Digital Twins for Intelligent Green Buildings
Abstract
:1. Introduction
- ➢
- Section 1 introduces the development status and trend of the core word involved, green building, and mentions the advantages of the combination of DTs and IGB.
- ➢
- Section 2 conducts a specific overview and analysis of the intelligent application, realization and trend of IGB.
- ➢
- Section 3 discusses development research on the integration of IGB and DTs.
- ➢
- Section 4 summarizes and studies the subsequent development advantages and challenges of IGB, making their advantages and problems more prominent.
- ➢
- Section 5 is the conclusion. It summarizes this review, highlights the results of this research and further understands the deficiencies and follow-up prospects.
2. Intelligent Development of Green Building
2.1. Content and Adoption of Green Building
2.1.1. Content and Development of Green Building
2.1.2. Concrete Adoption of Green Building
2.2. The Intelligence of Green Building
2.3. Realization and Adoption of Intelligent Green Building
3. Intelligent Green Building in a Digital Twin Smart City
3.1. Digital Twins in Smart Cities
3.1.1. Digital Twin 3D Modeling and Real-Time Visualization
3.1.2. Adoption of Digital Twins in Smart Cities
3.2. Integration of Smart Cities and Intelligent Green Building
4. Development Advantages and Challenges of Intelligent Green Building
4.1. Development Advantage and Adoption Value of Intelligent Green Building
4.2. Challenges and Opportunities of Intelligent Green Building
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Franco, M.A.J.Q.; Pawar, P.; Wu, X. Green building policies in cities: A comparative assessment and analysis. Energy Build. 2021, 231, 110561. [Google Scholar] [CrossRef]
- Yadegaridehkordi, E.; Hourmand, M.; Nilashi, M.; Alsolami, E.; Samad, S.; Mahmoud, M.; Alarood, A.A.; Zainol, A.; Majeed, H.D.; Shuib, L. Assessment of sustainability indicators for green building manufacturing using fuzzy multi-criteria decision making approach. J. Clean. Prod. 2020, 277, 122905. [Google Scholar] [CrossRef]
- Azis, S.S.A.; Zulkifli, N.A.A.; Rahman, N.H.A. Influential factors to occupy green residential building among green building occupants. Environ. Toxicol. Manag. 2021, 1, 7–13. [Google Scholar] [CrossRef]
- Wei, W.; Wargocki, P.; Zirngibl, J.; Bendžalová, J.; Mandin, C. Review of parameters used to assess the quality of the indoor environment in Green Building certification schemes for offices and hotels. Energy Build. 2020, 209, 109683. [Google Scholar] [CrossRef]
- Vyas, G.S.; Jha, K.N.; Patel, D.A. Development of green building rating system using AHP and fuzzy integrals: A case of India. J. Archit. Eng. 2019, 25, 04019004. [Google Scholar] [CrossRef]
- Shan, M.; Hwang, B.-G. Green building rating systems: Global reviews of practices and research efforts. Sustain. Cities Soc. 2018, 39, 172–180. [Google Scholar] [CrossRef]
- Lin, Y.H.; Lin, M.D.; Tsai, K.T.; Deng, M.J.; Ishii, H. Multi-objective optimization design of green building envelopes and air conditioning systems for energy conservation and CO2 emission reduction. Sustain. Cities Soc. 2021, 64, 102555. [Google Scholar] [CrossRef]
- Jiang, S.; Wang, N.; Wu, J. Combining BIM and Ontology to Facilitate Intelligent Green Building Evaluation. J. Comput. Civ. Eng. 2018, 32, 04018039. [Google Scholar] [CrossRef]
- Berawi, M.A.; Miraj, P.; Windrayani, R.; Berawi, A.R.B. Stakeholders’ perspectives on green building rating: A case study in Indonesia. Heliyon 2019, 5, e01328. [Google Scholar] [CrossRef] [Green Version]
