☀️ SolarSentinel AI

AI-Powered Solar Flare Forecasting & Nowcasting using ISRO's Aditya-L1 SoLEXS & HEL1OS Data

Transforming scientific solar telemetry into explainable, AI-driven space weather intelligence.

🛰 Built for Bharatiya Antariksh Hackathon 2026

🌐 Live Demo: https://solar-sentinel-ai1.vercel.app

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📸 Platform Preview

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🚀 Overview

SolarSentinel AI is an end-to-end Space Weather Intelligence Platform built to forecast and nowcast solar flares using Aditya-L1 SoLEXS (Soft X-Ray) and HEL1OS (Hard X-Ray) observations.

The platform automates the complete scientific workflow—from telemetry ingestion and preprocessing to AI inference, explainability, visualization, and Earth impact analysis—through an interactive cloud-native dashboard.

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💡 Why SolarSentinel AI?

• Combines SoLEXS + HEL1OS observations for richer solar event analysis.
• Bridges scientific telemetry with Explainable AI for transparent predictions.
• Automates the complete telemetry-to-insight pipeline.
• Synchronizes forecasting, analytics, observatory, explainability, and mission dashboards automatically after every dataset upload.

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🎯 Solution Highlights

✅ Read & process Aditya-L1 SoLEXS & HEL1OS Level-1 datasets

✅ Combined Soft + Hard X-Ray analysis

✅ AI-powered Solar Flare Nowcasting

✅ Probabilistic Solar Flare Forecasting

✅ Explainable AI using SHAP

✅ Automated telemetry preprocessing pipeline

✅ Scientific telemetry visualization

✅ Searchable telemetry & prediction database

✅ Interactive analytics & mission dashboards

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✨ Core Features

Module	Capabilities
🛰 Mission Dashboard	Mission health, solar activity index, flare probability, operational status
☀️ Solar Observatory	SoLEXS & HEL1OS visualization, waveform analysis, historical telemetry
🤖 AI Forecasting	LightGBM inference, flare probability estimation, confidence scoring
⚡ Nowcasting	Automated flare detection using combined telemetry signals
🧠 Explainable AI	SHAP feature importance & transparent prediction reasoning
🌍 Earth Impact	GPS disruption, satellite risk, communication impact estimation
📊 Analytics	Historical trends, prediction insights, telemetry statistics
📂 Dataset Manager	CSV upload, validation, preprocessing, metadata, history, deletion
🔌 REST APIs	Prediction, telemetry, analytics, datasets & health monitoring

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📊 Scientific Dataset

Dataset	Description
SoLEXS (Level-1)	Solar Low Energy X-Ray Spectrometer
HEL1OS (Level-1)	High Energy L1 Orbiting X-Ray Spectrometer
Storage	MongoDB Atlas
Input Format	CSV

Dataset Pipeline

• CSV Upload
• Validation
• Cleaning
• Time Synchronization
• Feature Engineering
• Database Storage
• AI Inference
• Dashboard Synchronization

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🤖 AI Workflow

          SoLEXS + HEL1OS
                  │
                  ▼
         Scientific Telemetry
                  │
                  ▼
          CSV Upload / API
                  │
                  ▼
      Validation & Preprocessing
                  │
                  ▼
 Physics + Temporal Feature Engineering
                  │
                  ▼
         ML Inference Engine
                  │
        ┌─────────┴─────────┐
        ▼                   ▼
   Solar Nowcasting    Solar Forecasting
                  │
                  ▼
        SHAP Explainability
                  │
                  ▼
     FastAPI Backend Services
                  │
                  ▼
 Mission Dashboard • Observatory
 Analytics • Earth Impact
 Dataset Manager

Every uploaded dataset automatically refreshes forecasting, explainability, analytics, observatory visualizations, and mission monitoring without manual intervention.

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⭐ Innovation Highlights

• Combined Soft + Hard X-Ray telemetry analysis.
• End-to-end automated telemetry-to-insight pipeline.
• Explainable AI with SHAP for scientific transparency.
• Physics-aware & temporal feature engineering.
• Automatic synchronization across all dashboards.
• Cloud-native, modular, production-ready architecture.

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🛠 Tech Stack

Category	Technologies
Frontend	React • TypeScript • Vite • Tailwind CSS
Backend	FastAPI • Python • Uvicorn
Machine Learning	LightGBM • SHAP • Scikit-learn
Visualization	Recharts
Data Processing	Pandas • NumPy • SciPy
Database	MongoDB Atlas
Deployment	Vercel • Railway

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📂 Project Structure

SolarSentinel-AI
│
├── src/
│   ├── components/
│   ├── hooks/
│   ├── lib/
│   └── pages/
│
├── backend/
│   ├── api/
│   ├── ml/
│   ├── repositories/
│   ├── services/
│   └── configs/
│
├── docs/
└── artifacts/

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🚀 Getting Started

# Clone Repository
git clone https://github.com/<your-username>/SolarSentinel-AI.git

cd SolarSentinel-AI

# Frontend
npm install
npm run dev

# Backend
cd backend
pip install -r requirements.txt

uvicorn backend.app.main:app --reload

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☁️ Deployment

Component	Platform
🌐 Frontend	Vercel
⚡ Backend	Railway
🗄 Database	MongoDB Atlas
📖 API Documentation	/docs (Swagger UI)

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🔮 Future Scope

• Live Aditya-L1 telemetry integration
• Transformer/LSTM-based forecasting
• Real-time solar event alerts
• Advanced anomaly detection
• Multi-mission support
• Global space weather visualization

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👥 Team

Developed for Bharatiya Antariksh Hackathon 2026.

SolarSentinel AI demonstrates how Artificial Intelligence, Explainable Machine Learning, and scientific telemetry can be integrated into a unified platform for intelligent space weather monitoring, solar flare forecasting, and decision support inspired by ISRO's Aditya-L1 Mission.