HackStack

Project Info

ZvezdaCardio

Devpost

This project did not submit a demo video on Devpost.

Inspiration

We took inspiration in using positive reinforcement to motivate workouts and fitness training. ZvezdaCardio is intended to act like a virtual fitness trainer.

What it does

In its current iteration, ZvezdaCardio tracks steps of the user and calories burnt. It tracks these in lifetime and daily stats. This is converted into points using an algorithm. Currently points are used on the leaderboard where users can compete to see who can get the most. You are also able to set daily goals which you get additional points for completing. We have also implemented an Zvezda AI, a chatbot that can tell you proximity to your goal and with other useful fitness advice.

How we built it

The UI and frontend was designed using Swift and React for the mobile and web applications respectively. The backend was built using Firebase.

Challenges we ran into

Implementing Firebase across React and Swift was difficult and took a lot of time. Made us contribute more time to the mobile app since the Firebase was set up for Swift first.

Accomplishments we're proud of

Linking both React and Swift to Firebase, since it was so difficult for us. In addition, we are proud of the Zvezda AI chatbot, since it was our first time using Gemini Generative AI.

What we learned

It’s important to choose a tech stack that suits the project you want to build. Having a well thought out plan before building will pay dividends.

What's next

Personalized icons/characters that you can customize with items bought from the in-game marketplace with your points. Connect with friends to do pair runs for double points, or compete with them on the contact-only leaderboard. Make the app more social through implementing a forum and a way to communicate with friends. Go beyond just tracking cardio through implementing manually input workouts. Expand the Zvezda chatbot so it can provide personalized workouts based on user requests Implement a workout calendar, which Zvezda chatbot can project recommendations onto. The user can also edit manually and invite friends to their workouts calendar.

Analysis

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Technology

Found in codeClaimed only
  • CSSIn code
  • HTMLIn code
  • JavaScriptIn code
  • ReactIn code
  • SwiftIn code
  • FirebaseClaimed
  • Google GeminiClaimed

5 of 7 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

55 KB

Source files

34

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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