Project Aether 🌌

An innovative educational platform that spreads awareness about space weather through immersive storytelling, interactive experiences, and AI-powered learning.

🌟 Overview

Project Aether combines cutting-edge technology with engaging narratives to educate users about space weather phenomena. Meet Aether, a 1000-year-old cosmic Phoenix who has witnessed countless space weather events and is here to share his wisdom through interactive conversations, curated stories, games, and scientific predictions.

✨ Features

1. Home Dashboard

Live space weather data visualization from NASA sources with real-time updates and project introduction.

2. Aether's Tales

• AI Chatbot: Interact with Aether, an ancient Phoenix powered by Gemini API with ElevenLabs voice synthesis
• Aether's Library: Curated collection of real space weather event stories narrated in Aether's mystical voice, available as interactive cards with audio playback

3. Interactive Game

An educational adventure game where you play as an astronaut exploring space events:

• Learn about various space weather phenomena
• Battle enemies while discovering cosmic mysteries
• Complete a quiz to test your knowledge
• Guided by Aether throughout your journey

4. Aurora Prediction Model

• Interactive 3D Earth visualization
• Click any location to predict Aurora intensity
• Powered by Random Forest machine learning models
• Real-time predictions based on longitude and latitude

5. User Survey

Collect data on public knowledge about space weather to measure educational impact.

📁 Project Structure

Project-Aether/
├── ML/
│   ├── Aurora_model_training.ipynb    # Model training notebook
│   ├── aurora_model_temp.pkl          # Random Forest model (pickle)
│   └── Aurora_model.onxx              # ONNX model for web deployment
│
├── backend/
│   ├── .env                           # API keys (Gemini, ElevenLabs)
│   ├── server.js                      # Backend server
│   ├── package.json
│   ├── package-lock.json
│   └── .gitignore
│
├── frontend/
│   ├── assets/
│   │   ├── comic/                     # Comic panels
│   │   ├── stories/                   # MP3 audio files for stories
│   │   └── *.png                      # Aether character images
│   ├── css/
│   │   ├── dashboard.css
│   │   └── style.css
│   ├── js/
│   │   ├── dashboard.js
│   │   ├── earth3d-space.js
│   │   ├── earth3d.js
│   │   ├── main.js
│   │   ├── phoenix.js
│   │   └── sun3d.js
│   ├── index.html
│   ├── server.js
│   ├── package.json
│   ├── package-lock.json
│   └── .gitignore
│
├── game/
│   └── Aether.exe                     # Educational space game
│
├── README.md
├── requirements.txt
└── start-all.js                       # Unified startup script

🚀 Getting Started

Prerequisites

• Node.js (v14 or higher) Link Here

• npm (comes with Node.js)

• Python dependencies for ML model:

  • numpy>=1.21.0
  • scikit-learn>=1.0.0

Installation

1. Clone the repository

   git clone https://github.com/Kareem-Taha-05/4Bit-Orbit
   cd 4Bit-Orbit

2. Install backend dependencies

   cd backend
   npm install
   cd ..

3. Install frontend dependencies

   cd frontend
   npm install
   cd ..

4. Configure environment variables

   Create a .env file in the backend/ directory with:

   GEMINI_API_KEY=your_gemini_api_key
   ELEVENLABS_API_KEY=your_elevenlabs_api_key
   ELEVENLABS_VOICE_ID=your_voice_id
   

5. Start the application

   node start-all.js

6. Access the application

   Open your browser and navigate to:

   http://localhost:8000/
   

🤖 Machine Learning Model

The Aurora prediction model uses Random Forest algorithm trained on geospatial data to predict Aurora intensity based on:

• Longitude: Geographic longitude position
• Latitude: Geographic latitude position

Two model formats are provided:

• PKL format: Standard scikit-learn pickle format
• ONNX format: Optimized for web deployment with better performance

🎮 Game Installation

The Aether game executable is located in the game/ folder. Download and run Aether.exe to begin your educational space adventure.

🛠️ Technologies Used

• Frontend: HTML5, CSS3, JavaScript, Three.js (3D visualizations)
• Backend: Node.js, Express.js
• AI/ML:
  • Gemini API (conversational AI)
  • ElevenLabs (voice synthesis)
  • scikit-learn (Aurora prediction)
  • ONNX Runtime (model deployment)
• Game Development: Unity/Custom game engine

📚 Educational Impact

Project Aether aims to:

• Increase public awareness of space weather phenomena
• Make complex scientific concepts accessible through storytelling
• Provide interactive learning experiences
• Collect data on space weather knowledge gaps

👥 Authors

• Kareem Taha
• Bassel Shaheen
• Karim Hassan
• Hakeem Taha

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📄 License

This project is licensed under the MIT License.

🙏 Acknowledgments

• NASA for space weather data APIs
• Gemini API for conversational AI capabilities
• ElevenLabs for voice synthesis technology

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Experience the cosmos through Aether's eyes. Learn, explore, and understand the weather of space. 🌠