| id |
caadria2021_088 |
| authors |
Batalle Garcia, Anna, Cebeci, Irem Yagmur, Vargas Calvo, Roberto and Gordon, Matthew |
| year |
2021 |
| title |
Material (data) Intelligence - Towards a Circular Building Environment |
| source |
A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 361-370 |
| doi |
https://doi.org/10.52842/conf.caadria.2021.1.361
|
| summary |
The integration of repurposed material in new construction products generates resiliency strategies that diminish the dependency on raw resources and reduce the CO2 emissions produced by their extraction, transportation, and manufacturing. This research emphasizes the need to expand preliminary data collation from pre-demolition sites to inform early design decisions. Material (data) Intelligence investigates how the merging of artificial intelligence and data analysis could have a crucial impact on achieving widespread material reuse. The first step consists of automating the process of detecting materials and construction elements from pre-demolition sites through drone photography and computer vision. The second part of the research links the resulting database with a computational design tool that can be integrated into construction software. This paper strengthens the potential of circular material flows in a digital paradigm and exposes the capability for constructing big data sets of reusable materials, digitally available, for sharing and organizing material harvesting. |
| keywords |
computer vision; material database; automation; reclaimed material; digitalization |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (16,705,246 bytes) |
| references |
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