## Inspiration

When thinking about how we could make a difference within local communities impacted by Covid-19, what came to mind are our frontline workers. Our doctors, nurses, grocery store workers, and Covid-19 testing volunteers, who have tirelessly been putting themselves and their families on the line. They are the backbone and heartbeat of our society during these past 10 months and counting. We want them to feel the appreciation and gratitude they deserve. With our app, we hope to bring moments of positivity and joy to those difficult and trying moments of our frontline workers. Thank you!

## What it does

Love 4 Heroes is a web app to support our frontline workers by expressing our gratitude for them. We want to let them know they are loved, cared for, and appreciated. In the app, a user can make a thank you card, save it, and share it with a frontline worker. A user's card is also posted to the "Warm Messages" board, a community space where you can see all the other thank-you-cards.

## How we built it

Our backend is built with Firebase. The front-end is built with Next.js, and our design framework is Tailwind CSS.

## Challenges we ran into

* Working with different time zones [12 hour time difference].
* We ran into trickiness figuring out how to save our thank you cards to a user's phone or laptop.
* Persisting likes with Firebase and Local Storage

## Accomplishments that we're proud of

* Our first Hackathon
	+ We're not in the same state, but came together to be here!
	+ Some of us used new technologies like Next.js, Tailwind.css, and Firebase for the first time!
	+ We're happy with how the app turned out from a user's experience
	+ We liked that we were able to create our own custom card designs and logos, utilizing custom made design-textiles

## What we learned

* New Technologies: Next.js, Firebase
* Managing time-zone differences
* How to convert a DOM element into a .jpeg file.
* How to make a Responsive Web App
* Coding endurance and mental focus
-Good Git workflow

## What's next for love4heroes

More cards, more love! Hopefully, we can share this with a wide community of frontline workers.
## Inspiration

Traffic is a pain and hurdle for everyone. It costs time and money for everyone stuck within it. We wanted to empower everyone to focus on what they truly enjoy instead of having to waste their time in traffic. We found the challenge to connect autonomous vehicles and enable them to work closely with each other to make maximize traffic flow to be very interesting. We were specifically interested in aggregating real data to make decisions and evolve those over time using artificial intelligence.

## What it does

We engineered an autonomous network that minimizes the time delay for each car in the network as it moves from its source to its destination. The idea is to have 0 intersections, 0 accidents, and maximize traffic flow.

We did this by developing a simulation in P5.js and training a network of cars to interact with each other in such a way that they do not collide and still travel from their source to target destination safely. We slowly iterated on this idea by first creating the idea of incentivizing factors and negative points. This allowed the cars to learn to not collide with each other and follow the goal they're set out to do. After creating a full simulation with intersections (allowing cars to turn and drive so they stop the least number of times), we created a simulation on Unity. This simulation looked much nicer and took the values trained by our best result from our genetic AI. From the video, we can see that the generation is flawless; there are no accidents, and traffic flows seamlessly. This was the result of over hundreds of generations of training of the genetic AI. You can see our video for more information!

## How I built it

We trained an evolutionary AI on many physical parameters to optimize for no accidents and maximal speed. The allowed the AI to experiment with different weights for each factor in order to reach our goal; having the cars reach from source to destination while staying a safe distance away from all other cars.

## Challenges we ran into

Deciding which parameters to tune, removing any bias, and setting up the testing environment. To remove bias, we ended up introducing randomly generated parameters in our genetic AI and "breeding" two good outcomes. Setting up the simulation was also tricky as it involved a lot of vector math.

## Accomplishments that I'm proud of

Getting the network to communicate autonomously and work in unison to avoid accidents and maximize speed. It's really cool to see the genetic AI evolve from not being able to drive at all, to fully being autonomous in our simulation. If we wanted to apply this to the real world, we can add more parameters and have the genetic AI optimize to find the parameters needed to reach our goals in the fastest time.

## What I learned

We learned how to model and train a genetic AI. We also learned how to deal with common issues and deal with performance constraints effectively. Lastly, we learned how to decouple the components of our application to make it scalable and easier to update in the future.

## What's next for Traffix

We want to increasing the user-facing features for the mobile app and improving the data analytics platform for the city. We also want to be able to extend this to more generalized parameters so that it could be applied in more dimensions.
Hello and thank you for judging my project. I am listing below two different links and an explanation of what the two different videos are. Due to the time constraints of some hackathons, I have a shorter video for those who require a lower time. As default I will be placing the lower time video up above, but if you have time or your hackathon allows so please go ahead and watch the full video at the link below. Thanks!

[3 Minute Video Demo](https://youtu.be/8tns9b9Fl7o)

[5 Minute Demo & Presentation](https://youtu.be/Rpx7LNqh7nw)

For any questions or concerns, please email me at [joshiom28@gmail.com](mailto:joshiom28@gmail.com)

## Inspiration

Resource extraction has tripled since 1970. That leaves us on track to run out of non-renewable resources by 2060. To fight this extremely dangerous issue, I used my app development skills to help everyone support the environment.

As a human and a person residing in this environment, I felt that I needed to used my technological development skills in order to help us take care of the environment better, especially in industrial countries such as the United States. In order to do my part in the movement to help sustain the environment. I used the symbolism of the LORAX to name LORAX app; inspired to help the environment.

