Closet AI Pátákò Ìṣòwò Àtúntà láti ọwọ́ Ruoxuan Pan, Junjie Tang and Huixiang Chen

Closet AI Pátákò Ìṣòwò Àtúntà láti ọwọ́ Ruoxuan Pan, Junjie Tang and Huixiang Chen jẹ́ aṣẹ́gun olókìkí púpọ̀ ti 2026 Àmì-ẹ̀yẹ Irin A' Design Award nínú Ẹ̀ka Ìdíje Àpẹẹrẹ Ìmọ̀-ẹ̀rọ Alágbèéká, Ohun-èlò Fóònù àti Sọ́fítíwéà.

IrinAlágbèéká· 2026

Closet AI Pátákò Ìṣòwò Àtúntà

látọ̀wọ́ Ruoxuan Pan, Junjie Tang and Huixiang Chen

Aṣẹ́gun Àmì-ẹ̀yẹ Irin A' Design Award nínú Ẹ̀ka Alágbèéká

5,797

Aṣẹ́gun Àmì Ẹ̀yẹ Tí a Jẹ́rìísí

Jẹ́rìísí Ipò Àmì Ẹ̀yẹ fún #182338

Wo ní A' Design Award Ìwé Ìròyìn Àmì Ẹ̀yẹ

Àwọ̀

Àpẹrẹ Náà

Nípa Closet AI Pátákò Ìṣòwò Àtúntà

Closet AI jẹ́ pátákò àtúntà lórí ẹ̀rọ alágbèéká fún aṣọ tí a ti lò tẹ́lẹ̀. Àwọn olùmúlò máa ń gbé àwòrán aṣọ sórí ẹ̀rọ, àpò-ìṣe náà yóò sì ṣẹ̀dá àwọn ẹ̀ka, àpèjúwe àti iye owó tí a dábàá ní ìbámu pẹ̀lú dátà àtúntà. Nígbà ìjíròrò owó, ètò náà máa ń ṣe àkọsílẹ̀ àwọn ìdábàá ìdáhùn tí àwọn olùmúlò lè ṣàtúnṣe tàbí fọwọ́ sí, kí ìpinnu ìkẹyìn lè wà lọ́wọ́ olùtà. Ètò ẹ̀bùn kan máa ń tọpasẹ̀ ìlọsíwájú nípasẹ̀ àwọn iṣẹ́-àyànfúnni, àmì-ẹ̀yẹ àti àwọn ibi-àfojúsùn. A ṣe àgbékalẹ̀ pátákò náà nípasẹ̀ ìwádìí lórí ìwà àtúntà. Ète rẹ̀ ni láti dín àkókò àti ìsapá tí ó ń kó ìrẹ̀wẹ̀sì bá ìkópa nínú aṣíkí aṣọ alátúnlò kù.

Ìdánimọ̀ Náà

Nípa Àmì-ẹ̀yẹ Irin A' Design Award

Closet AI Pátákò Ìṣòwò Àtúntà jẹ́ olùborí Àmì-ẹ̀yẹ Irin A' Design Award, ìdánimọ̀ olókìkí tí a fún àwọn àwòṣe tó dára tí wọ́n pàdé àwọn ohun tí iṣẹ́ àti ilé-iṣẹ́ nílò tí a retí láti ọ̀dọ̀ àwọn ẹ̀dá tí a ṣàwòṣe dáradára. Àwọn olùborí Irin ń fi ìjáfáfá ńlá, ìmọ̀ pàtó gíga, òye ògbóǹtarìgì àti agbára ìṣẹ̀dá àwọn olùṣẹ̀dá wọn hàn. A retí pé Closet AI Pátákò Ìṣòwò Àtúntà yóò jẹ́ ẹ̀dá tí a kà sí gidigidi, tí a gbóríyìn fún tí a sì nífẹ̀ẹ́, tó wúlò tó sì ní ìmúṣẹ̀dá tuntun. Àwòṣe tó borí Àmì-ẹ̀yẹ Irin A' Design Award yìí ń kó àwọn ọ̀nà tó dára jùlọ ilé-iṣẹ́ jọ, ó sì ní àwọn ànímọ́ ìmọ̀-ẹ̀rọ tó péye tí a so mọ́ ìmọ̀ ṣíṣe àti ẹ̀bùn. A bọ̀wọ̀ fún Closet AI Pátákò Ìṣòwò Àtúntà nítorí ìfọ̀kànbalẹ̀ rẹ̀, a sì ṣàwòṣe rẹ̀ láti pèsè ìmúdára ìgbésí ayé tó ń ran ayé lọ́wọ́ láti di ibi tó dára jù.

