## Inspiration

Lyft's round up and donate system really inspired us here.

We wanted to find a way to benefit both users and help society. We all want to give back somehow, but don't know how sometimes or maybe we want to donate, but don't really know how much to give back or if we could afford it.

We wanted an easy way incorporated into our lives and spending habits.

This would allow us to reach a wider amount of users and utilize the power of the consumer society.

## What it does

With a chrome extension like "Heart of Gold", the user gets every purchase's round up to nearest dollar (for example: purchase of $9.50 has a round up of $10, so $0.50 gets tracked as the "round up") accumulated. The user gets to choose when they want to donate and which organization gets the money.

## How I built it

We built a web app/chrome extension using Javascript/JQuery, HTML/CSS.
Firebase javascript sdk library helped us store the calculations of the accumulation of round up's.
We make an AJAX call to the Paypal API, so it took care of payment for us.

## Challenges I ran into

For all of the team, it was our first time creating a chrome app extension. For most of the team, it was our first time heavily working with javascript let alone using technologies like Firebase and the Paypal API.

Choose what technology/platform would make the most sense was tough, but the chrome extension would allow for more relevance since a lot of people make more online purchases nowadays and an extension can run in the background/seem omnivalent.

So we picked up the javascript language to start creating the extension. Lisa Lu integrated the PayPal API to handle donations and used HTML/CSS/JavaScript to create the extension pop-up. She also styled the user interface.

Firebase was also completely new to us, but we chose to use it because it didn't require us to have a two step process: a server (like Flask) + a database (like mySQL or MongoDB). It also helped that we had a mentor guide us through. We learned a lot about the Javascript language (mostly that we haven't even really scratched the surface of it), and the importance of avoiding race conditions. We also learned a lot about how to strategically structure our code system (having a background.js to run firebase database updates

## Accomplishments that I'm proud of

Veni, vidi, vici.

We came, we saw, we conquered.

## What I learned

We all learned that there are multiple ways to create a product to solve a problem.

## What's next for Heart of Gold

Heart of Gold has a lot of possibilities: partnering with companies that want to advertise to users and social good organizations, making recommendations to users on charities as well as places to shop, game-ify the experience, expanding capabilities of what a user could do with the round up money they accumulate. Before those big dreams, cleaning up the infrastructure would be very important too.
## Inspiration

We were inspired very locally, by the resident hot dog stand owner, Nasir Al-Huttam. He's been taking orders for the UTSc community for almost a decade, and has been in need of an easier way of taking orders, as taking orders through text has been somewhat cumbersome for him.

## What it does

Using a chatbot powered by Microsoft Azure and Recast.ai, we've created a chatbot that takes orders from the customer from the Facebook Messenger App, and gives the user an interactive, intuitive experience akin to buying from another human, allowing them to even pay for their meal in advance, further streamlining the process.

## How we built it

For frontend, we used HTML and CSS, in combination with JQuery and Javascript to receive json files from the serverside, and interpret that information into display material for the business owner to look.

Recast.ai as well as the Microsoft Bot Framework was used to create the chatbot and program natural language and reactive conversation with the user. Node.js was also used.

The backend is powered by Python and Flask, using Microsoft Azure to deploy the database, postgreSQL, SQLAlchemy were also used.

## Challenges we ran into

Frontend-backend interactions, getting the JQuery to work properly.

## Accomplishments that we're proud of

Creating a functional chatbot that can handle a variety of situations, creating a clean, sleek user interface on the frontend.

## What we learned

Frontend-to-backend interactions, JQuery functionality, the basics of creating a chatbot.

## What's next for DogGo

Finishing the app in time to deploy to Nasir, then seeing if it can be looked into as a business venture.
## Inspiration

As university students and soon to be graduates, we understand the financial strain that comes along with being a student, especially in terms of commuting. Carpooling has been a long existing method of getting to a desired destination, but there are very few driving platforms that make the experience better for the carpool driver. Additionally, by encouraging more people to choose carpooling at a way of commuting, we hope to work towards more sustainable cities.

## What it does

FaceLyft is a web app that includes features that allow drivers to lock or unlock their car from their device, as well as request payments from riders through facial recognition. Facial recognition is also implemented as an account verification to make signing into your account secure yet effortless.

## How we built it

We used IBM Watson Visual Recognition as a way to recognize users from a live image; After which they can request money from riders in the carpool by taking a picture of them and calling our API that leverages the Interac E-transfer API. We utilized Firebase from the Google Cloud Platform and the SmartCar API to control the car. We built our own API using stdlib which collects information from Interac, IBM Watson, Firebase and SmartCar API's.

## Challenges we ran into

IBM Facial Recognition software isn't quite perfect and doesn't always accurately recognize the person in the images we send it. There were also many challenges that came up as we began to integrate several APIs together to build our own API in Standard Library. This was particularly tough when considering the flow for authenticating the SmartCar as it required a redirection of the url.

## Accomplishments that we're proud of

We successfully got all of our APIs to work together! (SmartCar API, Firebase, Watson, StdLib,Google Maps, and our own Standard Library layer). Other tough feats we accomplished was the entire webcam to image to API flow that wasn't trivial to design or implement.

## What's next for FaceLyft

While creating FaceLyft, we created a security API for requesting for payment via visual recognition. We believe that this API can be used in so many more scenarios than carpooling and hope we can expand this API into different user cases.