Team Tweakistan

We present AURA - the first Adaptive Unified Routine Assistant using gamification - that employs automated detection of burnout symptoms and depression, taking preventive measures such as therapy.

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Inspiration

We were driven by the growing mental health crisis, particularly burnout and depression, highlighted by modern digital lifestyles. We wanted to create a proactive, tech-driven solution that could intervene before a person reaches a crisis point.

What it does

AURA is an agentic system that uses biometric and screen behavior data to analyze early warning signals of burnout and depression. It goes beyond simple analytics by actively intervening through personalized notifications, strategic screen blocking, and a unique gamification system designed to counter dopamine addiction. To bridge the gap to professional help, it also recommends nearby therapists and can send pre-drafted emails to lower the barrier to seeking support.

How we built it

We architected AURA as a full-stack application. The frontend was built using Lovable for a dynamic and engaging user interface. The backend was developed with Python and FastAPI to create a robust and scalable API. For data persistence, we used SQLite, and the application was deployed using Railway. We rigorously tested all our API endpoints with Postman to ensure reliability.

Challenges we ran into

Since tracking data, provided by smartwatches, and mobile app tracking were not available, we used mock data. Therefore, we could not use specific events that triggered the backend endpoints.

Accomplishments that we're proud of

We are proud of having successfully built a functional, learning-based, agentic system that tackles a real-world problem. A key accomplishment is the creation of our novel gamification system, specifically designed to reward healthy digital habits and help users break the cycle of dopamine addiction associated with their devices.

What we learned

This project was a deep dive into full-stack development, teaching us how to integrate complex systems from the frontend to a deployed backend. We gained practical experience in building AI agent workflows, handling user data responsibly, and the importance of designing user interactions that are supportive, not stressful.

What's next for Team Tweakistan

We are hungry for the Student Clash! This competition is the immediate next step for us to showcase AURA, test it against other innovative ideas, and receive valuable feedback to push our project even further.

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