Closet Go: A Data-Driven Digital Closet System to Improve the Dressing Experience
Abstract
This thesis aims to introduce a system design that supports the user experience of outfit selection, storage, and matching. Clothes are indispensable items in daily human life. Purchasing one's wardrobe has become more affordable. This has allowed people to focus on purchasing more fashionable clothes. Garment shopping has even become a type of social and leisure activity. With the development of internet technology, shopping methods have changed dramatically. However, these seemingly convenient shopping methods also bring unavoidable problems, such as an inability to understand apparel companies' different size standards and the challenge of seeing the details of materials. On the other side, while overemphasizing the convenience of the shopping process, online companies have ignored people's clothes-wearing experience that is the most enjoyable and valuable for customers. This paper introduces an IoT (Internet of Things) design: "Closet Go" including a mobile application and a clip-able camera. "Closet Go" aims to improve customers' daily outfit selection experience by digitalizing their closets and conducting data analysis of customized dressing habits. In this thesis, I present the entire design process: user research, Ideation, UI/UX design, product development, and evaluation. In the research section, potential users were recruited for interviews to discover the current problems in acquiring, selecting, and matching outfits in daily life. The design process section introduces the design development progress and results via user flow, experience map, prototype, and user interface. Finally, the thesis concludes with a heuristics evaluation section that tests the design's usability and experience to refine the project.
Degree
M.A.
Advisors
Qian, Purdue University.
Subject Area
Aesthetics|Design|Commerce-Business|Computer science|Fashion|Industrial engineering|Information Technology|Marketing|Textile Research|Web Studies
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