P, Baudry D, Bigaud D (2021) BIM-based digital twin and XR devices to improve maintenance procedures in smart buildings: A literature review. Appl Sci 11:6810. https://doi.org/10.3390/app11156810
• Kaewunruen S, Rungskunroch P, Welsh J (2019) A digital-twin evaluation of net zero energy building for existing buildings. Sustainability 11:159. https://doi.org/10.3390/su11010159
• Teisserenc B, Sepasgozar S (2021) Adoption of blockchain technology through digital twins in the construction industry 4.0: A PESTELS approach. Buildings 11:670. https://doi.org/10.3390/buildings11120670
• Davila Delgado JM, Oyedele L (2021) Digital twins for the built environment: Learning from conceptual and process models in manufacturing. Adv Eng Inform 49:101332. https://doi.org/10.1016/j.aei.2021.101332
• Deng M, Menassa CC, Kamat VR (2021) From BIM to digital twins: A systematic review of the evolution of intelligent building representations in the AEC-FM industry. J Inf Technol Constr 26. https://doi.org/10.36680/j.itcon.2021.005
• Rathore MM, Shah SA, Shukla D, Bentafat E, Bakiras S (2021) The role of AI, machine learning, and big data in digital twinning: A systematic literature review, challenges, and opportunities. IEEE Access 9:32030–32052. https://doi.org/10.1109/ACCESS.2021.3060863
• Wang W, Guo H, Li X, Tang S, Li Y, Xie L, Lv Z (2022) BIM information integration-based VR modeling in digital twins in Industry 5.0. J Ind Inf Integr 28:100351. https://doi.org/10.1016/j.jii.2022.100351
• Pregnolato M, Gunner S, Voyagaki E, De Risi R, Carhart N, Gavriel G, Tully P, Tryfonas T, Macdonald J, Taylor C (2022) Towards Civil Engineering 4.0: Concept, workflow and application of Digital Twins for existing infrastructure. Autom Constr 141:104421. https://doi.org/10.1016/j.autcon.2022.104421
• Lv Z, Chen D, Lv H (2022) Smart city construction and management by digital twins and BIM big data in COVID-19 scenario. ACM Trans Multimed Comput Commun Appl 18(2s):1–21
• Lei B, Janssen P, Stoter J, Biljecki F (2023) Challenges of urban digital twins: A systematic review and a Delphi expert survey. Autom Constr 147:104716. https://doi.org/10.1016/j.autcon.2022.104716
• Weil C, Bibri SE, Longchamp R, Golay F, Alahi A (2023) Urban digital twin challenges: A systematic review and perspectives for sustainable smart cities. Sustain Cities Soc 99:104862. https://doi.org/10.1016/j.scs.2023.104862
• Tuhaise VV, Tah JHM, Abanda FH (2023) Technologies for digital twin applications in construction. Autom Constr 152:104931. https://doi.org/10.1016/j.autcon.2023.104931
• Megahed NA, Hassan AM (2022) Evolution of BIM to DTs: A paradigm shift for the post-pandemic AECO industry. Urban Sci 6:67. https://doi.org/10.3390/urbansci6040067
• Afzal M, Li RYM, Shoaib M, Ayyub MF, Tagliabue LC, Bilal M, Ghafoor H, Manta O (2023) Delving into the digital twin developments and applications in the construction industry: A PRISMA approach. Sustainability 15:16436. https://doi.org/10.3390/su152316436
• Lauria M, Azzalin M (2024) Digital twin approach in buildings: Future challenges via a critical literature review. Buildings 14:376. https://doi.org/10.3390/buildings14020376
• Revolti A, Gualtieri L, Pauwels P, Dallasega P (2024) From building information modeling to construction digital twin: A conceptual framework. Prod Manuf Res 12:2387679. https://doi.org/10.1080/21693277.2024.2387679
• García-Aranda C, Martínez-Cuevas S, Torres Y, Pedrote Sanz M (2024) A digital twin of a university campus from an urban sustainability approach: Case study in Madrid (Spain). Urban Sci 8:167. https://doi.org/10.3390/urbansci8040167
• Lam P-D, Gu B-H, Lam H-K, Ok S-Y, Lee S-H (2024) Digital twin smart city: Integrating IFC and CityGML with semantic graph for advanced 3D city model visualization. Sensors 24:3761. https://doi.org/10.3390/s24123761
• Arsecularatne B, Rodrigo N, Chang R (2024) Digital twins for reducing energy consumption in buildings: A review. Sustainability 16:9275. https://doi.org/10.3390/su16219275
