Baurley, Sharon, Ozden Yenigun, Elif, Hatfield, Lissy, Jansen, Chipp, Ma, Zengtao and Tuo, Boyuan, 2023, Show, Exhibition or Event, AiLoupe at Dubai Design Week 2023
Abstract or Description: | AiLoupe is the first in the suite of AI-driven design tools developed to benefit both the designer and consumer as part of research into how humans experience materials. AiLoupe takes inspiration from the Loupe, a traditional tool used to conduct fabric analysis, translating this tacit knowledge into a digital tool. AiLoupe uses a camera to recognise different materials and provide information about them. This includes information about the material, its sensory properties, composition, supply chain and volume of water used during the manufacturing process. By making this information readily available, AiLoupe aims to reduce waste and educate on sustainable practices throughout the supply chain. The tool will be useful for manufacturers, suppliers, designers and the end consumer. Intelligent Design System for Innovation is part of AiDLab, a research collaboration between Hong Kong Polytechnic University and the Royal College of Art. This research is funded by the Laboratory for Artificial Intelligence in Design under the InnoHK Research Clusters, Hong Kong Special Administrative Region Government. |
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Events: | Title Location Dates Type Dubai Design Week 2023 Dubai, UAE 2023-11-07 - 2023-11-12 UNSPECIFIED |
Official URL: | https://web.archive.org/web/20231109122332/https:/... |
Subjects: | Other > Mathematical and Computer Sciences > G400 Computer Science Other > Mathematical and Computer Sciences > G700 Artificial Intelligence Creative Arts and Design > W200 Design studies > W230 Clothing/Fashion Design Creative Arts and Design > W200 Design studies > W230 Clothing/Fashion Design > W231 Textile Design |
School or Centre: | Other |
Funders: | Funded by the Laboratory for Artificial Intelligence in Design under the InnoHK Research Clusters, Hong Kong Special Administrative Region Government |
Date Deposited: | 02 Sep 2024 10:39 |
Last Modified: | 04 Jun 2025 22:12 |
URI: | https://researchonline.rca.ac.uk/id/eprint/5962 |
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