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Scientific Article details

Title Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications
ID_Doc 29211
Authors Baduge, SK; Thilakarathna, S; Perera, JS; Arashpour, M; Sharafi, P; Teodosio, B; Shringi, A; Mendis, P
Title Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications
Year 2022
Published
DOI 10.1016/j.autcon.2022.104440
Abstract This article presents a state-of-the-art review of the applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in building and construction industry 4.0 in the facets of architectural design and visualization; material design and optimization; structural design and analysis; offsite manufacturing and automation; construction management, progress monitoring, and safety; smart operation, building management and health monitoring; and durability, life cycle analysis, and circular economy. This paper presents a unique perspective on applications of AI/DL/ML in these domains for the complete building lifecycle, from conceptual stage, design stage, construction stage, operational and maintenance stage until the end of life. Furthermore, data collection strategies using smart vision and sensors, data cleaning methods (post-processing), data storage for developing these models are discussed, and the challenges in model development and strategies to overcome these challenges are elaborated. Future trends in these domains and possible research avenues are also presented.
Author Keywords Artificial intelligence; Machine learning; Deep learning; Automation; Internet of things; Building information modelling; Smart vision; Convolution neural network; Generative adversarial network; Artificial neural network
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000819461600001
WoS Category Construction & Building Technology; Engineering, Civil
Research Area Construction & Building Technology; Engineering
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