We were inspired by the idea of listening to music on a road trip. What if your playlist was able to adapt and change with you on your trip?
What it does
Our initial idea was to create spotify playlists based on location. Since people's moods and preferred music changes with their environment, we extended the idea to generate playlists based on other environment variables such as time of day or the current weather. We generate a set of track features based upon inputs provided by an Android phone. It queries the Spotify API to get recommendations.
How we built it
We used the Android SDK to develop the application. The backend was built using Django and Heroku.
Challenges we ran into
We are fairly new to using the Android SDK and generating web servers in python. We had to overcome this steep learning curve in order to develop our idea.
Accomplishments that we're proud of
We're proud that we were able to create an app that communicated with not only an external API, but our own custom web server. We are also proud of how extensible our framework is. We developed it so that plugins can be built by simply writing a function to map the inputs to the track features.
What we learned
We learned how to create a restful API on top of the python Django stack. We also learned how to make an Android app with multiple integreated activities.
What's next for StreetSmart
We would like to have this app allow for different feature configurations. We also have some ideas about other inputs to influence recommendations, such as mining twitter feeds or monitoring the stock market.