NightOwls

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🌌 Night Owl — Intelligent Stargazing Platform 🚀 Tagline

Find the best place and time to see the universe using real-time astronomy, weather, and AI.

🧠 Inspiration

Stargazing sounds simple — but in reality, it depends on many unpredictable factors like weather, light pollution, moon brightness, and celestial positioning.

My colleague once missed a rare solar eclipse due to cloud cover despite careful planning. That moment sparked a question:

What if we could predict the perfect sky like a navigation system?

Night Owl was built to solve exactly that.

🌟 What it does

Night Owl is an intelligent stargazing engine that helps users find the best time and place to observe the night sky.

It:

Calculates a Visibility Score (0–100) based on real conditions Finds optimal locations for astrophotography and sky viewing

Supports natural language queries like:

“I want to see the Milky Way near Kitchener this weekend”

Use Cases: 🌌 Milky Way photography planning 🌠 Aurora viewing predictions 🔭 Deep-sky observation timing 🌃 Night sky exploration spots

It also returns:

Best exact coordinates Nearby real-world viewing locations (parks, reserves, lookouts) Weather + sky condition breakdown 🛠️ How we built it Backend FastAPI (Python) for high-performance API system Skyfield for precise astronomical calculations Async processing for parallel location scoring Frontend React + Three.js (React Three Fiber) Real-time 3D sky visualization Interactive celestial motion system Data Sources Open-Meteo → Weather forecasting OpenStreetMap → Location + light pollution NOAA → Aurora predictions Google Gemini → AI-powered sky explanations Core Engine

A grid-based optimization system:

Scans 40–50+ nearby coordinates Scores each location in parallel Returns the best possible sky conditions in the region ⚔️ Challenges we ran into

1. Concurrency & Performance

Running multiple astronomical + weather calculations in parallel required careful throttling to avoid overload.

1. 3D Rendering Stability

Integrating React with Three.js caused rendering and context issues that required architectural refactoring.

1. Data Synchronization

Weather data, celestial calculations, and light pollution maps all update at different rates — syncing them accurately was complex.

1. Balancing Accuracy vs Speed

High-precision astronomy calculations had to be optimized to maintain real-time API response speeds.

🏆 Accomplishments Built a full end-to-end astronomy intelligence system Integrated real-world + astronomical + AI data sources Created a working grid-based sky optimization engine Designed a cinematic 3D interactive sky interface Successfully unified multiple complex APIs into one system 📚 What I learned How to structure scalable backend systems with FastAPI Real-world challenges of combining multiple asynchronous APIs 3D rendering architecture using React Three Fiber Importance of caching and performance optimization How to turn complex scientific data into a user-friendly experience 🔮 What’s next for NightOwl 🤖 Predictive AI for multi-day sky forecasting 🌍 Community-driven sky condition reports 📱 Mobile app version 🛰️ Satellite-based real-time sky tracking 🎯 Personalized recommendations based on user preferences 🧰 Built With FastAPI Python Skyfield React Three.js (React Three Fiber) Open-Meteo API OpenStreetMap Google Gemini API

Built With

• ai
• fastapi
• framer
• react
• three.js
• vite