## Inspiration

In the fight against COVID, social distancing has converted grocery shopping into an inefficient and difficult necessity. From chatting with our parents to browsing on Reddit, we have discovered that people are waiting outside in close proximity to grocery shop. For the immunocompromised and the elderly, this endangers their lives due to close contact with others and unpredicatble weather conditions in varying regions. On the other hand, it is unproductive for many to wait upwards of half an hour to purchase groceries. Previously, we were able to go to a store on a whim. Nowadays, many stores enforce capacity restrictions and long waits are required to enter most stores.

We are a team of designers and developers interested in solving problems from the user's perspective. There were a couple goals we had in mind when tackling this problem
- Reducing grocery wait-times
- Creating a low touch process for store waitlists
- Utilize user location to prevent bad waitlist behavior and streamline waitlist process
- Create incentives for both stores and customers to adopt this model
- Users are incentivized to use this app since they can save time by queuing at home and crowdsource store cleanliness information
- Stores are incentivized to use the app to streamline the queue and gain insights on how their store is performing in terms of cleanliness and from a capacity standpoint
- Promote shopping at local businesses and encourage safe social behaviors

## What it does

- Display a map of grocery stores based on your location and their associated wait times and crowdsourced health-rating.
- Users can browse stores near them and decide which queue to join.
- Small and local businesses are highlighted to promote visibility
- Users can join queues from anywhere, but must be within range of the store when it's their turn in order to check in
- When it's almost their turn, we notify users and start a countdown.
- At the store, users can show their confirmation screen to the store attendant.
- Users are prompted to rate the store's cleanliness experience
- Finally, we encourage users to donate to local food banks and support their community. We're all in this together!

## How I built it
Our application was developed using a MERN (Mongo, Express, React Native, and Nodejs) stack. With expo, we were able to rapidly prototype and test our mobile application.

Starting with ideation, we slowly centered our app around the ideas in the inspiration section. From there, half of the team worked on mocks in Figma and the other half started on setting up the structure for frontend and backend development.

Using these Figma mocks, a majority of our team worked on the front end to ensure a responsive UI/UX.

Our backend utilized the Yelp API to surface nearby grocery stores based on your location. From there, we put all queried store information, waitlists, and cleanliness ratings on Mongo Atlas. Our backend is hosted on Google Cloud using the App Engine which our front end uses through get and post requests.

## Challenges I ran into
We encountered a lot of difficulty with integrating Radar.io into our application. In order to leverage Radar's platform on our app, we had to eject expo in order to link their SDK. We tried for two hours, but decided that it was better that we pivoted in order to fully-flesh out other parts of the application.

## Accomplishments that I'm proud of & What I learned

Our team consisted of a mix of designers and developers. Half of our team had light experience with Expo and React Native, while the other half has never developed on React Native before. For all of us, this is the quickest we have ever developed a product from ideation to design to development.

## What's next for Cue

- Create geofences to streamline the check-in process even further via Radar's API
- Incorporate historical data and crowdsourcing into the store-time waiting length for more accurate estimates
- Feedback form for customer to fill out so stores can improve their distancing and safety initiatives
- Develop a UI for stores to understand their foot traffic and whether they are following capacity guidelines within each county