I Wear It Better

Trade Fashion with Friends

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Inspiration

Our inspiration for "I Wear It Better" stems from the addictive algorithms employed by popular platforms like Tinder and TikTok. Additionally, we were motivated by the increasing appeal of fast fashion trends, while also recognizing the need to reduce clothing waste. Our aim is to adapt these concepts to engage a broader audience by infusing elements of excitement and mental stimulation into the process.

What it does

"I Wear It Better" gamifies the experience of searching for fashion items, fostering interactions and trades among users that might not occur otherwise. By incentivizing users to explore new clothing options rather than discarding old ones, the platform promotes sustainable fashion practices while also providing entertainment value.

How we built it

Utilizing React Native and employing a component-based approach, we developed "I Wear It Better" despite being newcomers to the framework. Despite facing challenges with emulation and environment setup due to our limited experience in app development, we successfully created a functional app.

Challenges we ran into

Our main challenge revolved around emulation and environment setup, as our team had minimal prior knowledge of app development. However, through perseverance and problem-solving, we overcame these obstacles to deliver a working solution.

Accomplishments that we're proud of

We take pride in achieving our goal of creating a fully functional app and successfully emulating it. As first-time React Native users, this accomplishment marks a significant milestone in our journey as developers.

What we learned

Throughout the development process, we gained a basic understanding of React Native and honed our skills in state management, component creation, and overall project structure. These learnings have equipped us with valuable knowledge for future projects in app development.

What's next for I Wear It Better

Looking ahead, we plan to enhance the platform by implementing stronger algorithms such as the stable matching algorithm to improve the success rate of matches between users. Additionally, we aim to integrate AI models that analyze user preferences and interactions to provide personalized clothing recommendations, further enriching the user experience.

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