Inspiration
We got inspired by our friend’s smart fridge, which can detect what food is inside and generate meal plans based on the available ingredients. This idea sparked our vision to create a similar system for clothing. Instead of meal suggestions, our app identifies clothes in your closet and helps you build personalised outfits effortlessly.
What it does
Closet Cloud is a smart virtual app that helps users to organise, visualise, and style their clothes effortlessly. It uses image recognition technology to detect which clothing items are in your closet and automatically categorises them by type, colour, and style. The app can then generate outfit combinations based on factors like occasion, weather, and personal preferences. Users can also upload a photo of themselves to virtually “try on” different outfits and see how they would look in real life. A built-in recommendation system suggests new ways to style existing pieces or highlights unworn items to encourage diverse fashion choices. You can save your favourite looks, plan outfits for future events, and track what you wear most often. Overall, the app transforms your wardrobe into an interactive, AI-powered styling assistant that makes fashion smarter, more fun, and eco-friendly.
How we built it
We built our project using Figma to design and prototype the entire app interface. Figma allowed us to create interactive screens for each feature, including the smart closet dashboard, outfit generator, and virtual try-on page, with smooth navigation and a cohesive visual theme. We used Figma’s AI design features to generate clean layouts, add icons, and simulate how users would interact with the app. Each page was carefully linked to demonstrate the full user flow, from uploading clothing photos to viewing outfit recommendations.
Challenges we ran into
One of the biggest challenges we ran into was dealing with technical errors and limitations while trying to make our app function the way we envisioned. Some features didn’t work properly at first, and certain design elements or interactions couldn’t be implemented exactly as planned. We had to constantly adjust our ideas, and modify parts of the project to make everything flow smoothly. It took a lot of trial and error, but through collaboration and problem-solving, we managed to overcome those issues.
Accomplishments that we're proud of
We’re really proud of how much we accomplished, especially since it was our first time using Figma. Learning a new design tool and figuring out how to bring our ideas to life was a big step for us. It was so rewarding to see our app come together visually and function the way we imagined. We’re also proud that we were able to fix the many errors we faced along the way through persistence and teamwork.
What we learned
We learned a lot throughout this project, especially about how to use Figma to design and prototype an app from scratch. It taught us how to think like designers; organising layouts, connecting pages, and creating smooth user interactions. We also learned the importance of patience when things don’t go as planned. Whenever we got stuck on an error, we realised that taking a short break or walk helped us come back with a clearer mindset to solve the problem. Most importantly, we learned that staying calm and being positive is key to overcoming challenges and keeping the creative process enjoyable.
What's next for Closet Cloud
What’s next for Closet Cloud is turning our prototype into a fully functional app with even smarter features. We plan to integrate bar code or RFID scanning so users can quickly add clothing items by simply scanning their tags, similar to how retail stores track inventory. This would make detecting and organising clothes even faster and more accurate. We also want to connect the app to real wardrobe data and potentially use AI outfit recommendations that adapt to a user’s personal style, weather, and upcoming events. Our long-term goal is to make Closet Cloud a complete, interactive fashion assistant that bridges technology, convenience, and creativity.
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