Study on city digital twin technologies for sustainable smart city design: A review and bibliometric analysis of geographic information system and building information modeling integration

Sustainable Cities and Society, Journal Year: 2022, Volume and Issue: 84, P. 104009 - 104009

Published: June 18, 2022

Language: Английский

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Building Information Modelling and Internet of Things Integration for Facility Management—Literature Review and Future Needs

Applied Sciences, Journal Year: 2021, Volume and Issue: 11(7), P. 3062 - 3062

Published: March 30, 2021

Digitisation of the built environment is seen as a significant factor for innovation in Architecture, Engineering, Construction and Operation sector. However, lack data information as-built digital models considerably limits potential Building Information Modelling Facility Management. Therefore, optimisation collection management needed, all more so now that Industry 4.0 has widened use sensors into buildings infrastructures. A literature review on two main pillars digitalisation construction, Internet Things, presented, along with bibliographic analysis citations abstracts databases focusing operations stage. The research been carried out using Web Science Scopus databases. article aimed at providing detailed BIM–IoT integration Management (FM) process improvements. Issues, opportunities areas where further efforts are required outlined. Finally, four key development FM have proposed, optimising management.

Language: Английский

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Augmented and Virtual Reality (AR/VR) for Education and Training in the AEC Industry: A Systematic Review of Research and Applications

Buildings, Journal Year: 2022, Volume and Issue: 12(10), P. 1529 - 1529

Published: Sept. 25, 2022

With updated equipment and maturing technology, the applications of augmented virtual reality (AR/VR) technologies in architecture, engineering, construction (AEC) industry are receiving increasing attention rapidly. Especially education training, an number researchers have started to implement AR/VR provide students or trainees with a visual, immersive, interactive environment. In this article, systematic review for training AEC is conducted. First all, through comprehensive analysis, 82 related studies identified from two databases, namely Scopus Web Science. Secondly, VOSviewer used analyze current status industry. Thirdly, classified into different categories according their application domains by qualitative analysis. Fourthly, after further filtering, 17 out included meta-analysis quantify actual impact AR/VR. The results indicate that there some limitations Finally, explore reasons existence limitations, summarized challenges This study also provides insights future trends

Language: Английский

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State-of-the-Art of Artificial Intelligence and Big Data Analytics Reviews in Five Different Domains: A Bibliometric Summary

Sustainability, Journal Year: 2023, Volume and Issue: 15(5), P. 4026 - 4026

Published: Feb. 22, 2023

Academicians and practitioners have recently begun to accord Artificial Intelligence (AI) Big Data Analytics (BDA) significant consideration when exploring emerging research trends in different fields. The technique of bibliometric review has been extensively applied the AI BDA literature map out existing scholarships. We summarise 711 articles on & its sub-sets published multiple fields identify academic disciplines with contributions. pulled papers from Scopus Q1 Q2 journal database between 2012 2022. returned documents journals 59 countries, averaging 17.9 citations per year. Multiple software Database Analysers were used investigate data illustrate most active scientific indicators such as authors co-authors, citations, co-citations, institutions, sources, subject areas. USA was influential nation (101 documents; 5405 citations), while China productive (204 2371 citations). institution Symbiosis International University, India (32 4.5%). results reveal a substantial increase reviews five clusters disciplines: (a) Business Management, (b) Engineering Construction, (c) Healthcare, (d) Sustainable Operations I4.0, (e) Tourism Hospitality Studies, majority which applications use cases address real-world problems field. keyword co-occurrence past analyses indicates that BDA, AI, Machine Learning, Deep NLP, Fuzzy Logic, Expert Systems will remain conspicuous areas these diverse domain Therefore, this paper summarises Business, Engineering, Operations, serves starting point for novice experienced researchers interested topics.

