| Title |
Adopting Artificial Intelligence for enhancing the implementation of systemic circularity in the construction industry: A critical review |
| ID_Doc |
22376 |
| Authors |
Oluleye, BI; Chan, DWM; Antwi-Afari, P |
| Title |
Adopting Artificial Intelligence for enhancing the implementation of systemic circularity in the construction industry: A critical review |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.spc.2022.12.002 |
| Abstract |
Data-driven technology such as Artificial Intelligence is considered an essential enabler of circular economy (CE) in the building construction industry (BCI). As both AI and CE applications are emerging areas in the BCI, there exists little systematic guidance on how AI can be applied to capture the full potential of systemic circularity along the building product lifecycle. To fill this gap, this study provides an extensive systematic review of scien-tific research advancement in AI and CE in the BCI. AI algorithms for enabling systemic circularity in the BCI were discussed alongside their respective Strengths, Weaknesses, Threats, and Opportunities (SWOT) analysis con-cerning CE solutions. Further, thirteen application areas of the AI models were illustrated and summarised using a tree diagram. Among the application areas include circular materials selection, design for disassembly, pre-demolition auditing, demolition waste sorting, materials strength prediction, technical and economic circu-larity of materials, operation of circular business model, onsite waste recycling, and reverse logistics. In addition, the profound challenges of applying AI in enabling CE implementation in BCI were identified and their potential solutions were highlighted. A holistic framework integrating the AI models and their application domains along the building product lifecycle was developed. Future research directions including a deep reinforcement learning (DRL) adaptive control system for circularity, AI in 3D printing of circular materials, optimisation of management infrastructure for circular products, optimisation of circular business model and reverse logistics are highlighted. The findings have delineated the core application domains of AI in enabling CE adoption along the building lifecycle and provided insightful future research needs that could promote digital systemic circularity in BCI.(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved. |
| Author Keywords |
Artificial Intelligence; Machine learning; Circular economy; Building life cycle; Building construction industry; Waste management |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000906249600001 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
https://doi.org/10.1016/j.spc.2022.12.002
|