| Title |
Artificial intelligence for deconstruction: Current state, challenges, and opportunities |
| ID_Doc |
18870 |
| Authors |
Balogun, H; Alaka, H; Demir, E; Egwim, CN; Olu-Ajayi, R; Sulaimon, I; Oseghale, R |
| Title |
Artificial intelligence for deconstruction: Current state, challenges, and opportunities |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.autcon.2024.105641 |
| Abstract |
Artificial intelligence and its subfields, such as machine learning, robotics, optimisation, knowledge-based systems, reality capture and extended reality, have brought remarkable advancements and transformative changes to various industries, including the building deconstruction industry. Acknowledging AI's benefits for deconstruction, this paper aims to investigate AI applications within this domain. A systematic review of existing literature focused on AI applications for planning, implementation and post-implementation activities within the context of deconstruction was carried out. Furthermore, the challenges and opportunities of AI for deconstruction activities were identified and presented in this paper. By offering insights into AI's application for key deconstruction activities, this paper paves the way for realising AI's potential benefits for this sector. |
| Author Keywords |
Artificial intelligence; Deconstruction; Sustainability; Challenges; Opportunities |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001284511900001 |
| WoS Category |
Construction & Building Technology; Engineering, Civil |
| Research Area |
Construction & Building Technology; Engineering |
| PDF |
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