• Arowoiya VA, Moehler RC, Fang Y (2024) Digital twin technology for thermal comfort and energy efficiency in buildings: A state-of-the-art and future directions. Energy Built Environ 5:641–656
• Li C, Lu P, Zhu W, Zhu H, Zhang X (2023) Intelligent monitoring platform and application for building energy using information based on digital twin. Energies 16:6839. https://doi.org/10.3390/en16196839
• Desogus G, Frau C, Quaquero E, Rubiu G (2023) From building information model to digital twin: A framework for building thermal comfort monitoring, visualizing, and assessment. Buildings 13:1971. https://doi.org/10.3390/buildings13081971
• Kang TW, Mo Y (2024) A comprehensive digital twin framework for building environment monitoring with emphasis on real-time data connectivity and predictability. Dev Built Environ 17:100309. https://doi.org/10.1016/j.dibe.2023.100309
• Opoku DGJ, Perera S, Osei-Kyei R, Rashidi M, Bamdad K, Famakinwa T (2024) Digital twin for indoor condition monitoring in living labs: University library case study. Autom Constr 157:105188. https://doi.org/10.1016/j.autcon.2023.105188
• Naderi H, Shojaei A (2022) Civil infrastructure digital twins: Multi-level knowledge map, research gaps, and future directions. IEEE Access 10:122022–122037. https://doi.org/10.1109/ACCESS.2022.3223557
• Salem T, Dragomir M (2022) Options for and challenges of employing digital twins in construction management. Appl Sci 12:2928. https://doi.org/10.3390/app12062928
• Naderi H, Shojaei A (2023) Digital twinning of civil infrastructures: Current state of model architectures, interoperability solutions, and future prospects. Autom Constr 149:104785. https://doi.org/10.1016/j.autcon.2023.104785
• Lucchi E (2023) Digital twins for the automation of the heritage construction sector. Autom Constr 156:105073. https://doi.org/10.1016/j.autcon.2023.105073
• Omrany H, Al-Obaidi KM, Husain A, Ghaffarianhoseini A (2023) Digital twins in the construction industry: A comprehensive review of current implementations, enabling technologies, and future directions. Sustainability 15:10908. https://doi.org/10.3390/su151410908
• Osadcha I, Jurelionis A, Fokaides P (2023) Geometric parameter updating in digital twin of built assets: A systematic literature review. J Build Eng 73:106704. https://doi.org/10.1016/j.jobe.2023.106704
• Hakimi O, Liu H, Abudayyeh O (2024) Digital twin-enabled smart facility management: A bibliometric review. Front Eng Manag 11:32–49. https://doi.org/10.1007/s42524-023-0254-4
• Radzi AR, Azmi NF, Kamaruzzaman SN, Rahman RA, Papadonikolaki E (2024) Relationship between digital twin and building information modeling: A systematic review and future directions. Constr Innov 24:811–829. https://doi.org/10.1108/CI-07-2022-0183
• Zhou Y, Wei X, Peng Y (2021) The modelling of digital twins technology in the construction process of prefabricated buildings. Adv Civ Eng 2021: Article 2801557. https://doi.org/10.1155/2021/2801557
• Mohseni S-R, Zeitouni MJ, Parvaresh A, Abrazeh S, Gheisarnejad M, Khooban M-H (2023) FMI real-time co-simulation-based machine deep learning control of HVAC systems in smart buildings: Digital-twins technology. Trans Inst Meas Control 45:661–673. https://doi.org/10.1177/01423312221119635
• de Wilde P (2023) Building performance simulation in the brave new world of artificial intelligence and digital twins: A systematic review. Energy Build 292:113171. https://doi.org/10.1016/j.enbuild.2023.113171
• Ammar A, Nassereddine H, AbdulBaky N, AbouKansour A, Tannoury J, Urban H, Schranz C (2022) Digital twins in the construction industry: A perspective of practitioners and building authority. Front Built Environ. https://doi.org/10.3389/fbuil.2022.834671
• Gourlis G, Kovacic I (2022) A holistic digital twin simulation framework for industrial facilities: BIM-based data acquisition for building energy modeling. Front Built Environ 8:918821. https://doi.org/10.3389/fbuil.2022.918821
