## Inspiration: Being a manager is hard work, so finding a way to help them would be nice. We thought it would be a good idea to make a shift scheduler, making managing a company easier by planning ahead when employees will work during the week.

## What it does: Lets a manager schedule shifts for employees in advance.

## How we built it:

Our designer Audrey Garcia came up with the idea and design for the project for the front end. We talked about what's needed and what could be simplified within the design.

The front end: React-native in typescript

The back end: Nodejs, Apollo Server Express, MongoDB database, GraphQL API, for testing Mocha + Chai + Supertest

## Challenges we ran into

Not enough teammates to program, frontend and backend was stretched for time. Frontend issues like how to make and organize complex components, and found backend middleware issues resulting in tests stalling.

## Accomplishments that we're proud of

We participated in this event and learned a lot :)

## What we learned

Front end web design in react native, backend organization and middleware design

## What's next for Shift Scheduler

Completing the frontend and backend, fixing middleware issues and completing the test suite for shift scheduling. Also creating a ts-sdk for the frontend to access the GraphQL API.
## Inspiration

Almost a year ago, reporter **Kurt Eichenwald** was the victim of a potentially deadly attack. Knowing that the journalist suffered from epilepsy, alt-right Twitter users tweeted animated strobe GIFs at him, in an effort to trigger an epileptic seizure. Prosecutors believe that Eichenwald was chosen due his Jewish descent and his critical view of Donald Trump.

![Twitter user attacks reporter Kurt Eichenwald](https://i.amz.mshcdn.com/XOJc2-BgY5AhxM3X03uNgxlsIBc=/fit-in/1200x9600/https%3A%2F%2Fblueprint-api-production.s3.amazonaws.com%2Fuploads%2Fcard%2Fimage%2F418455%2F5d2cc67c-c8b0-4ae8-b40c-5928d6964aeb.jpg)

While the Internet has revolutionized communication and various other functions of our society, the relative freedom and anonymity on the web often inspires **questionable** and occasionally **dangerous** content. Rather than relying on social media companies and other tech giants, to police content and cater to the various needs of users, we decided to build **pro.tech**.

## What it does

**pro.tech** is a browser extension that utilizes deep learning to identify user-defined visually malicious images and GIFs. We allow users to toggle filters, and use sophisticated deep learning technologies to identify:

* GIFs that may potentially trigger an epileptic seizures
* images/GIFs that may have content that you'd like to avoid (e.g., spiders, rats, Donald Trump...etc.)
* images/GIFs that may contain nudity

![Select your content blocking filters](https://i.imgur.com/ZMbnjf4.png)

We also use Microsoft's Cognitive Services API to caption blocked images and ensure that your browser experience is hindered as little as possible.

![Example of blocked content](https://i.imgur.com/IgK5Pfk.png)

## How I built it

The extension itself was built in vanilla Javascript with the web extensions API, allowing it to run in Chrome, Edge, Firefox and Opera.

The server-side functionality is built with Python and the Tornado framework. Due to the environment-related difficulties associated with deep learning models, we're hosting servers on both **Microft Azure** and **AWS**.

We're identify GIFs that may trigger epileptic seizures by calculating the L2-norm between subsequent frames in the GIF and using medically-inspired heuristics to determine whether a GIF can be potentially dangerous.

For image tagging, we are using a pre-trained VGG-16 model in PyTorch as well as the Microft Cognitive Services API.

To keep track of analytics, we utilize stdlib to calculate and record metrics pertaining to the effectiveness of our extension.

We also use Microsoft's Cognitive Services API to caption blocked images and ensure that your browser experience is hindered as little as possible.

## What's next for pro.tech

We also use Microsoft's Cognitive Services API to caption blocked images and ensure that your browser experience is hindered as little as possible. We will also extend our content blocking algorithms beyond images and GIFs, potentially to videos and even live streams.

It is our hope that pro.tech will enable users to browse the web with a restored sense of safety. When the content gets questionable, we will pro.tech.
## Inspiration

The inspiration for our project stems from the increasing trend of online shopping and the declining foot traffic in physical stores. Our goal was to provide a unique and engaging experience for customers, encouraging them to visit physical stores and rediscover the joy of in-person shopping. We wanted to create an interactive and entertaining shopping experience that would entice customers to visit stores more frequently and foster a deeper connection between them and the store's brand.

## What it does

Our project is an AR scavenger hunt experience that gamifies the shopping experience. The scavenger hunt encourages customers to explore the store and discover new products they may have otherwise overlooked. As customers find specific products, they can earn points which can be redeemed for exclusive deals and discounts on future purchases. This innovative marketing scheme not only provides customers with an entertaining experience but also incentivizes them to visit stores more frequently and purchase products they may have otherwise overlooked.

## How we built it

To create the AR component of our project, we used Vuforia and Unity, two widely used platforms for building AR applications. The Vuforia platform allowed us to create and track image targets, while Unity was used to design the 3D models for the AR experience. We then integrated the AR component into an Android application by importing it as a Gradle project. Our team utilized agile development methodologies to ensure efficient collaboration and problem-solving throughout the development process.

## Challenges we ran into

One of the challenges we faced was integrating multiple APIs and ensuring that they worked together seamlessly. Another challenge was importing the AR component and creating the desired functionality within our project. We also faced issues with debugging and resolving technical errors that arose during the development process.

## Accomplishments that we're proud of

Despite the challenges we faced, we were able to achieve successful teamwork and collaboration. Despite forming the team later than other groups, we were able to effectively communicate and work together to bring our project to fruition. We are proud of the end result, which was a polished and functional AR scavenger hunt experience that met our objectives.

## What we learned

We learned how difficult it is to truly ship out software, and we are grateful to have joined the hackathon. We gained a deeper understanding of the importance of project planning, effective communication, and collaboration among team members. We also learned that the development process can be challenging and unpredictable, and that it requires perseverance and problem-solving skills. Additionally, participating in the hackathon taught us valuable technical skills such as integrating APIs, creating AR functionality, and importing projects onto an Android application.

## What's next for Winnur

Looking forward, we plan to incorporate Computer Vision technology into our project to prevent potential damage to our product's packaging. We also aim to expand the reach of our AR scavenger hunt experience by partnering with more retailers and enhancing the user interface and experience. We are excited about the potential for future development and growth of Winnur.