Lẹ́yìn Àpẹrẹ Náà

Àkójọ Ìròyìn

Àwọn ẹ̀tọ́, àwọn ọmọ ẹgbẹ́ àti àlàyé ìmọ̀ ẹ̀rọ tí olùṣàpẹrẹ pèsè.

Àwọn Ohun Àkànṣe: Closet AI is an AI powered resale platform designed to remove friction from circular fashion. It automates listing creation, pricing suggestions and negotiation support, transforming second hand selling into a streamlined experience. By integrating intelligent automation with a reward system that tracks impact and milestones, Closet AI reduces emotional barriers and encourages sustainable participation, making fashion circulation measurable and efficient.
Ìwọ̀n àti Àpò: Closet AI is a mobile first digital platform prototyped in Figma at 402 x 874 pixels aligned with iPhone interface standards. The system follows a modular and scalable architecture supporting real time feedback and adaptive interaction flows. A structured design system ensures visual consistency accessibility compliance and responsive layout behavior across future multi platform extensions.
Àwọn Àkọlé: AI powered resale platform, UX/UI design, circular fashion system, sustainable commerce design, intelligent negotiation support, automated listing generation, user centered interaction design, behavioral incentive system, mobile marketplace experience, fashion sustainability innovation
Ìmọ̀-ẹ̀rọ Ìṣelọ́pọ̀: Closet AI was developed through a human centered design process informed by user research and resale behavior analysis. Insights into pricing uncertainty and negotiation stress shaped the interaction framework. Computer vision, natural language generation and data driven recommendations were integrated as supportive technologies. Iterative prototyping refined the system into an assisted workflow that reduces cognitive load while preserving user agency.
Ìpèníjà Àpèsè: The major challenge was balancing automation with user autonomy. Fully automated systems risk removing agency, while manual systems maintain friction. Closet AI introduces assisted intelligence, where AI drafts and recommends actions but users retain final control. Another challenge was integrating sustainability incentives without overwhelming users. The solution implements subtle impact indicators and milestone badges that reinforce behavior without creating gamified complexity.
Ìwádìí: Type of Research: Qualitative behavioral research and workflow analysis. Research Objectives: To identify barriers preventing users from participating in clothing resale despite sustainability awareness. Methodology: User interviews journey mapping and competitive benchmarking. Data Collection: Structured interviews usability testing and prototyping. Participants: Gen Z and Millennial users. Results: Identified negotiation fatigue and listing complexity as key friction points. Insights and Impact: Automation reduces participation barriers and supports circular fashion adoption.
Ìmísí: Closet AI was inspired by the gap between sustainable intention and practical behavior. While many Gen Z and Millennial users want to reduce waste, resale platforms often demand time and effort. Listing creation, price negotiation and cross platform management introduce friction that discourages participation. The project explores how artificial intelligence can reduce this friction and connect resale with meaningful environmental impact.
Àkókò Iṣẹ́ Àkànṣe: The project began in Dec 2025 in Austin and is currently in advanced prototype development.
Ìlànà Ìṣiṣẹ́: Users upload clothing images to generate automatic categories, descriptions, and smart pricing suggestions based on resale data. They publish listings, track engagement insights, and receive recommendations such as price adjustments or repost timing. Users complete quests, earn badges, and unlock milestones as they list, optimize, and close deals. During negotiations, AI drafts reply suggestions that users can edit or approve, keeping full control.
Àwọn Ọmọ Ẹgbẹ́: Ruoxuan Pan
Junjie Tang
Huixiang Chen
Ìfọwọ́sí Àwòrán: Main Image: Creator Junjie Tang, Huixiang Chen, Closet AI Home page and Swipe flow, 2026
Image #1: Creator Huixiang Chen, Item Scan, Item Swipe and Select, Item Editing, and Item Posting page, 2026
Image #2: Creator Ruoxuan Pan, AI listing and message assistant flow, 2026
Image #3: Creator Junjie Tang, reward and badge pages, 2026
Image #4: Creator Ruoxuan Pan, Huixiang Chen, Junjie Tang, Closet AI interface overview, 2026