Cited by Towards a digitally enabled intelligent coal mine integrated energy system: Evolution, conceptualization, and implementation

Digital Twins for Reducing Energy Consumption in Buildings: A Review DOI

B.P. Arsecularatne, Navodana Rodrigo, Ruidong Chang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(21), P. 9275 - 9275

Published: Oct. 25, 2024

This research investigates the use of digital twin (DT) technology to improve building energy management and analyse occupant behaviour. DTs perform function acting as virtual replicas physical assets, which facilitates real-time monitoring, predictive maintenance, data-driven decision-making. Consequently, performance comfort can be enhanced. study evaluates efficiency in optimising usage by a mix systematic literature review scientometric analysis 466 articles from Scopus database. Among main obstacles noted are interoperability issues, privacy data quality difficulties, requirement for more thorough integration interactions. The results highlight necessity standardised frameworks direct DT implementations suggest areas further study, especially improving cybersecurity incorporating behaviour into models. makes practical recommendations using increase sustainability built environment.

Language: Английский

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AI-Driven Digital Twins for Enhancing Indoor Environmental Quality and Energy Efficiency in Smart Building Systems DOI

İbrahim Yitmen,

Amjad Almusaed,

Mohammed Bahreldin Hussein

et al.

Buildings, Journal Year: 2025, Volume and Issue: 15(7), P. 1030 - 1030

Published: March 24, 2025

Smart buildings equipped with diverse control systems serve the objectives of gathering data, optimizing energy efficiency (EE), and detecting diagnosing faults, particularly in domain indoor environmental quality (IEQ). Digital twins (DTs) offering an environmentally sustainable solution for managing facilities incorporated artificial intelligence (AI) create opportunities maintaining IEQ EE. The purpose this study is to assess impact AI-driven DTs on enhancing EE smart building (SBS). A scoping review was performed establish theoretical background about DTs, AI, IEQ, SBS, semi-structured interviews were conducted specialists industry obtain qualitative quantitative data gathered via a computerized self-administered questionnaire (CSAQ) survey, focusing how can improve SBS. results indicate that DT enhances occupants’ comfort energy-efficiency performance enables decision-making automatic fault detection maintenance conditioning buildings’ serviceability real time, response key industrial needs management (BEMS) interrogative predictive analytics maintenance. integration AI presents transformative approach improving practical implications advancement span across design, construction, policy domains, significant challenges need be carefully considered.

Language: Английский

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The role of metaverse technologies in energy systems towards sustainable development goals DOI

Raghu Raman, Pradeep Kautish, Aaliyah Siddiqui

et al.

Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 4459 - 4476

Published: April 14, 2025

Language: Английский

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

Aslıhan Şenel Solmaz

Journal of Innovative Engineering and Natural Science, Journal Year: 2025, Volume and Issue: 5(1), P. 399 - 435

Published: Jan. 30, 2025

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

Language: Английский

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Monocular depth estimation via a detail semantic collaborative network for indoor scenes DOI

Wen Song, Xu Cui, Yakun Xie

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 31, 2025

Monocular image depth estimation is crucial for indoor scene reconstruction, and it plays a significant role in optimizing building energy efficiency, environment modeling, smart space design. However, the small variability of scenes leads to weakly distinguishable detail features. Meanwhile, there are diverse types objects, expression correlation among different objects complicated. Additionally, robustness recent models still needs further improvement given these environments. To address problems, detail‒semantic collaborative network (DSCNet) proposed monocular scenes. First, contextual features contained images fully captured via hierarchical transformer structure. Second, structure established, which establishes selective attention feature map extract details semantic information from maps. The extracted subsequently fused improve perception ability network. Finally, complex addressed by aggregating detailed at levels, model accuracy effectively improved without increasing number parameters. tested on NYU SUN datasets. approach produces state-of-the-art results compared with 14 performance optimal methods. In addition, discussed analyzed terms stability, robustness, ablation experiments availability

Language: Английский

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Digital Twin-Enabled Building Information Modeling–Internet of Things (BIM-IoT) Framework for Optimizing Indoor Thermal Comfort Using Machine Learning DOI

Fahad Iqbal, Shayan Mirzabeigi

Buildings, Journal Year: 2025, Volume and Issue: 15(10), P. 1584 - 1584

Published: May 8, 2025

As the world moves toward a low-carbon future, key challenge is improving buildings’ energy performance while maintaining occupant thermal comfort. Emerging digital tools such as Internet of Things (IoT) and Building Information Modeling (BIM) offer significant potential, enabling precise monitoring control building systems. However, integrating these technologies into unified Digital Twin (DT) framework remains underexplored, particularly in relation to Additionally, real-world case studies are limited. This paper presents DT-based system that combines BIM IoT sensors monitor indoor comfort real time through an easy-to-use web platform. By using spatial geometric data along with real-time from sensors, visualizes simplified Predicted Mean Vote (sPMV) index. Furthermore, it also uses hybrid machine learning model Facebook Prophet Long Short-Term Memory (LSTM) predict future environmental parameters. The enables Model Predictive Control (MPC) providing managers scalable tool collect, analyze, visualize, optimize time.

Language: Английский

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Data Analytics for XR-Based Environmental Sustainability Metrics DOI

Krishnamurty Raju Mudunuru

Published: Jan. 1, 2025

Language: Английский

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Data Science for Environmental Impact Assessment Using XR DOI

Sandip J. Gami

Published: Jan. 1, 2025

Language: Английский

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