## Inspiration

The present disconnect between an equation written on the board and the visual representation of that equation. As previous Multivariable Calculus students, we struggled to grasp the complex equations thrown at us that were not trivial to conceptualize.

## What it does

This application is that connection. We interpret handwritten math equations using OCR within Wolfram's Mathematica platform. This data is then used to generate visual 3d models which are layered over a chosen surface within augmented reality. Essentially you strap on your Hololens start the HoloWolfram app then scan a math equation to instantly see the 3d model right on your desk.

## How we built it

HoloWolfram was built using the Wolfram Mathematica platform to parse the data obtained from a picture taken with the Hololens Once Wolfram was able to successfully read the equations we were writing out by hand on a standard sheet of paper it then generates a 3d model of the equation. This 3d model is loaded into unity as a GameObject using the Unity Link beta that was graciously provided to us by Kyle from Wolfram. Once we were able to load the 3d model into Unity it was just a matter of bringing all these separate pieces together and building the project to the Hololens.

## Challenges we ran into

Each different piece had its own pitfalls and being new to all of the different technologies used in HoloWolfram's creation was not an advantage. Building a Minimum Viable Product to Hololens successfully was perhaps our greatest feat because there are just so many moving parts of an app such as this and under the strict time constraints of a hackathon, decisions have to be made swiftly.

## Accomplishments that we're proud of

-Successfully Using the Unity Link in its beta form
-Learning how to build applications for the Hololens
-Diving deep into the Unity development environment

## What we learned

-Wolfram Mathematica is extremely powerful.

## What's next for HoloWolfram

-More interactivity,
-Gamification,
-Polished UI, and
-Publication to the Windows Store
## Inspiration

We hope this app encourages users to invest in the stocks and grow their personal investments.

## What it does

When the user sees a logo in everyday life and wants to learn more about the financial performance of said company in the stock exchange, the user can simply perform the airtap gesture and the HoloLens will take a snapshot of the current view. Then, the image is sent to Google’s Cloud Vision API and analyzed to see if there are any logos in the picture. If a logo is detected, the company of the logo is found and the NASDAQ API is used to determine the recent performance of the company’s stock. Finally, this financial data is visualized on the HoloLens through Unity.

## How we built it

We had the HoloLens take a picture after receiving an airtap gesture. The picture is then run through a chain of APIs, specifically Google Vision (to detect logos), a company name .csv (to get ticker names from company names), and NASDAQ API (to check stock prices).

## Challenges we ran into

We had challenges in implementing a gesture to capture photos, capturing photos, sending a JSON request through Unity to the Cloud Vision API, parsing XML from the NASDAQ API, and scripting in Unity. Because the HoloLens hasn’t been developed on much yet, there was little documentation and examples to learn from.

## Accomplishments that we're proud of

Becoming familiarized with developing for an AR environment, using Unity and the Windows Holographic Platform. Figuring out the Cloud Vision image recognition API to detect images from the snapshot the user takes on the HoloLens.

## What we learned

AR/Mixed Reality is an emerging field and devices like the HoloLens have incredible potential. It was a great learning experience to work with the HoloLens and figure out how to use Unity

## What's next for Logo Lens

1) By incorporating Capital One API, we could simulate buying and selling stocks on the go.
2) Selecting what pieces of data are more helpful to the user and presenting them using clean and easy to understand visualizations.
## Inspiration

With forest fires being a major issue in California and the Pacific North West, it is surprising to see technology lacking to provide information about them. With forest fire maps and air quality inconstantly appearing on Google and fires moving so fast that government agencies cannot alert endangered individuals quickly enough, there is clearly room for improvement. These three things are what I set off to solve.

## What it does

Fire! is a mobile app that allows a user to input their properties and are alerted through text and email when a government agency or another user reports an endangering forest fire. In addition to this, Fire! also provides global air quality information and recommendations with respect to the quality.

## How I built it

The mobile app was built with React Native connected to a Node.js + Express backend with MongoDB. Live forest fire data pulled from US government services InciWeb and FIRMS and air quality data pulled from Breezometer. Email + SMS notifications were made with AWS SNS.

## Accomplishments that I'm proud of

Being able to accomplish quite so much as a solo project

## What I learned

Flights can be delayed for longer than 4 hours

## What's next for Fire!

Fix the bugs + improve UI, still lots to be done