ExoQuest is an interactive AI/ML-powered web demo that simulates how machine learning can detect exoplanets using telescope flux data. Built with Streamlit, it provides a step-by-step workflow to load data, train a model, and test new inputs interactively.
- Load Sample Data
The app loads a dataset with flux readings from a telescope:
Flux_1, Flux_2, and Flux_3 represent light intensity variations.
Exoplanet (0 or 1) indicates whether a planet was detected based on flux changes.
Data visualization helps users understand the pattern behind exoplanet detection.
- Train AI Model
A simple but powerful machine learning classifier is trained on the loaded data.
Displays model accuracy (as seen in the demo — 100% accuracy on the sample data).
Uses supervised learning to classify whether an exoplanet exists or not.
- Try Your Own Input
Users can manually adjust Flux_1, Flux_2, and Flux_3 sliders.
The model instantly predicts:
✅ Exoplanet Detected
❌ No Exoplanet Detected
Interactive feedback allows users to experiment with telescope data intuitively.
Frontend & UI : Streamlit
Programming Language: Python
ML Algorithm : Scikit-learn (classification model) Data Visualization : Pandas, Matplotlib/Seaborn (optional)
Load Data → Simulated telescope readings are loaded.
Train Model → AI model learns relationships between flux patterns and exoplanet presence.
Predict → User inputs new flux values to get instant predictions.
| Flux_1 | Flux_2 | Flux_3 | Exoplanet |
|---|---|---|---|
| 0.8 | 0.2 | 0.7 | 1 |
| 0.5 | 0.1 | 0.3 | 0 |
| 0.9 | 0.6 | 0.4 | 0 |
| 0.3 | 0.8 | 0.95 | 1 |
| 0.3 | 0.4 | 0.2 | 0 |
# 1️⃣ Clone the repository
git clone https://github.com/your-username/ExoQuest.git
cd ExoQuest
# 2️⃣ Install dependencies
pip install -r requirements.txt
# 3️⃣ Run the Streamlit app
streamlit run app.pyThen open your browser at http://localhost:8501.
Integration with real telescope datasets (e.g., Kepler or TESS missions).
Neural network-based model for complex pattern detection.
Interactive data visualization dashboards.
Exportable report summaries of predictions.
Developed by : Joshna Maria Joseph
Purpose : To demonstrate how AI/ML techniques can identify exoplanets from telescope signal data.