Abstract
Offsite construction (OSC) offers a sustainable approach to building, employing innovative methods to reduce waste and enhance delivery efficiency. Integrating circular economy (CE) principles into OSC can further improve its circularity
performance, fostering a more sustainable environment. More so, artificial
intelligence (AI) can accelerate this integration, augmenting CE application
capabilities in OSC. Despite the extensive literature on OSC and CE, implementing
AI to enable the integration of CE and OSC, or CE in OSC, remains underexplored.
The review aims to analyse the convergence of these domains, uncovering insights for
advancing sustainable OSC practices. This research employed scientometric and
qualitative analysis to assess 619 journal articles on AI, CE, and OSC literature.
Science mapping quantitative literature review and visualisation techniques were used
to investigate the data, determining frequently discussed concepts. The evaluation
details AI’s integration of CE and OSC, summarising primary applications and
limitations. A framework highlighting AI’s potential for promoting CE practices in
OSC was developed. The findings highlight AI-machine learning models that
overcome the synergy barriers of CE and OSC and serve as a benchmark for future
studies
performance, fostering a more sustainable environment. More so, artificial
intelligence (AI) can accelerate this integration, augmenting CE application
capabilities in OSC. Despite the extensive literature on OSC and CE, implementing
AI to enable the integration of CE and OSC, or CE in OSC, remains underexplored.
The review aims to analyse the convergence of these domains, uncovering insights for
advancing sustainable OSC practices. This research employed scientometric and
qualitative analysis to assess 619 journal articles on AI, CE, and OSC literature.
Science mapping quantitative literature review and visualisation techniques were used
to investigate the data, determining frequently discussed concepts. The evaluation
details AI’s integration of CE and OSC, summarising primary applications and
limitations. A framework highlighting AI’s potential for promoting CE practices in
OSC was developed. The findings highlight AI-machine learning models that
overcome the synergy barriers of CE and OSC and serve as a benchmark for future
studies
| Original language | English |
|---|---|
| Title of host publication | Looking Back to Move Forward |
| Subtitle of host publication | 40th Annual Conference and General Meeting |
| Pages | 477-486 |
| Number of pages | 10 |
| Publication status | Published - 4 Sept 2024 |
| Externally published | Yes |
| Event | ARCOM Conference 2024: Looking Back to Move Forward - London South Bank University, London, United Kingdom Duration: 2 Sept 2024 → 4 Sept 2024 |
Academic conference
| Academic conference | ARCOM Conference 2024: Looking Back to Move Forward |
|---|---|
| Country/Territory | United Kingdom |
| City | London |
| Period | 2/09/24 → 4/09/24 |
Keywords
- artificial intelligence, circular economy, offsite construction