Language: Английский

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Quantifying Arctic oil spilling event risk by integrating an analytic network process and a fuzzy comprehensive evaluation model

Ocean & Coastal Management, Journal Year: 2022, Volume and Issue: 228, P. 106326 - 106326

Published: Aug. 17, 2022

Language: Английский

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Predicting compressive strength of high-performance concrete with high volume ground granulated blast-furnace slag replacement using boosting machine learning algorithms

Scientific Reports, Journal Year: 2022, Volume and Issue: 12(1)

Published: June 9, 2022

Predicting the compressive strength of concrete is a complicated process due to heterogeneous mixture and high variable materials. Researchers have predicted for various mixes using machine learning deep models. In this research, high-performance with volume ground granulated blast-furnace slag replacement boosting (BML) algorithms, namely, Light Gradient Boosting Machine, CatBoost Regressor, Regressor (GBR), Adaboost Extreme Boosting. these studies, BML model's performance evaluated based on prediction accuracy error rates, i.e., R2, MSE, RMSE, MAE, RMSLE, MAPE. Additionally, models were further optimised Random Search algorithms compared default hyperparameters. Comparing all 5 models, GBR model shows highest R2 0.96 lowest MAE RMSE 2.73 3.40, respectively test dataset. conclusion, are best performing predicting accuracy, modelling error.

Language: Английский

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MARCOS approach based upon cubic Fermatean fuzzy set and its application in evaluation and selecting cold chain logistics distribution center

Engineering Applications of Artificial Intelligence, Journal Year: 2022, Volume and Issue: 116, P. 105401 - 105401

Published: Sept. 16, 2022

Language: Английский

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Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

Buildings, Journal Year: 2024, Volume and Issue: 14(1), P. 220 - 220

Published: Jan. 14, 2024

In the last decade, despite rapid advancements in artificial intelligence (AI) transforming many industry practices, construction largely lags adoption. Recently, emergence and adoption of advanced large language models (LLMs) like OpenAI’s GPT, Google’s PaLM, Meta’s Llama have shown great potential sparked considerable global interest. However, current surge lacks a study investigating opportunities challenges implementing Generative AI (GenAI) sector, creating critical knowledge gap for researchers practitioners. This underlines necessity to explore prospects complexities GenAI integration. Bridging this is fundamental optimizing GenAI’s early stage within sector. Given unprecedented capabilities generate human-like content based on learning from existing content, we reflect two guiding questions: What will future bring industry? are delves into reflected perception literature, analyzes using programming-based word cloud frequency analysis, integrates authors’ opinions answer these questions. paper recommends conceptual implementation framework, provides practical recommendations, summarizes research questions, builds foundational literature foster subsequent expansion its allied architecture engineering domains.

Language: Английский

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An improved failure mode and effect analysis method for group decision-making in utility tunnels construction project risk evaluation

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 244, P. 109943 - 109943

Published: Jan. 11, 2024

Language: Английский

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Risk Factors Assessment of Smart Supply Chain in Intelligent Manufacturing Services Using DEMATEL Method With LINGUISTIC q-ROF Information

Journal of Operations Intelligence, Journal Year: 2024, Volume and Issue: 2(1), P. 129 - 152

Published: Jan. 28, 2024

With the rapid development of technological informatization, competition among enterprises is gradually transitioning from being "production-centered" to "customer-centric," making service-oriented increasingly important. In addition this, as global manufacturing advances in process intelligent (IM), there growing attention on integration and service industry, which has garnered interest numerous experts scholars field services (IMS). This article combines enterprises, nodes, consumers. Based background services, it collected risk factors within smart supply chain (SSC) that connect different nodes. These were evaluated by using a proposed linguistic q-rung orthopair fuzzy weighted averaging (Lq-ROFWA) operator combination with Decision-Making Trial Evaluation Laboratory (DEMATEL) method for aggregation operations. Finally, we obtain conclusions most influential factor affecting other inadequate identification core customer needs; important chains oriented leakage information. After analyzing relevant data, will provide some theoretical managerial implications IM enterprises.

Language: Английский

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