- Apanaviciene, R.; Vanagas, A.; Fokaides, P.A. Smart Building Integration into a Smart City (SBISC): Development of a New Evaluation Framework. Energies 2020, 13, 2190. [Google Scholar] [CrossRef]
- Purwantiasning, A.W.; Bahri, S. An application of smart building concept for historical building using automatic control system. case study: Fatahillah Museum. Int. J. Built Environ. Sci. Res. 2017, 1, 115–122. [Google Scholar]
- Plageras, A.P.; Psannis, K.E.; Stergiou, C.; Wang, H.; Gupta, B.B. Efficient IoT-based sensor BIG Data collection–processing and analysis in smart buildings. Future Gener. Comput. Syst. 2018, 82, 349–357. [Google Scholar] [CrossRef]
- Dey, M.; Rana, S.P.; Dudley, S. A Case Study Based Approach for Remote Fault Detection Using Multi-Level Machine Learning in A Smart Building. Smart Cities 2020, 3, 401–419. [Google Scholar] [CrossRef]
- Talei, H.; Benhaddou, D.; Gamarra, C.; Benbrahim, H.; Essaaidi, M. Smart Building Energy Inefficiencies Detection through Time Series Analysis and Unsupervised Machine Learning. Energies 2021, 14, 6042. [Google Scholar] [CrossRef]
- Rashid, S.J.; Alkababji, A.; Khidhir, A.S. Communication and network technologies of IoT in smart building: A survey. NTU J. Eng. Technol. 2021, 1, 1–18. [Google Scholar]
- Chew MY, L.; Teo EA, L.; Shah, K.W.; Kumar, V.; Hussein, G.F. Evaluating the Roadmap of 5G Technology Implementation for Smart Building and Facilities Management in Singapore. Sustainability 2020, 12, 10259. [Google Scholar] [CrossRef]
- Dong, B.; Prakash, V.; Feng, F.; O’Neill, Z. A review of smart building sensing system for better indoor environment control. Energy Build. 2019, 199, 29–46. [Google Scholar] [CrossRef]
- Ren, Z.; Verma, A.S.; Li, Y.; Teuwen, J.J.; Jiang, Z. Offshore wind turbine operations and maintenance: A state-of-the-art review. Renew. Sustain. Energy Rev. 2021, 144, 110886. [Google Scholar] [CrossRef]
- Yang, L.; Li, G.; Zhang, Z.; Ma, X.; Zhao, Y. Operations & Maintenance Optimization of Wind Turbines Integrating Wind and Aging Information. IEEE Trans. Sustain. Energy 2020, 12, 211–221. [Google Scholar] [CrossRef]
- Sartori, T.; Drogemuller, R.; Omrani, S.; Lamari, F. A schematic framework for Life Cycle Assessment (LCA) and Green Building Rating System (GBRS). J. Build. Eng. 2021, 38, 102180. [Google Scholar] [CrossRef]
- Lu, Y.; Liu, C.; Kevin, I.; Wang, K.; Huang, H.; Xu, X. Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues. Robot. Comput.-Integr. Manuf. 2019, 61, 101837. [Google Scholar] [CrossRef]
- Khajavi, S.H.; Motlagh, N.H.; Jaribion, A.; Werner, L.C.; Holmström, J. Digital twin: Vision, benefits, boundaries, and creation for buildings. IEEE Access 2019, 7, 147406–147419. [Google Scholar] [CrossRef]
- Krężlik, A. Wiele początków: Idea, myśliciele i działania stojące za architekturą przyjazną dla planety. Bud. I Arch.-Tektura 2021, 20, 5–24. [Google Scholar]
- Li, Y.; Rong, Y.; Ahmad, U.M.; Wang, X.; Zuo, J.; Mao, G. A comprehensive review on green buildings research: Bibliometric analysis during 1998–2018. Environ. Sci. Pollut. Res. 2021, 28, 46196–46214. [Google Scholar] [CrossRef]
- MacNaughton, P.; Cao, X.; Buonocore, J.; Cedeno-Laurent, J.; Spengler, J.; Bernstein, A.; Allen, J. Energy savings, emission reductions, and health co-benefits of the green building movement. J. Expo. Sci. Environ. Epidemiol. 2018, 28, 307–318. [Google Scholar] [CrossRef]
