A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Artificial intelligence in green building
Abstract The Architecture, Engineering and Construction (AEC) sector faces severe sustainability and efficiency challenges. The application of artificial intelligence in green building (AI-in-GB) is an effective solution to enhance the sustainability and efficiency of the sector. While studies have been conducted in the AI-in-GB domain, an in-depth study on the state-of-the-art of AI-in-GB research is hitherto lacking. To provide a better understanding of this underexplored area, this study was initiated via a bibliometric-systematic analysis method. The study aims to reveal the synthesis between AI and GB, as well as to highlight research trends along with knowledge gaps that may be tackled in future AI-in-GB research. A quantitative bibliometric analysis was conducted to objectively identify the major research hotspots, trends, knowledge gaps and future research needs based on 383 research publications identified from Scopus. A further qualitative systematic analysis was also conducted on 76 screened research publications on AI-in-GB. Through this mixed-methods systematic review, knowledge gaps were identified, and future research directions of AI-in-GB were proposed as follows: digital twins and AI of things; blockchain; robotics and 4D printing; and legal, ethical, and moral responsibilities of AI-in-GB. This study adds to the GB knowledge domain by synthesizing the state-of-the-art of AI-in-GB and revealing the research needs in this field to enhance the sustainability and efficiency of the AEC sector.
Graphical abstract Display Omitted
Highlights AI-in-GB promotes knowledge-discovery, intelligent optimization, and augmenting or automating decision-making process. Major strengths of AI-in-GB include increased efficiency, cost-and-time savings, reliability, and improved accuracy. AI-in-GB has significant scope for further research. Key future research directions include digital twins and AIoT; blockchain; robotics and 4D printing.
Artificial intelligence in green building
Abstract The Architecture, Engineering and Construction (AEC) sector faces severe sustainability and efficiency challenges. The application of artificial intelligence in green building (AI-in-GB) is an effective solution to enhance the sustainability and efficiency of the sector. While studies have been conducted in the AI-in-GB domain, an in-depth study on the state-of-the-art of AI-in-GB research is hitherto lacking. To provide a better understanding of this underexplored area, this study was initiated via a bibliometric-systematic analysis method. The study aims to reveal the synthesis between AI and GB, as well as to highlight research trends along with knowledge gaps that may be tackled in future AI-in-GB research. A quantitative bibliometric analysis was conducted to objectively identify the major research hotspots, trends, knowledge gaps and future research needs based on 383 research publications identified from Scopus. A further qualitative systematic analysis was also conducted on 76 screened research publications on AI-in-GB. Through this mixed-methods systematic review, knowledge gaps were identified, and future research directions of AI-in-GB were proposed as follows: digital twins and AI of things; blockchain; robotics and 4D printing; and legal, ethical, and moral responsibilities of AI-in-GB. This study adds to the GB knowledge domain by synthesizing the state-of-the-art of AI-in-GB and revealing the research needs in this field to enhance the sustainability and efficiency of the AEC sector.
Graphical abstract Display Omitted
Highlights AI-in-GB promotes knowledge-discovery, intelligent optimization, and augmenting or automating decision-making process. Major strengths of AI-in-GB include increased efficiency, cost-and-time savings, reliability, and improved accuracy. AI-in-GB has significant scope for further research. Key future research directions include digital twins and AIoT; blockchain; robotics and 4D printing.
Artificial intelligence in green building
Debrah, Caleb (author) / Chan, Albert P.C. (author) / Darko, Amos (author)
2022-02-26
Article (Journal)
Electronic Resource
English
Risk Assessment of Green Intelligent Building Based on Artificial Intelligence
| DOAJ | 2022
Artificial intelligence in building
| Taylor & Francis Verlag | 1988