We are all currently university students with one thing in common: we can never get up in the morning. Our inspiration for this project were the daily battles with sleep, which often leads to an unproductive, groggy, start of the day.
With the constant pressure to balance schoolwork, extracurriculars, hobbies, and social events, students are always in a fight with time. By optimizing the process of waking up, we hope that other students can use our tool to effectively start off their day.
Rooster is a personalized alarm system—it utilizes a machine learning backend to fetch the most ideal alarm music to wake up the user with increasing efficiency over-time. By using the reaction time of the user to a given alarm song, our model will use various facets to generate songs with increases in refreshing musical features, such as higher tempo, liveliness, and valence to elicit a faster response. Like other alarm apps, the user can add, and delete alarms as they please.
Rooster is built with a Python ML Model + Flask, React Native frontend powered by Expo CLI and REST API's.
Will be released when the project is finalized.