Rate Your Ride

Inspiration

We were inspired by the fact that we happened to have proximity sensors, and that USC is chock full of longboards and penny boards, and so we saw the opportunity to put two and two together.

What it does

It records metrics about the smoothness and quality of a given longboard ride, and then returns that to the user

How we built it

We built it by connecting a proximity sensor via bluetooth to an android application, which then sent data to a server for processing.

Challenges we ran into

Inconsistent readings from the sensor, bluetooth connectivity issues, low level UID identification, connection with the server, dealing with deprecated APIs, etc.

Accomplishments that we're proud of

We actually made it work, in only 24 hours, on technologies that most of us hadn't used before. And, it works surprisingly well.

What we learned

A lot of different APIs, working with IoT for the first time, getting used to the whole partitioning of work based on what every individual is good at, and just all the human challenges that come with working for 24 hours nonstop.

What's next for Rate Your Ride

Aggregating mass user data to create a map which shows the optimal(smoothest) routes for longboards, around campus, or around the world!

Built With

Submitted to

TrojanHacks 2016

Created by

I primarily developed the Android application, as well as interfaced via bluetooth to our proximity sensor, and wrote code to communicate with the server. There were a lot of new technologies, particularly Simblee and Bluetooth, as well as working with our own API

Samuel Resendez
A computer science student at the University of Southern California.
I worked on the cherrypy backend creating an API for gathering and analyzing sensor data. I had a lot of firsts on this project: first time using AWS, first time working with MongoDB, and first big project communicating with JSON.

Caleb Thomas
I worked with a partner (Raghav) to optimize the vibration detection system along the z-axis of the longboard using a distance sensor. I also worked with the Google Charts API to output dynamic graphs of real-time data. In creating these graphs, I worked in Javascript and a bit of CSS.

Joel George
I worked on implementing source code to initially connect the Simblee infrared proximity sensor with the Android mobile platform and establish the sending/receiving of data. Collaborated with Joel to optimize the vibration detection of the long-board in the Z-axis, by attaching the distance sensor to a spring-like mechanic at the bottom of the board

Raghav Maheshwari

Updates

Samuel Resendez started this project — Oct 30, 2016 02:57 PM EDT

Leave feedback in the comments!

Log in or sign up for Devpost to join the conversation.