- Abd Rahman, N.M.; Lim, C.H.; Fazlizan, A. Optimizing the energy saving potential of public hospital through a systematic ap-proach for green building certification in Malaysia. J. Build. Eng. 2021, 43, 103088. [Google Scholar] [CrossRef]
- Ashraf, S. A proactive role of IoT devices in building smart cities. Internet Things Cyber-Phys. Syst. 2021, 1, 8–13. [Google Scholar] [CrossRef]
- Zhang, X.; Mohandes, S.R. Occupational Health and Safety in green building construction projects: A holistic Z-numbers-based risk management framework. J. Clean. Prod. 2020, 275, 122788. [Google Scholar] [CrossRef]
- Ade, R.; Rehm, M. Buying limes but getting lemons: Cost-benefit analysis of residential green buildings-A New Zealand case study. Energy Build. 2019, 186, 284–296. [Google Scholar] [CrossRef]
- Tirkey, N.; Kumar, G.B.R. Analysis on the diagrid structure with the conventional building frame using ETABS. Mater. Today Proc. 2020, 22, 514–518. [Google Scholar] [CrossRef]
- Daissaoui, A.; Boulmakoul, A.; Karim, L.; Lbath, A. IoT and big data analytics for smart buildings: A survey. Procedia Comput. Sci. 2020, 170, 161–168. [Google Scholar] [CrossRef]
- Razmjoo, A.; Nezhad, M.M.; Kaigutha, L.G.; Marzband, M.; Mirjalili, S.; Pazhoohesh, M.; Memon, S.; Ehyaei, M.A.; Piras, G. Investigating smart city development based on green buildings, electrical vehicles and feasible indicators. Sustainability 2021, 13, 7808. [Google Scholar] [CrossRef]
- Ma, M.; Cai, W.; Wu, Y. China Act on the Energy Efficiency of Civil Buildings (2008): A decade review. Sci. Total Environ. 2019, 651, 42–60. [Google Scholar] [CrossRef] [PubMed]
- Hannan, M.A.; Faisal, M.; Ker, P.J.; Mun, L.H.; Parvin, K.; Mahlia, T.M.; Blaabjerg, F. A review of internet of energy based building energy management systems: Issues and recommendations. IEEE Access 2018, 6, 38997–39014. [Google Scholar] [CrossRef]
- Su, Y.; Wang, L.; Feng, W.; Zhou, N.; Wang, L. Analysis of green building performance in cold coastal climates: An in-depth evaluation of green buildings in Dalian, China. Renew. Sustain. Energy Rev. 2021, 146, 111149. [Google Scholar] [CrossRef]
- Bano, F.; Sehgal, V. Evaluation of energy-efficient design strategies: Comparison of the thermal performance of energy-efficient office buildings in composite climate, India. Sol. Energy 2018, 176, 506–519. [Google Scholar] [CrossRef]
- Nguyen, H.T.; Skitmore, M.; Gray, M.; Zhang, X.; Olanipekun, A.O. Will green building development take off? An exploratory study of barriers to green building in Vietnam. Resour. Conserv. Recycl. 2017, 127, 8–20. [Google Scholar] [CrossRef] [Green Version]
- Cecchini, M.; Zambon, I.; Pontrandolfi, A.; Turco, R.; Colantoni, A.; Mavrakis, A.; Salvati, L. Urban sprawl and the ‘olive’ landscape: Sustainable land management for ‘crisis’ cities. GeoJournal 2019, 84, 237–255. [Google Scholar] [CrossRef]
- Fan, Y.; Xia, X. Energy-efficiency building retrofit planning for green building compliance. Build. Environ. 2018, 136, 312–321. [Google Scholar] [CrossRef]
- Sharma, M. Development of a ‘Green building sustainability model’ for Green buildings in India. J. Clean. Prod. 2018, 190, 538–551. [Google Scholar] [CrossRef]
- Wu, X.; Peng, B.; Lin, B. A dynamic life cycle carbon emission assessment on green and non-green buildings in China. Energy Build. 2017, 149, 272–281. [Google Scholar] [CrossRef]