\_ side note: when referencing firebase I mean firebase as a whole since two different databases were used; one to upload images and the other to upload data (ex. form data) in realtime. Firestore is the specific realtime database for user data versus firebase storage for image uploading \_

## Main Features of the App

To start out we are prompted with the **authentication panel** where we are able to either sign in with an existing email or sign up with a new account. Since we are new, we will go ahead and create a new account. After registering we are signed in and now are at the home page of the app. Here I will type in my name, email and password and log in. Now if we go back to firebase authentication, we see a new user pop up over here and a new user is added to firestore with their user associated data such as their **points, their user ID, Name and email.** Now lets go back to the main app. Here at the home page we can see the various things we can do. Lets start out with the Rewards tab where we can choose rewards depending on the amount of points we have.

If we press redeem rewards, it takes us to the rewards tab, where we can choose various coupons from companies and redeem them with the points we have. Since we start out with zero points, we can‘t redeem any rewards right now.

Let's go back to the home page.

The first three pages I will introduce are apart of the point incentive system for purchasing items that help the environment

If we press the view requests button, we are then navigated to a page where we are able to view our requests we have made in the past. These requests are used in order to redeem points from items you have purchased that help support the environment. Here we would we able to **view some details and the status of the requests**, but since we haven’t submitted any yet, we see there are none upon refreshing. Let’s come back to this page after submitting a request.

If we go back, we can now press the request rewards button. By pressing it, we are navigated to a form where we are able to **submit details regarding our purchase and an image of proof to ensure the user truly did indeed purchase the item**. After pressing submit, **this data and image is pushed to firebase’s realtime storage (for picture) and Firestore (other data)** which I will show in a moment.

Here if we go to firebase, we see a document with the details of our request we submitted and if we go to storage we are able to **view the image that we submitted**. And here we see the details. Here we can review the details, approve the status and assign points to the user based on their requests. Now let’s go back to the app itself.

Now let’s go to the view requests tab again now that we have submitted our request. If we go there, we see our request, the status of the request and other details such as how many points you received if the request was approved, the time, the date and other such details.

Now to the Footprint Calculator tab, where you are able to input some details and see the global footprint you have on the environment and its resources based on your house, food and overall lifestyle. Here I will type in some data and see the results. **Here its says I would take up 8 earths, if everyone used the same amount of resources as me.** The goal of this is to be able to reach only one earth since then Earth and its resources would be able to sustain for a much longer time. We can also share it with our friends to encourage them to do the same.

Now to the last tab, is the savings tab. Here we are able to find daily tasks we can simply do to no only save thousands and thousands of dollars but also heavily help sustain and help the environment. \**Here we have some things we can do to save in terms of transportation and by clicking on the saving, we are navigated to a website where we are able to view what we can do to achieve these savings and do it ourselves. \**

This has been the demonstration of the LORAX app and thank you for listening.

## How I built it

For the navigation, I used react native navigation in order to create the authentication navigator and the tab and stack navigators in each of the respective tabs.

## For the incentive system

I used Google Firebase’s Firestore in order to view, add and upload details and images to the cloud for reviewal and data transfer. For authentication, I also used **Google Firebase’s Authentication** which allowed me to create custom user data such as their user, the points associated with it and the complaints associated with their **user ID**. Overall, **Firebase made it EXTREMELY easy** to create a high level application. For this entire application, I used Google Firebase for the backend.

## For the UI

for the tabs such as Request Submitter, Request Viewer I used React-native-base library to create modern looking components which allowed me to create a modern looking application.

## For the Prize Redemption section and Savings Sections

I created the UI from scratch trialing and erroring with different designs and shadow effects to make it look cool. The user react-native-deeplinking to navigate to the specific websites for the savings tab.

## For the Footprint Calculator

I embedded the **Global Footprint Network’s Footprint Calculator** with my application in this tab to be able to use it for the reference of the user of this app. The website is shown in the **tab app and is functional on that UI**, similar to the website.

I used expo for wifi-application testing, allowing me to develop the app without any wires over the wifi network.

For the Request submission tab, I used react-native-base components to create the form UI elements and firebase to upload the data.

For the Request Viewer, I used firebase to retrieve and view the data as seen.

## Challenges I ran into

Some last second challenges I ran to was the manipulation of the database on Google Firebase. While creating the video in fact, I realize that some of the parameters were missing and were not being updated properly. I eventually realized that the naming conventions for some of the parameters being updated both in the state and in firebase got mixed up. Another issue I encountered was being able to retrieve the image from firebase. I was able to log the url, however, due to some issues with the state, I wasnt able to get the uri to the image component, and due to lack of time I left that off. Firebase made it very very easy to push, read and upload files after installing their dependencies.
Thanks to all the great documentation and other tutorials I was able to effectively implement the rest.

## What I learned

I learned a lot. Prior to this, I had not had experience with **data modelling, and creating custom user data points. \*\*However, due to my previous experience with \*\*firebase, and some documentation referencing** I was able to see firebase’s built in commands allowing me to query and add specific User ID’s to the the database, allowing me to search for data base on their UIDs. Overall, it was a great experience learning how to model data, using authentication and create custom user data and modify that using google firebase.

## Theme and How This Helps The Environment

Overall, this application used **incentives and educates** the user about their impact on the environment to better help the environment.

## Design

I created a comprehensive and simple UI to make it easy for users to navigate and understand the purposes of the Application. Additionally, I used previously mentioned utilities in order to create a modern look.

## What's next for LORAX (Luring Others to Retain our Abode Extensively)

I hope to create my **own backend in the future**, using **ML** and an **AI** to classify these images and details to automate the submission process and **create my own footprint calculator** rather than using the one provided by the global footprint network.