Artificial intelligence and smart vision for building and construction 4.0 : machine and deep learning methods and applications / Shanaka Kristombu Baduge [and six others].
Material type:
ArticlePublication details: Amsterdam : Elsevier, 2022. Subject(s): Artificial Intelligence (AI) | Machine Learning (ML) | Deep Learning (DL) | Automation | Offsite manufacturing and automation | Internet of Things (IoT) | Building information modelling | Smart Vision (SV) | Cloud computing | Building and Construction Industry (4.0) | Artificial Intelligence (AI) in Building and Construction Industry (4.0) | Artificial Intelligence (AI) in Architectural design | Structural analysis and design | Convolution Neural Network (CNN) | Generative Adversarial Network (GAN) | Artificial Neural Network (ANN) | Variational Autoencoder (VAE) | Recurrent Neural Network (RNN) | Architectural design and visualization | Design generation (for CAD) | Design evaluation (for CAE) | Construction management | Smart building operation and health monitoring | Energy and emission management | Climate controlling systems | Structural Health Monitoring (SHM) and durability | Research | Engineering -- Research | Journal articles (Open access)Online resources: Click here to access online
In:
Automation in Construction , volume 141, pages 1-26 (September 2022).Summary: 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.
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Includes bibliographical references.
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.
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