- Zou, Y.; Zhao, W.; Zhong, R. The spatial distribution of green buildings in China: Regional imbalance, economic fundamentals, and policy incentives. Appl. Geogr. 2017, 88, 38–47. [Google Scholar] [CrossRef]
- Islam, S.; Bhat, G. Environmentally-friendly thermal and acoustic insulation materials from recycled textiles. J. Environ. Manag. 2019, 251, 109536. [Google Scholar] [CrossRef] [PubMed]
- Chan AP, C.; Darko, A.; Ameyaw, E.E.; Owusu-Manu, D.G. Barriers affecting the adoption of green building technologies. J. Manag. Eng. 2017, 33, 04016057. [Google Scholar] [CrossRef]
- Darko, A.; Chan AP, C.; Owusu-Manu, D.G.; Ameyaw, E.E. Drivers for implementing green building technologies: An international survey of experts. J. Clean. Prod. 2017, 145, 386–394. [Google Scholar] [CrossRef] [Green Version]
- Darko, A.; Chan, A.P.; Huo, X.; Owusu-Manu, D.-G. A scientometric analysis and visualization of global green building research. Build. Environ. 2019, 149, 501–511. [Google Scholar] [CrossRef]
- Chandrika, V.S.; Karthick, A.; Kumar, N.M.; Kumar, P.M.; Stalin, B. Experimental analysis of solar concrete collector for residential buildings. Int. J. Green Energy 2021, 18, 615–623. [Google Scholar] [CrossRef]
- Zhang, C.; Cui, C.; Zhang, Y.; Yuan, J.; Luo, Y.; Gang, W. A review of renewable energy assessment methods in green building and green neighborhood rating systems. Energy Build. 2019, 195, 68–81. [Google Scholar] [CrossRef]
- Hazama, H.; Masuoka, Y.; Suzumura, A.; Matsubara, M.; Tajima, S.; Asahi, R. Cylindrical thermoelectric generator with water heating system for high solar energy conversion efficiency. Appl. Energy 2018, 226, 381–388. [Google Scholar] [CrossRef]
- Sher, F.; Kawai, A.; Gulec, F.; Sadiq, H. Sustainable energy saving alternatives in small buildings. Sustain. Energy Technol. Assessments 2019, 32, 92–99. [Google Scholar] [CrossRef]
- Halawa, E.; Ghaffarianhoseini, A.; Ghaffarianhoseini, A.; Trombley, J.; Hassan, N.; Baig, M.; Yusoff, S.Y.; Ismail, M.A. A review on energy conscious designs of building façades in hot and humid climates: Lessons for (and from) Kuala Lumpur and Darwin. Renew. Sustain. Energy Rev. 2018, 82, 2147–2161. [Google Scholar] [CrossRef]
- Wang, J.; He, B.J.; Wang, H.; Santamouris, M. Towards higher quality green building agenda–an overview of the application of green building techniques in china. Sol. Energy 2019, 193, 473–493. [Google Scholar] [CrossRef]
- Kumar, A.; Shukla, S.; Dixit, P.; Thupstan, T.; Kumar, K. Vertical farming promising cultivation for horticultural crops. Int. J. Curr. Microbiol. Appl. Sci. 2020, 9, 2491–2494. [Google Scholar] [CrossRef]
- Eze, C.E.; Ugulu, R.A.; Egwunatum, S.I. Green building materials products and service market in the construction industry. J. Eng. Proj. Prod. Manag. 2021, 11, 89–101. [Google Scholar]
- Singh, S.K.; Jeong, Y.S.; Park, J.H. A deep learning-based IoT-oriented infrastructure for secure smart city. Sustain. Cities Soc. 2020, 60, 102252. [Google Scholar] [CrossRef]
- Almeida, L.M.; Tam, V.W.Y.; Le, K.N. Quantification of the energy use due to occupant behaviour collected in surveys: A case study of a green and non-green building. J. Build. Perform. Simul. 2020, 13, 777–803. [Google Scholar] [CrossRef]
- Yu, K.H.; Zhang, Y.; Li, D.; Montenegro-Marin, C.E.; Kumar, P.M. Environmental planning based on reduce, reuse, recycle and recover using artificial intelligence. Environ. Impact Assess. Rev. 2021, 86, 106492. [Google Scholar] [CrossRef]
