AstroMedAI

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🚀 Inspiration Space travel pushes the boundaries of human health. Astronauts face radiation exposure, muscle/bone loss, and psychological strain — all influenced by unpredictable solar activity. Inspired by NASA’s public DONKI API and the need for proactive space health tools, we built AstroMedAI: a smart, offline-capable risk simulator to make astronaut health forecasting both data-driven and accessible.

🧠 What it does AstroMedAI helps simulate astronaut health risks for custom space missions. It: Pulls real-time solar flare data from NASA (or falls back to offline CSV) Calculates Radiation Risk, Muscle/Bone Loss, and Mental Stress Visualizes risk levels in a Matplotlib chart Generates a PDF Mission Report and saves mission logs to CSV Includes a fun space health quiz to educate and engage The app works fully offline, making it ideal for remote missions, field researchers, and classrooms.

🛠 How we built it We used only Python and free tools, keeping it lightweight and offline-friendly: Tkinter for the GUI Matplotlib for risk charts FPDF to export styled PDF reports NASA DONKI API to fetch recent solar flare activity Custom risk model based on duration, orbit type, and shielding Fallback CSV for offline flare intensity simulation Modular design allowed us to split the app into distinct components: GUI, risk engine, API, charts, export modules, and quiz.

🧗 Challenges we ran into Handling API failures gracefully and designing a fallback model Designing an intuitive UI with zero external UI libraries Keeping everything offline-compatible yet feature-rich Balancing scientific accuracy with usability

🏅 Accomplishments that we're proud of Created a fully functional space risk simulator using real NASA data Built a modular Python app that runs offline, works cross-platform, and is easy to extend Designed a clean, dark-themed UI using just Tkinter Added features like PDF export, CSV logging, and an interactive quiz to boost utility + engagement

📚 What we learned The power of open space APIs like NASA DONKI How to blend data science + UI + educational design in a single Python app Importance of offline capability and fallback logic in real-world scenarios Python is still one of the best tools for hackathons with limited resources!

🚀 What's next for AstroMedAI Add AI-based risk prediction using historical solar weather trends Integrate voice assistant for astronauts in zero-G environments Support for multi-mission logging and visualization Turn it into a web dashboard or mobile version for wider accessibility Open-source the tool to educators and space simulation researchers

Built With

• fpdf
• github
• matplotlib
• nasadonkiapi
• numpy
• pyinstaller
• python
• reportlab
• requests
• tkinter
• venv