Next-gen flood risk intelligence powered by AI, satellite analytics, and actionable geospatial data science
🌐 Live Demo •
Features •
Architecture •
App Modules •
Tech Stack •
Deploy
“Empowering communities and governments with ultra-granular, predictive flood analytics. Visualize, predict, and act—before disaster strikes.”
AquaVisor is a data-driven, AI-powered flood risk decision platform. Harnessing satellite data, real-time weather signals, and ML-powered analytics, it enables both citizens and officials to predict, visualize, and mitigate the impact of floods—city by city, monsoon by monsoon.
- 📊 Interactive dashboards & live heatmaps
- 🛰️ Satellite image analysis & rainfall maps
- 🤖 Machine Learning–driven flood forecasting
- 🦾 Seamless user UX with modern web tech & sharp UI
Want to see it in action?
🔗 Click here for the live AquaVisor demo
Experience live prediction dashboards, dynamic heatmaps, and satellite-based flood visualization in real time.
- AI Flood Prediction: 98% accuracy with a tuned Random Forest classifier on curated, multi-year India flood data
- Geospatial Visualization: Interactive city-level plots, precipitation analysis, and geo-anchored heatmaps
- Satellite Insights: Dynamic, month-wise overlays using processed NASA GPM/Visual Crossing satellite data
- Real-Time UI: Lightning-fast Flask/Bootstrap frontend with responsive charts and map visualizations
- User-centric: Simple navigation, global city support, robust error handling, and flexible expansion modules
| Module | Description |
|---|---|
index.html |
Stunning landing page showcasing AquaVisor’s mission, demo video, and “Get Started” interface |
plots.html |
Data visualizations for rainfall prediction, flood intensity plots, and historical risk analytics |
heatmaps.html |
Live flood-risk heatmaps across regions and cities |
satellite.html |
Month-wise satellite flood imagery and rainfall overlays |
predicts.html |
Interactive ML-driven prediction tool for city-level flood probabilities |
| Layer | Tools / Frameworks |
|---|---|
| Web Backend | Flask, Gunicorn |
| ML + Data | scikit-learn, pandas, numpy, pickle |
| Visualization | Plotly, D3.js, Custom CSS, Bootstrap 4 |
| Satellite/API | NASA GPM, Visual Crossing, HERE Geocode |
| Infra/Deploy | GitHub, Render, Vercel, PythonAnywhere |
graph TD
A[User] -->|UI| B(Flask Web App)
B -->|Prediction| C(RandomForest ML Model)
B -->|Plots/Heatmaps| D[Plotly/D3 Visualization]
B -->|Satellite Map| E(NASA/Visual Crossing API)
B -->|Geocoding| F(HERE API)
B -->|Database| G[Static/CSV/Cache]