- Das, S.; Mao, E. The global energy footprint of information and communication technology electronics in connected Inter-net-of-Things devices. Sustain. Energy Grids Netw. 2020, 24, 100408. [Google Scholar] [CrossRef]
- Popli, S.; Jha, R.K.; Jain, S. A Survey on Energy Efficient Narrowband Internet of Things (NBIoT): Architecture, Application and Challenges. IEEE Access 2018, 7, 16739–16776. [Google Scholar] [CrossRef]
- Alsamhi, S.H.; Ma, O.; Ansari, M.S.; Meng, Q. Greening internet of things for greener and smarter cities: A survey and future prospects. Telecommun. Syst. 2019, 72, 609–632. [Google Scholar] [CrossRef]
- Jin, D.; Yuan, K.; Du, X.; Wang, Q.; Wang, S.; Zhang, L. Domino Reaction Encoded Heterogeneous Colloidal Microswarm with On-Demand Morphological Adaptability. Adv. Mater. 2021, 33, 2100070. [Google Scholar] [CrossRef] [PubMed]
- Prada, M.; Prada, I.F.; Cristea, M.; Popescu, D.E.; Bungău, C.; Aleya, L. New solutions to reduce greenhouse gas emissions through energy efficiency of buildings of special importance—Hospitals. Sci. Total. Environ. 2020, 718, 137446. [Google Scholar] [CrossRef] [PubMed]
- Xu, W.; Yang, L.J.; Lee, Y.K. CMOS compatible MEMS air velocity sensor with improved sensitivity and linearity for human thermal comfort sensing applications. IEEE Sens. J. 2021, 21, 23872–23879. [Google Scholar]
- Sharma, D.; Rehu, J.; Känsälä, K.; Ailisto, H. An Automatic Aggregator of Power Flexibility in Smart Buildings Using Software Based Orchestration. Sensors 2021, 21, 867. [Google Scholar] [CrossRef] [PubMed]
- Yu, L.; Nazir, B.; Wang, Y. Intelligent power monitoring of building equipment based on Internet of Things technology. Comput. Commun. 2020, 157, 76–84. [Google Scholar] [CrossRef]
- Panteli, C.; Kylili, A.; Fokaides, P.A. Building information modelling applications in smart buildings: From design to commissioning and beyond A critical review. J. Clean. Prod. 2020, 265, 121766. [Google Scholar] [CrossRef]
- Al Dakheel, J.; Del Pero, C.; Aste, N.; Leonforte, F. Smart buildings features and key performance indicators: A review. Sustain. Cities Soc. 2020, 61, 102328. [Google Scholar] [CrossRef]
- Aguilar, J.; Garces-Jimenez, A.; R-Moreno, M.; García, R. A systematic literature review on the use of artificial intelligence in energy self-management in smart buildings. Renew. Sustain. Energy Rev. 2021, 151, 111530. [Google Scholar] [CrossRef]
- Singh, T.; Solanki, A.; Sharma, S.K. Role of Ssmart buildings in smart city—Components, technology, indicators, challenges, future research opportunities. In Digital Cities Roadmap: IoT-Based Architecture and Sustainable Buildings; Wiley: Hoboken, NJ, USA, 2021; pp. 449–476. [Google Scholar]
- Bibri, S.E. The eco-city and its core environmental dimension of sustainability: Green energy technologies and their integration with data-driven smart solutions. Energy Inform. 2020, 3, 1–26. [Google Scholar] [CrossRef]
- Zhang, Y.; Wang, W.; Wang, Z.; Gao, M.; Zhu, L.; Song, J. Green building design based on solar energy utilization: Take a kindergarten competition design as an example. Energy Rep. 2021, 7, 1297–1307. [Google Scholar] [CrossRef]
- Sepasgozar, S.M.E. Differentiating digital twin from digital shadow: Elucidating a paradigm shift to expedite a smart, sus-tainable built environment. Buildings 2021, 11, 151. [Google Scholar] [CrossRef]
- Yang, J.; Kang, Z.; Zeng, L.; Akwensi, P.H.; Sester, M. Semantics-guided reconstruction of indoor navigation elements from 3D colorized points. ISPRS J. Photogramm. Remote Sens. 2021, 173, 238–261. [Google Scholar] [CrossRef]
