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
- amazon-web-services
- android-studio
- bluetooth
- cherrypy
- google-chart
- iot
- mongodb
- simblee
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