## Inspiration

Between my friends and I, when there is a task everyone wants to avoid, we play a game to decide quickly. These tasks may include, ordering pizza or calling an uber for the group. The game goes like this, whoever thinks of this game first says "shotty not" and then touches their nose. Everyone else reacts to him and touches their nose as fast as they can. The person with the slowest reaction time is chosen to do the task. I often fall short when it comes to reaction time so I had to do something about it

## What it does

The module sits on top of your head, waiting to hear the phrase "shotty not." When it is recognized the finger will come down and touch your nose. You will never get caught off guard again.

## How I built it

The finger moves via a servo and is controlled by an arduino, it is connected to a python script that recognizes voice commands offline. The finger is mounted to the hat with some 3d printed parts.

## Challenges I ran into

The hardware lab did not have a voice recognition module or a bluetooth module for arduino. I had to figure out how to go about implementing voice recognition and connect it to the arduino.

## Accomplishments that I'm proud of

I was able to model and print all the parts to create a completely finished hack to the best of my abilities.

## What I learned

I learned to use a voice recognition library and use Pyserial to communicate to an arduino with a python program.

## What's next for NotMe

I will replace the python program with a bluetooth module to make the system more portable. This allows for real life use cases.
## Inspiration

When we thought about tackling the pandemic, it was clear to us that we'd have to **think outside the box**. The concept of a hardware device to enforce social distancing quickly came to mind, and thus we decided to create the SDE device.

## What it does

We utilized an ultra-sonic sensor to detect bodies within 2m of the user, and relay that data to the Arduino. If we detect a body within 2m, the buzzer and speaker go off, and a display notifies others that they are not obeying social distancing procedures and should relocate.

## How we built it

We started by creating a wiring diagram for the hardware internals using [Circuito](circuito.io). This also provided us some starter code including the libraries and tester code for the hardware components.
We then had part of the team start the assembly of the circuit and troubleshoot the components while the other focused on getting the CAD model of the casing designed for 3D printing.
Once this was all completed, we printed the device and tested it for any bugs in the system.

## Challenges we ran into

We initially wanted to make an Android partner application to log the incidence rate of individuals/objects within 2m via Bluetooth but quickly found this to be a challenge as the team was split geographically, and we did not have Bluetooth components to attach to our Arduino model. The development of the Android application also proved difficult, as no one on our team had experience developing Android applications in a Bluetooth environment.

## Accomplishments that we're proud of

Effectively troubleshooting the SDE device and getting a functional prototype finished.

## What we learned

Hardware debugging skills, how hard it is to make an Android app if you have no previous experience, and project management skills for distanced hardware projects.

## What's next for Social Distancing Enforcement (SDE)

Develop the Android application, add Bluetooth functionality, and decrease the size of the SDE device to a more usable size.
## Inspiration

In online documentaries, we saw visually impaired individuals and their vision consisted of small apertures. We wanted to develop a product that would act as a remedy for this issue.

## What it does

When a button is pressed, a picture is taken of the user's current view. This picture is then analyzed using OCR (Optical Character Recognition) and the text is extracted from the image. The text is then converted to speech for the user to listen to.

## How we built it

We used a push button connected to the GPIO pins on the Qualcomm DragonBoard 410c. The input is taken from the button and initiates a python script that connects to the Azure Computer Vision API. The resulting text is sent to the Azure Speech API.

## Challenges we ran into

Coming up with an idea that we were all interested in, incorporated a good amount of hardware, and met the themes of the makeathon was extremely difficult. We attempted to use Speech Diarization initially but realized the technology is not refined enough for our idea. We then modified our idea and wanted to use a hotkey detection model but had a lot of difficulty configuring it. In the end, we decided to use a pushbutton instead for simplicity in favour of both the user and us, the developers.

## Accomplishments that we're proud of

This is our very first Makeathon and we were proud of accomplishing the challenge of developing a hardware project (using components we were completely unfamiliar with) within 24 hours. We also ended up with a fully function project.

## What we learned

We learned how to operate and program a DragonBoard, as well as connect various APIs together.

## What's next for Aperture

We want to implement hot-key detection instead of the push button to eliminate the need of tactile input altogether.