Artificial Intelligence Enabling Sustainable Construction: A Systematic Review-Reference-Cited by-同舟云学术

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Artificial Intelligence Enabling Sustainable Construction: A Systematic Review

Published:2024-03-18 Issue: Volume:11 Page:600-609
ISSN:
Container-title:Construction Research Congress 2024
language:
Short-container-title:

Author:

Ramachandra Vaishnavi Jagalur¹¹²³,Mahaveen Naila¹¹²³,Banerjee Siddharth¹¹²³,Ghannad Pedram¹¹²³

Affiliation:

1. Graduate Student, Dept. of Civil Engineering and Construction, Bradley Univ.

2. Assistant Professor, Dept. of Civil Engineering, California State Polytechnic Univ., Pomona. ORCID: .

3. Assistant Professor, Dept. of Civil Engineering and Construction, Bradley Univ.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485279.060

Reference38 articles.

1. Predictive Maintenance Planning for Industry 4.0 Using Machine Learning for Sustainable Manufacturing

2. Building Information Modelling Diffusion Research in Developing Countries: A User Meta-Model Approach;Adekunle S. A.;Buildings,2021

3. Agostinelli S. 2021. “Actionable Framework for City Digital Twin-Enabled Predictive Maintenance and Security Management Systems.” Building Information Modelling (BIM) in Design Construction and Operations IV 205–223.

4. Artificial Neural Networks for Sustainable Development of the Construction Industry

5. Al Braiki A. A. Taha H. Al Rubaiey H. Al Naabi Y. Al Lawati A. Al Subhi Q. Al Hinai and M. Radwan. 2022. “Improving Drilling Performance Using Drilling Efficiency Optimization (DEO).” Abu Dhabi International Petroleum Exhibition and Conference. Abu Dhabi. doi:10.2118/211768-MS.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The Potential of Using Artificial Intelligence (AI) to Analyse the Impact of Construction Industry on the Carbon Footprint;Mobile Networks and Applications;2024-07-24

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