- Perc, M.N.; Topolšek, D. Using the scanners and drone for comparison of point cloud accuracy at traffic accident analysis. Ac-Cident Anal. Prev. 2020, 135, 105391. [Google Scholar]
- Shi, X.; Liu, T.; Han, X. Improved Iterative Closest Point(ICP) 3D point cloud registration algorithm based on point cloud filtering and adaptive fireworks for coarse registration. Int. J. Remote Sens. 2020, 41, 3197–3220. [Google Scholar] [CrossRef]
- Wang, K.J.; Lee, Y.H.; Angelica, S. Digital twin design for real-time monitoring–a case study of die cutting machine. Int. J. Prod. Res. 2021, 59, 6471–6485. [Google Scholar] [CrossRef]
- Jiang, H.; Qin, S.; Fu, J.; Zhang, J.; Ding, G. How to model and implement connections between physical and virtual models for digital twin application. J. Manuf. Syst. 2020, 58, 36–51. [Google Scholar] [CrossRef]
- Guo, J.; Yuan, L.; Wang, Q. Time and cost analysis of geometric quality assessment of structural columns based on 3D terrestrial laser scanning. Autom. Constr. 2020, 110, 103014. [Google Scholar] [CrossRef]
- Ren, K.; Chew, Y.; Zhang, Y.; Fuh, J.; Bi, G. Thermal field prediction for laser scanning paths in laser aided additive manufacturing by physics-based machine learning. Comput. Methods Appl. Mech. Eng. 2020, 362, 112734. [Google Scholar] [CrossRef]
- Lee, D.; Lee, S.H.; Masoud, N.; Krishnan, M.S.; Li, V.C. Integrated digital twin and blockchain framework to support accountable information sharing in construction projects. Autom. Constr. 2021, 127, 103688. [Google Scholar] [CrossRef]
- Li, X.; Cao, J.; Liu, Z.; Luo, X. Sustainable Business Model Based on Digital Twin Platform Network: The Inspiration from Haier’s Case Study in China. Sustainability 2020, 12, 936. [Google Scholar] [CrossRef] [Green Version]
- Liu, M.; Fang, S.; Dong, H.; Xu, C. Review of digital twin about concepts, technologies, and industrial applications. J. Manuf. Syst. 2021, 58, 346–361. [Google Scholar] [CrossRef]
- Fan, C.; Jiang, Y.; Mostafavi, A. Social Sensing in Disaster City Digital Twin: Integrated Textual–Visual–Geo Framework for Situational Awareness during Built Environment Disruptions. J. Manag. Eng. 2020, 36, 04020002. [Google Scholar] [CrossRef]
- Nguyen, T.; Duong, Q.H.; Van Nguyen, T.; Zhu, Y.; Zhou, L. Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review. Int. J. Prod. Econ. 2022, 244, 108381. [Google Scholar] [CrossRef]
- Shirowzhan, S.; Tan, W.; Sepasgozar, S.M.E. Digital Twin and CyberGIS for Improving Connectivity and Measuring the Impact of Infrastructure Construction Planning in Smart Cities. ISPRS Int. J. Geo-Inf. 2020, 9, 240. [Google Scholar] [CrossRef]
- Yigitcanlar, T.; Mehmood, R.; Corchado, J.M. Green artificial intelligence: Towards an efficient, sustainable and equitable tech-nology for smart cities and futures. Sustainability 2021, 13, 8952. [Google Scholar] [CrossRef]
- Liang, C. Exploring the “Green” Transformation Planning of Industrial Parks in the Era of Low Carbon Economy. World J. Eng. Technol. 2021, 09, 747–754. [Google Scholar] [CrossRef]
- Mahmoud, M.M.A.S. Automated smart utilization of background lights and daylight for green building efficient and economic indoor lighting intensity control. Intell. Control. Autom. 2021, 12, 1. [Google Scholar] [CrossRef]
