## Inspiration

The app idea originated from the expense of testing such basic physical properties as Young's modulus, a standard measure of the stiffness of a material. Instron force testing machines, typically used to measure properties like Young's modulus, are very expensive. In the field of bioengineering, materials tested are often much softer and do not require the full force of the machine. Furthermore, Instron machines are also utilized for labs, yet students don't usually require the full precision of the Instron to complete their work. A portable, cheap way for mechanical and biomedical engineers to measure physical properties is as simple as utilizing the accelerometers in the smartphone. This then evolved into the full EngineeringKit, a user-friendly virtual toolbox with 4 engineering features, all of which usually require more expensive equipment or a greater investiture of time, and brings them together for convenient usage.

## What it does

EngineeringKit has 4 features:

Young's modulus,
Calipers,
Material Properties, &
Mathematics.

## How I built it

Built in Android Studio with the Java language; makes use of the phone's accelerometers

Young's Modulus - Uses the phone's accelerometers and known mass and area of the object to calculate stress-strain graph and display it with a graphing library

Calipers utilize listeners for screen touch events and allowing the user to drag lines across the screen to fit against the object needed, then converts the distance between these lines to inches.

Material properties utilizes Google Voice API or text entry to listen for a query, then uses Wolfram Alpha API to search a specific answer, hand-parsing the XML string for the correct data

Mathematics similarly uses Google Voice API or text entry to listen for a query, then uses Wolfram Alpha API to search a specific answer, hand-parsing the XML for a correct image of the needed equation.

## Accomplishments that I'm proud of

Implementing the Wolfram Alpha API by querying their website and returning the relevant information for the search.

## What's next for EngineeringKit

Calibrating Young's modulus calculator more thoroughly, implementing a Kalman filter to increase its position-sensing accuracy; allowing for stepped force input rather than just constant force which would primarily be useful for only viscoelastic materials; allowing for three-point bending with a 3D-printed attachment to phone case; allowing for calculation of shear modulus
## Inspiration

After Apple announced their first ARDevKit, our group knew we wanted to tinker with the idea. Having an experienced group who won previous hackathons with mobile apps, we were excited to delve head-first into the world of Augmented Reality.

## What it does

It calculates the instantaneous/average velocity of an object.

## How we built it

Using Swift in Xcode, we incorporated Calculus concepts into the development of the AR.

## Challenges we ran into

To calculate instantaneous velocity, we had to get very small time increments that approach infinitesimally small changes in time. Processing as many position values per second becomes important to improving the accuracy. However, this can be CPU-intensive. So we created an efficient and optimised program.

## Accomplishments that we're proud of

Creating a full-functioning app in less than 24 hours after concept.

## What we learned

Working as a cohesive unit and the potential AR has.
Managing time properly.

## What's next for SpeedAR

Adding a slider to change the accuracy of the velocity.
Adding a low-power mode to further save battery and limit processing clock speeds.
Individual object-tracking to remove the need to manually pan the camera to trace an object's movement.
## Inspiration

Cute factor of dogs/cats, also to improve the health of many pets such as larger dogs that can easily become overweight.

## What it does

Reads accelerometer data on collar, converted into steps.

## How I built it

* Arduino Nano
* ADXL345 module
* SPP-C Bluetooth module
* Android Studio for app

## Challenges I ran into

Android studio uses a large amount of RAM space.
Interfacing with the accelerometer was challenging with finding the appropriate algorithm that has the least delay and lag.

## Accomplishments that I'm proud of

As a prototype, it is a great first development.

## What I learned

Some android studio java shortcuts/basics

## What's next for DoogyWalky

Data analysis with steps to convert to calories, and adding a second UI for graphing data weekly and hourly with a SQLite Database.