Core Functionality
- AR Outfit Builder: Users can drag & drop clothing items onto a live camera feed of themselves or a mannequin to visualize looks before purchasing.
- Virtual Wardrobe & Mix‑and‑Match: Store digital copies of purchased clothes; AI suggests outfit combinations for upcoming events (classes, parties).
- Social Style Challenges: Weekly themes where students upload AR selfies; peers vote and earn points redeemable for discounts or merch.
- Sustainability Tracker: Calculates carbon footprint of each outfit based on material data and recommends eco‑friendly swaps.
Problem It Solves
Students often spend time deciding what to wear, struggle with limited campus budgets, and lack a quick way to try out outfits before buying. The app reduces trial‑and‑error, promotes sustainable fashion choices, and builds a community around style experimentation.
Technical Requirements
- ARKit / ARCore for real‑time rendering of garments on live video.
- Computer Vision & Pose Estimation (e.g., MediaPipe) to align clothes accurately on user body.
- Backend Cloud Services (Firebase, AWS Amplify) for authentication, storage, and AI recommendation pipelines.
- Machine Learning Models for style suggestion and sustainability scoring.
Monetization Strategy
- Freemium Model: Basic AR try‑on free; premium subscription unlocks advanced filters, exclusive designer items, and offline wardrobe management.
- Affiliate Partnerships: Earn commissions on purchases made through in‑app links to partner e‑retailers.
- Sponsored Style Challenges: Brands sponsor challenges offering branded apparel for participants.
- Data Insights: Aggregated anonymized trend data sold to fashion brands (compliant with GDPR/FERPA).
Implementation Approach
- Phase 1 – MVP
- Build core AR try‑on with a limited catalog of generic garments.
- Implement user authentication and basic profile.
- Phase 2 – Personalization & AI
- Integrate pose estimation for accurate garment fitting.
- Deploy recommendation engine using collaborative filtering on student wardrobe data.
- Phase 3 – Social Layer
- Add photo upload, voting, and points system.
- Enable sharing to Instagram/TikTok with AR filters.
- Phase 4 – Sustainability & Partnerships
- Integrate material database; calculate footprint.
- Onboard affiliate partners and launch sponsored challenges.
- Launch & Iterate
- Beta test on a university campus, gather feedback, optimize UI/UX.
Potential Challenges
- Accurate Garment Fit in AR: Body shape variation can cause misalignment. Solution: Use adaptive cloth simulation and allow users to adjust fit manually.
- Privacy & Data Compliance: Handling student images requires strict controls. Solution: Store only encrypted, anonymized data; obtain explicit consent; comply with FERPA.
Future Expansion
- Virtual Events & Runways: Host live AR fashion shows where students model virtual outfits.
- Cross‑Platform Integration: Sync wardrobes across campus apps (calendar, dorm services).
- Augmented Shopping Assistants: Voice‑controlled style guides in university bookstores.
- Marketplace for Custom Prints: Allow students to upload designs and print on demand.