- Yuan, X.; Chen, Z.; Liang, Y.; Pan, Y.; Jokisalo, J.; Kosonen, R. Heating energy-saving potentials in HVAC system of swimming halls: A review. Build. Environ. 2021, 205, 108189. [Google Scholar] [CrossRef]
- Amiri, A.; Emami, N.; Ottelin, J.; Sorvari, J.; Marteinsson, B.; Heinonen, J.; Junnila, S. Embodied emissions of buildings—A forgotten factor in green building certificates. Energy Build. 2021, 241, 110962. [Google Scholar] [CrossRef]
- Long, H.; Liu, H.; Li, X.; Chen, L. An Evolutionary Game Theory Study for Construction and Demolition Waste Recycling Considering Green Development Performance under the Chinese Government’s Reward–Penalty Mechanism. Int. J. Environ. Res. Public Health 2020, 17, 6303. [Google Scholar] [CrossRef] [PubMed]
- Shafique, M.; Luo, X.; Zuo, J. Photovoltaic-green roofs: A review of benefits, limitations, and trends. Sol. Energy 2020, 202, 485–497. [Google Scholar] [CrossRef]
- Azizi, S.; Nair, G.; Rabiee, R.; Olofsson, T. Application of Internet of Things in academic buildings for space use efficiency using occupancy and booking data. Build. Environ. 2020, 186, 107355. [Google Scholar] [CrossRef] [PubMed]
- Taherahmadi, J.; Noorollahi, Y.; Panahi, M. Toward comprehensive zero energy building definitions: A literature review and recommendations. Int. J. Sustain. Energy 2020, 40, 120–148. [Google Scholar] [CrossRef]
- Liu, X.; Wang, M.; Fu, H. Visualized analysis of knowledge development in green building based on bibliographic data mining. J. Supercomput. 2020, 76, 3266–3282. [Google Scholar] [CrossRef]
- Gan, V.J.; Lo, I.M.; Ma, J.; Tse, K.T.; Cheng, J.C.; Chan, C.M. Simulation optimisation towards energy efficient green buildings: Current status and future trends. J. Clean. Prod. 2020, 254, 120012. [Google Scholar] [CrossRef]
- Sharma, N.K. Sustainable building material for green building construction, conservation and refurbishing. Int. J. Adv. Sci. Technol. 2020, 29, 5343–5350. [Google Scholar]
- Khoshnava, S.M.; Rostami, R.; Mohamad Zin, R.; Štreimikienė, D.; Mardani, A.; Ismail, M. The role of green building materials in reducing environmental and human health impacts. Int. J. Environ. Res. Public Health 2020, 17, 2589. [Google Scholar] [CrossRef]
- Li, L.; Sun, W.; Hu, W.; Sun, Y. Impact of natural and social environmental factors on building energy consumption: Based on bib-liometrics. J. Build. Eng. 2021, 37, 102136. [Google Scholar] [CrossRef]
- Martins, P.; Lopes, S.I.; Rosado da Cruz, A.M.; Curado, A. Towards a smart & sustainable campus: An application-oriented architecture to streamline digitization and strengthen sustainability in academia. Sustainability 2021, 13, 3189. [Google Scholar]
- Chi, B.; Lu, W.; Ye, M.; Bao, Z.; Zhang, X. Construction waste minimization in green building: A comparative analysis of LEED-NC 2009 certified projects in the US and China. J. Clean. Prod. 2020, 256, 120749. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Yang, B.; Lv, Z.; Wang, F. Digital Twins for Intelligent Green Buildings. Buildings 2022, 12, 856. https://doi.org/10.3390/buildings12060856
Yang B, Lv Z, Wang F. Digital Twins for Intelligent Green Buildings. Buildings. 2022; 12(6):856. https://doi.org/10.3390/buildings12060856
Chicago/Turabian StyleYang, Bin, Zhihan Lv, and Faming Wang. 2022. "Digital Twins for Intelligent Green Buildings" Buildings 12, no. 6: 856. https://doi.org/10.3390/buildings12060856
APA StyleYang, B., Lv, Z., & Wang, F. (2022). Digital Twins for Intelligent Green Buildings. Buildings, 12(6), 856. https://doi.org/10.3390/buildings12060856