• Chacón R, Posada H, Ramonell C, Jungmann M, Hartmann T, Khan R, Tomar R (2024) Digital twinning of building construction processes. Case study: A reinforced concrete cast-in structure. J Build Eng 84:108522. https://doi.org/10.1016/j.jobe.2024.108522
• Chen G, Alomari I, Taffese WZ, Shi Z, Afsharmovahed MH, Mondal TG, Nguyen S (2024) Multifunctional models in digital and physical twinning of the built environment—A university campus case study. Smart Cities 7:836–858. https://doi.org/10.3390/smartcities7020035
• Zhao L, Zhang H, Wang Q, Wang H (2021) Digital-twin-based evaluation of nearly zero-energy building for existing buildings based on scan-to-BIM. Adv Civ Eng 2021:6638897. https://doi.org/10.1155/2021/6638897
• Eneyew DD, Capretz MAM, Bitsuamlak GT (2022) Toward smart-building digital twins: BIM and IoT data integration. IEEE Access 10:130487–130506. https://doi.org/10.1109/ACCESS.2022.3229370
• Yang B, Lv Z, Wang F (2022) Digital twins for intelligent green buildings. Buildings 12:856. https://doi.org/10.3390/buildings12060856
• Zhao Y, Wang N, Liu Z, Mu E (2022) Construction theory for a building intelligent operation and maintenance system based on digital twins and machine learning. Buildings 12:87. https://doi.org/10.3390/buildings12020087
• Xie X, Merino J, Moretti N, Pauwels P, Chang JY, Parlikad A (2023) Digital twin enabled fault detection and diagnosis process for building HVAC systems. Autom Constr 146:104695. https://doi.org/10.1016/j.autcon.2022.104695
• Marienkov M, Kaliukh I, Trofymchuk O (2024) The digital twin use for modeling the multi-storey building response to seismic impacts. Struct Concr 25:2079–2096. https://doi.org/10.1002/suco.202300695
• Wang W, Xu K, Song S, Bao Y, Xiang C (2024) From BIM to digital twin in BIPV: A review of current knowledge. Sustain Energy Technol Assess 67:103855. https://doi.org/10.1016/j.seta.2024.103855
• Hosamo HH, Nielsen HK, Alnmr AN, Svennevig PR, Svidt K (2022) A review of the Digital Twin technology for fault detection in buildings. Front Built Environ 8:1013196. https://doi.org/10.3389/fbuil.2022.1013196
• Meschini S, Pellegrini L, Locatelli M, Accardo D, Tagliabue LC, Di Giuda GM, Avena M (2022) Toward cognitive digital twins using a BIM-GIS asset management system for a diffused university. Front Built Environ 8:959475. https://doi.org/10.3389/fbuil.2022.959475
• Tan Y, Chen P, Shou W, Sadick A-M (2022) Digital Twin-driven approach to improving energy efficiency of indoor lighting based on computer vision and dynamic BIM. Energy Build 270:112271. https://doi.org/10.1016/j.enbuild.2022.112271
• Hakimi O, Liu H, Abudayyeh O, Houshyar A, Almatared M, Alhawiti A (2023) Data fusion for smart civil infrastructure management: A conceptual digital twin framework. Buildings 13:2725. https://doi.org/10.3390/buildings13112725
• Zhou X, Sun K, Wang J, Zhao J, Feng C, Yang Y, Zhou W (2023) Computer vision enabled building digital twin using building information model. IEEE Trans Ind Inform 19:2684–2692. https://doi.org/10.1109/TII.2022.3190366
• Ghorbani A, Messner J (2024) A categorical approach for defining digital twins in the AECO industry. J Inf Technol Constr 29:198–218. https://doi.org/10.36680/j.itcon.2024.010
• 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 15:4497. https://doi.org/10.3390/en15124497
• Nguyen TD, Adhikari S (2023) The role of BIM in integrating digital twin in building construction: A literature review. Sustainability 15:10462. https://doi.org/10.3390/su151310462
• Yang J, Rong H (2024) Site-scale digital twinning: From city-scale modeling to multiple micro-urban interventions. SSRN. https://doi.org/10.2139/ssrn.4873135
• Mohandes SR, Singh AK, Fazeli A, Banihashemi S, Arashpour M, Cheung C, Ejohwomu O, Zayed T (2024) Determining the stationary digital twins implementation barriers for sustainable construction projects. Smart Sustain Built Environ. https://doi.org/10.1108/SASBE-11-2023-0344
• Walczyk G, Ożadowicz A (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 16:225. https://doi.org/10.3390/fi16070225
