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An example of a "danceability" graph
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Dynamic analysis
Inspiration
I have always had a problem with any given DJ. No matter how small that problem was, I just couldn't get over the bumps in a night of fun. Especially during house parties, oftentimes the host will just slap on any old playlist and hope for the best. We decided that we could do better.
What it does
When at parties, the DJ can't always read the room. But now, thanks to Dynamix, they don't have to! We're taking automation to the next level by utilizing activity movement and heart rate weighted against the amount of people in a room to achieve a "danceability" score. This score is then used to determine what kind of music should be playing - fast paced dubstep, chill slow R&B, or even some funky jazz. You keep movin' and we'll keep groovin'!
How I built it
We're accessing fitbit data of individuals registered with our 'party'. From there, we analyze the data through our algorithm, and then create a dynamic spotify playlist from the data results. Specifically, we used Node.JS, the Spotify API, MongoDB, AWS, JQuery, PHP, Ajax, and bootstrap.
Challenges I ran into
Ensuring the experience is fully automated and dynamic - it was difficult to utilize the Spotify API which can oftentimes be a little clunky.
Accomplishments that I'm proud of
Creating a fully working minimal-viable product that can be shipped out as soon as today. Not bad for 2 days.
What I learned
How to rave and party like mad with our ultra-new Dynamix, the mix that you know will always be dynamic.
What's next for Dynamix
Backend: better analytics, improve the algorithm, refactor code to be more efficient. User experience: automatic bluetooth connection to the party of your location based on geofencing
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