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🌊 FloodAI Hackathon - Epsilon Team

FloodAI Python License: MIT

A complete end-to-end AI-driven solution developed at the FloodAI Hackathon 2024 by Team Epsilon. Our system focuses on flood prediction, risk assessment, satellite image analysis, and real-time alert generation for Mumbai using meteorological, topographical, and urban data sources.


🚀 Features

  • 📊 Rainfall Prediction Model:
    Time series model trained on IMD data to forecast rainfall in mm.

  • 🗺️ Flooded Area Segmentation:
    Semantic segmentation using satellite images to identify flooded regions.

  • 🌧️ Risk Assessment System:
    Combines rainfall, elevation, drainage network, and land use data to compute flood risk across Mumbai.

  • 📍 Interactive Map & Alert System:
    Web-based dashboard to visualize risk zones and push alerts to residents.

  • 🧠 Integrated AI Pipeline:
    Combines predictive models, geospatial analysis, and real-time user interaction.


🏆 Achievements

🥉 Secured 3rd place at FloodAI Hackathon organized by IIT Gandhinagar and IIT Bombay Climate Studies Department.
🔬 Developed a research-backed multi-model architecture within 36 hours.
📍 Mumbai-focused system with real-world applicability.



🧠 Tech Stack

  • Languages: Python, JavaScript (for dashboard)
  • Libraries: TensorFlow, Keras, OpenCV, Scikit-learn, XGBoost, Pandas, NumPy, Matplotlib, Rasterio
  • Geospatial Tools: QGIS, Folium, GeoPandas, Shapely
  • Frontend: Leaflet.js, Streamlit
  • Other: Google Earth Engine, SRTM DEM, IMD Rainfall Data

⚙️ How to Run

  1. Clone the repository
git clone https://github.com/DeepMathukiya/FloodAI_Hackathon_Epsilon.git
cd FloodAI_Hackathon_Epsilon
  1. Run Backend
cd backend
python app.py
  1. Run Frontend
cd frontend
yarn run dev --host

Demo

demo

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Image Segementation Notebook Link || MLP Link (https://github.com/naim195/ML-Assignment-3)

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