• Ghansah FA, Lu W (2024) Major opportunities of digital twins for smart buildings: A scientometric and content analysis. Smart Sustain Built Environ 13:63–84. https://doi.org/10.1108/SASBE-09-2022-0192
• Jasiński M, Łaziński P, Piotrowski D (2023) The concept of creating digital twins of bridges using load tests. Sensors 23:7349. https://doi.org/10.3390/s23177349
• Oulefki A, Kheddar H, Amira A, Kurugollu F, Himeur Y (2024) Innovative AI strategies for enhancing smart building operations through digital twins: A survey. SSRN. https://doi.org/10.2139/ssrn.5015571
• Kosse S, Vogt O, Wolf M, König M, Gerhard D (2022) Digital twin framework for enabling serial construction. Front Built Environ 8:864722. https://doi.org/10.3389/fbuil.2022.864722
• Drobnyi V, Hu Z, Fathy Y, Brilakis I (2023) Construction and maintenance of building geometric digital twins: State of the art review. Sensors 23:4382. https://doi.org/10.3390/s23094382
• Sepasgozar SME, Khan AA, Smith K, Romero JG, Shen X, Shirowzhan S, Li H, Tahmasebinia F (2023) BIM and digital twin for developing convergence technologies as future of digital construction. Buildings 13:441. https://doi.org/10.3390/buildings13020441
• Bakhshi S, Ghaffarianhoseini A, Ghaffarianhoseini A, Najafi M, Rahimian F, Park C, Lee D (2024) Digital twin applications for overcoming construction supply chain challenges. Autom Constr 167:105679. https://doi.org/10.1016/j.autcon.2023.105679
• Mitera-Kiełbasa E, Zima K (2024) Automated classification of exchange information requirements for construction projects using Word2Vec and SVM. Infrastructures 9:194. https://doi.org/10.3390/infrastructures9110194
• Li T, Li X, Rui Y, Ling J, Zhao S, Zhu H (2024) Digital twin for intelligent tunnel construction. Autom Constr 158:105210. https://doi.org/10.1016/j.autcon.2023.105210
• Hosamo HH, Imran A, Cardenas-Cartagena J, Svennevig PR, Svidt K, Nielsen HK (2022) A review of the digital twin technology in the AEC-FM industry. Adv Civ Eng 2022(1):2185170. https://doi.org/10.1155/2022/2185170
• Yang Z, Tang C, Zhang T, Zhang Z, Doan DT (2024) Digital twins in construction: Architecture, applications, trends, and challenges. Build 14:2616. https://doi.org/10.3390/buildings14092616
• Yeom S, Kim J, Kang H, Jung S, Hong T (2024) Digital twin (DT) and extended reality (XR) for building energy management. Energy Build 323:114746. https://doi.org/10.1016/j.enbuild.2024.114746
• Zahedi F, Alavi H, Majrouhi Sardroud J, Dang H (2024) Digital twins in the sustainable construction industry. Build 14:11. https://doi.org/10.3390/buildings14113613
• Osama Z (2024) The digital twin framework: A roadmap to the development of user-centred digital twin in the built environment. J Build Eng 98:111081. https://doi.org/10.1016/j.jobe.2024.111081
• Wang J, Wu Y, Wang S, Narazaki Y, Liu H, Spencer Jr BF (2024) Development and validation of graphics-based digital twin framework for UAV-aided post-earthquake inspection of high-rise buildings. Struct Des Tall Spec Build 33(13):e2127. https://doi.org/10.1002/tal.2127
• Jradi M, Madsen BE, Kaiser JH (2023) DanRETwin: A digital twin solution for optimal energy retrofit decision-making and decarbonization of the Danish building stock. Appl Sci 13(17):9778. https://doi.org/10.3390/app13179778
• Bäcklund K, Lundqvist P, Molinari M (2024) Showcasing a digital twin for higher educational buildings: Developing the concept toward human centricity. Front Built Environ 10:1347451. https://doi.org/10.3389/fbuil.2024.1347451
• Xu J, Shu X, Qiao P, Li S, Xu J (2023) Developing a digital twin model for monitoring building structural health by combining a building information model and a real-scene 3D model. Meas 217:112955. https://doi.org/10.1016/j.measurement.2023.112955
• Ellul C, Hamilton N, Pieri A, Floros G (2024) Exploring data for construction digital twins: Building health and safety and progress monitoring twins using the Unreal gaming engine. Build 14(7):2216. https://doi.org/10.3390/buildings14072216
