Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications

Baduge, Shanaka Kristombu, Thilakarathna, Sadeep, Perera, Jude Shalitha, Arashpour, Mehrdad ORCID: 0000-0003-4148-3160, Sharafi, Pejman, Teodosio, Bertrand ORCID: 0000-0002-3909-4054, Shringi, Ankit and Mendis, Priyan ORCID: 0000-0003-4068-8201 (2022) Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications. Automation in Construction, 141. ISSN 0926-5805

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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Item type Article
URI https://vuir.vu.edu.au/id/eprint/47168
DOI 10.1016/j.autcon.2022.104440
Official URL https://www.sciencedirect.com/science/article/pii/...
Subjects Current > FOR (2020) Classification > 4602 Artificial intelligence
Current > Division/Research > College of Science and Engineering
Keywords AI, artificial intelligence, deep learning, machine learning, robotics, data collection
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