Clothest-Match

Tinder for clothes - match users with clothes they truly like while giving brands valuable insights into improving customer experience, and provide insightful data to brands.

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Inspiration

Online Shopping is always a time sink - we hate having to trawl through online shops for hours and hours just to find one item that suits us, especially in the era of AI-designed drop-shipped clothes. We also love scrolling and swiping, as many people of this generation do.

What it does

So, we decided to combine our love of swiping with a very real problem that many people face, and chose to work on a project that matches users with clothes that they love, finding a very real use case for businesses along the way

How we built it

For our frontend, we implement a standalone cross platform application using Flutter. For the backend, we use Spring boot, spring data JPA, mysql and spring session to make a RESTful API, with the backend containerised and deployed. Login is handled with session tokens, so users do not even need to log in to use the service if they do not wish to ie. tiktok style login

Challenges we ran into

The main challenge we ran into was in the usage of a newer framework. We had to learn an entirely new way to do things, which was fun.

Accomplishments that we're proud of

We're proud of the amount of things we got done in the short period of this hackathon - a standalone full stack mobile app, and a RESTful API. Some accomplishments of note - implementing an infinite queue in the swiping, and the polished look of the project.

What we learned

We learnt a lot about using the flutter framework, merge conflicts, communication between multiple people working on smaller parts of a larger project and time management. Also ->

-Front-end development using flutter

-Android App pipeline

-Springboot, Rest API and Android app communication

-MySQL database management

-Figma prototyping UI design

What's next for Clothest-Match

-The ability to bid on secondhand items, not just from catalogue!

-More accurate user preference prediction algorithm

-AI price prediction, AI user goods preference prediction, AB price testing

-Collaborate on logistics, and other aspects of the fashion industry

-Adding distance filters

-Expanding the API into a full dashboard for businesses to use

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