• Hu X, Olgun G, Assaad RH (2024) An intelligent BIM-enabled digital twin framework for real-time structural health monitoring using wireless IoT sensing, digital signal processing, and structural analysis. Expert Syst Appl 252(Part A):124204. https://doi.org/10.1016/j.eswa.2024.124204
• Almatared M, Liu H, Abudayyeh O, Hakim O, Sulaiman M (2024) Digital-twin-based fire safety management framework for smart buildings. Build 14(1):4. https://doi.org/10.3390/buildings14010004
• Sousa MNP de O e, Correa FR (2023) Towards digital twins for heritage buildings: A workflow proposal. Int J Archit Comput 21(4):712–729. https://doi.org/10.1177/14780771231168226
• Cheng JCP, Zhang J, Kwok HHL, Tong JCK (2024) Thermal performance improvement for residential heritage building preservation based on digital twins. J Build Eng 82:108283. https://doi.org/10.1016/j.jobe.2023.108283
• Rausch C, Lu R, Talebi S, Haas C (2021) Deploying 3D scanning-based geometric digital twins during fabrication and assembly in offsite manufacturing. Int J Constr Manag 23(3):565–578. https://doi.org/10.1080/15623599.2021.1896942
• Yevu SK, Owusu EK, Chan APC, Sepasgozar SME, Kamat VR (2023) Digital twin-enabled prefabrication supply chain for smart construction and carbon emissions evaluation in building projects. J Build Eng 78:107598. https://doi.org/10.1016/j.jobe.2023.107598
• Hauer M, Hammes S, Zech P, Geisler-Moroder D, Plörer D, Miller J, van Karsbergen V, Pfluger R (2024) Integrating digital twins with BIM for enhanced building control strategies: A systematic literature review focusing on daylight and artificial lighting systems. Build 14(3):805. https://doi.org/10.3390/buildings14030805
• Naeem G, Asif M, Khalid M (2024) Industry 4.0 digital technologies for the advancement of renewable energy: Functions, applications, potential and challenges. Energy Convers Manag X 100779.
• Jeong D, Lee C, Choi Y, Jeong T (2024) Building digital twin data model based on public data. Build 14(9):2911. https://doi.org/10.3390/buildings14092911
• Dittrichhudsonvasetti Architects (DHVA, YTL Arena Complex, Bristol. https://www.dhva.co.uk/ytl-arena-bristol, 15 September 2024.
• Buro Happold, Battersea Power Station. https://www.burohappold.com/projects/battersea-power-station-building-works/, Accessed 15 September 2024.
• Architectural Digest, Vessel in Hudson Yards. https://www.architecturaldigest.com/story/vessel-hudson-yards-opens-public, Accessed 15 September 2024.
• Amazing Architecture, King Abdullah Financial District by Henning Larsen Architects. https://amazingarchitecture.com/office/king-abdullah-financial-district-by-henning-larsen-architects, 15 September 2024.
• Foster & Partners, Apple Park. https://www.fosterandpartners.com/projects/apple-park, 15 September 2024.
• National University of Singapore (NUS), Digital Twin. https://cde.nus.edu.sg/research/digital-twin/, Accessed 5 October 2024.
• PLP Architecture, The EDGE Amsterdam. https://plparchitecture.com/the-edge/, Accessed 5 October 2024.
• Dezeen, Nanjing International Youth Cultural Centre. https://www.dezeen.com/2016/09/27/zaha-hadid-architects-nanjing-international-youth-cultural-centre-skyscraper-china/, 5 October 2024.
• Hammer Mission, BIM & Digital Twins: 3 Real-World Examples. https://www.hammermissions.com/post/bim-digital-twins-3-real-world-examples, 5 October 2024.
• Inexhibit, Stefano Boeri’s Vertical Forest. From Hype to Archetype. https://www.inexhibit.com/case-studies/the-vertical-forest-towers-in-milan-by-boeri-phenomenon-or-archetype/#google_vignette, Accessed 5 October 2024.
• Digital Dubai, Digital Dubai Initiatives. https://www.digitaldubai.ae/initiatives, 15 September 2024.
• Smart Nation Singapore, Smart Nation Initiatives. https://www.smartnation.gov.sg/, 15 September 2024.
• Florian MC (2024) Notre Dame Rebuilt: A Journey of Restoration for France's Iconic Cathedral. https://www.archdaily.com/1024689/notre-dame-rebuilt-a-journey-of-restoration-for-frances-iconic-cathedral, Accessed 5 January 2025.