Inspiration
Us three found that throughout college, we have a lot of issues staying focused while studying. We wanted to make a study tool that automatically adapts with you while still keeping you on task.
What it does
Lasagna is an AI powered study tool that helps you stay focused while studying using the Pomodoro method while also matching your mood to curate the perfect songs to listen to. While studying, your change in mood is detected and that mood is processed through Spotify's API in order to automatically queue up the perfect song to regulate your emotions. Experiencing extreme emotions can often distract when studying so Lasagna recommends songs to bring your mood back to a stable level. Does a Misurda project have you down? Lasagna queues up some happy music to turn that frown upside down. The built-in Pomodoro timer ensures you aren't stuck at the screen for too long. Every 25 minutes, you're given a break from whatever your working on to stretch or simply take your mind off of the work. These layers aren't entirely unique on their own, but together, they make a powerful study tool.
How we built it
Our project has three distinct layers to it:
Pomodoro
Our pomodoro timer uses Threading Timers in order to avoid a regular, blocking wait( ) based timer.
Facial Mood Recognition (using Google Gemini)
We chose to use Google Gemini because of it's image processing capabilities. We take an image of the user ~20 seconds before your song is about to end. We then send the image to Gemini and have it return whether or not you're paying attention and what mood you're currently in. This is then given to Spotify to recommend your next song.
Spotify Integration
Spotify provides an API for people to use. It gives access to information such as the current song and recommendations based on certain factors you input. In this case, we're feeding the mood received from facial detection into Spotify's API in order to get recommendations based off of current mood. It automatically adds it to your listening queue so it seamlessly plays after your song.
Challenges we ran into
Our initial idea was to make a game in Unity about the cycle of grief. Everything was going flawlessly until we opened Unity and remembered that none of us have used it before. We hard pivoted to this concept after a few hours of work.
MacOS is just a bit too secure. In our mood detection, we take a picture of the user with the camera which Tim Cook does not approve of. We unfortunately couldn't resolve this issue within the 24 hour bounds.
Accomplishments that we're proud of
It was two of our team member's first hackathons so we're proud we managed to put together a completed project in under 24 hours even after pivoting so hard from our first idea.
What we learned
Ambition can take you a long way, but trying to make something in an engine we've never used was extremely overambitious. We learned to set appropriate goals and expectations. We also learned a lot about the integration of AI within programs.
What's next for Lasagna
We plan on letting our beloved Lasagna cook a little bit longer. Our Apple related layers turned out raw and unstable. We plan on adding Apple Music integration and fixing our MacOS bug with the camera.
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