## Inspiration

Globally, over 92 million tons of textile waste are generated annually, contributing to overflowing landfills and environmental degradation. What's more, the fashion industry is responsible for 10% of global carbon emissions, with fast fashion being a significant contributor due to its rapid production cycles and disposal of unsold items. The inspiration behind our project, ReStyle, is rooted in the urgent need to address the environmental impact of fast fashion. Witnessing the alarming levels of clothing waste and carbon emissions prompted our team to develop a solution that empowers individuals to make sustainable choices effortlessly. We believe in reshaping the future of fashion by promoting a circular economy and encouraging responsible consumer behaviour.

## What it does

ReStyle is a revolutionary platform that leverages AI matching to transform how people buy and sell pre-loved clothing items. The platform simplifies the selling process for users, incentivizing them to resell rather than contribute to the environmental crisis of clothing ending up in landfills. Our advanced AI matching algorithm analyzes user preferences, creating tailored recommendations for buyers and ensuring a seamless connection between sellers and buyers.

## How we built it

We used React Native and Expo to build the front end, creating different screens and components for the clothing matching, camera, and user profile functionality. The backend functionality was made possible using Firebase and the OpenAI API. Each user's style preferences are saved in a Firebase Realtime Database, as are the style descriptions for each piece of clothing, and when a user takes a picture of a piece of clothing, the OpenAI API is called to generate a description for that piece of clothing, and this description is saved to the DB. When the user is on the home page, they will see the top pieces of clothing that match with their style, retrieved from the DB and the matches generated using the OpenAI API.

## Challenges we ran into

* Our entire team was new to the technologies we utilized.
* This included React Native, Expo, Firebase, OpenAI.

## Accomplishments that we're proud of

* Efficient and even work distribution between all team members
* A visually aesthetic and accurate and working application!

## What we learned

* React Native
* Expo
* Firebase
* OpenAI

## What's next for ReStyle

Continuously refine our AI matching algorithm, incorporating machine learning advancements to provide even more accurate and personalized recommendations for users, enabling users to save clothing that they are interested in.
## Inspiration

Today’s technological advances have resulted in many consumers having to increasingly rely on Web-based banking and financial systems. Consumers often overlooked as we make this transition include the visually impaired and/or the less tech-savvy populations (e.g. elderly). It is critical that we guarantee that systems give equal and complete access to everyone, and none are disregarded. Some may point out that paper billing is an option, but on top of not being eco-friendly, paper billing is not an ideal way of getting the latest information about your records on the go.

We combine the convenience and efficiency of mobile/web applications with the ease of paper billing. **One button is all you need in a clean, user-friendly interface.**

## What *Bank Yeller* Does

Our application allows the user to voice chat with an AI (created using Dasha AI) to get their latest bank account information and be able to pay their bills vocally.

Users can ask about their latest transactions to find out how much they spent at each location, and they can ask about their latest bank statements to find out when and how much is due, as well as have the option to pay them off!

## How We Built *Bank Yeller*

* We used existing Dasha AI repositories as inspiration and guides to create our own personalized AI that was geared to our particular use case.
* We created and deployed an SQL Database to Google Cloud Platform to mimic a bank’s database and demonstrate how this would work in everyday life.
* We used Javascript to set up our Dasha.AI interactions as well as connect to our SQL Database and run queries.
* We used Figma to construct prototypes of the web and mobile based apps.

## Challenges We Ran Into

Using Dasha AI had its own learning curve, but the Dasha AI team was amazing and provided us with numerous resources and support throughout the creation of our project! (Special shoutout to Arthur Grishkevich and Andrey Turtsev at Dasha AI for putting up with Joud’s endless questions.)

Having not had much experience with async functions, we also struggled with dealing with them and figuring out how to use them when performing queries. We ended up watching several YouTube videos to understand the concepts and help us approach our problem. We were exposed to several new platforms this weekend, each with its own challenges, which only pushed us to work harder and learn more.

## Accomplishments We're Proud of

One of the accomplishments that we are proud of is the implementation of our Dasha AI accessing and verifying information from our SQL Database stored in Google Cloud. We are also proud that we were able to divide our time well this weekend to give us time to create a project we really care about and enjoyed creating as well as time to meet new people and learn about some very cool concepts! In our past hackathon we created an application to support local businesses in London, and we are proud to continue in this path of improving lives through the targeting of (often) overlooked populations.

## What We Learned

Each of us had skills that the other had not used before, so we were able to teach each other new concepts and new ways of approaching ideas! The Hack Western workshops also proved to be excellent learning resources.

## What's Next for *Bank Yeller*

Expanding! Having it available as a phone application where users can press anywhere on the screen (shown in Figma mockups) to launch Dasha. There, they will be able to perform all the aforementioned actions, and possibly some additional features! Taking visual impairments into note, we would add clear, large captions that indicate what is being said.

* for instructions on how to run Bank Yeller, please check out our README file :))
## Inspiration

we were inspired by angry birds

## What it does

plays an educational game

## How we built it

not sleeping

## Challenges we ran into

we spent 4 hours trying to get unity collaboration to work and just gave up and used git

## Accomplishments that we're proud of

it works, kind of...

## What we learned

36 hours is not a lot of time

## What's next for DeerHacks Group Project Cannon Game

uhhhhh