pace.ai
iOS app published on the App Store generating structured training plans balancing performance gains with injury prevention for distance runners.
Overview
During high school, in an effort to make large improvements to my track times over break, I decided to overexert myself and run hard workouts everyday. Inevitably, I ended up getting injured.
This inspired me to make pace.ai as a way to keep runners accountable with their training. It uses VDOT scores as a measure of fitness to provide training plans with optimal paces and mileage. The app continuously learns from the user's performance, adjusting pace and mileage to reflect progress.
I designed the frontend using Swift and the backend and authentication using Firebase. I submitted pace.ai to the iOS App Store, and it was approved for publication.
My app was awarded Honorable Mention in the Congressional App Challenge for California's 16th Congressional District.
Key Languages, Platforms, and Frameworks Used
Swift
Python
Firebase