🌊 DripTect

Smart Flood Detection & Prediction System

🚀 An IoT + AI powered platform for real-time flood monitoring, weather visualization, and predictive risk analysis.

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📖 Overview

DripTect integrates ESP32 IoT sensors, a Flask + Machine Learning backend, and a Next.js dashboard to predict and visualize flood risk.
It empowers communities with real-time data, historical insights, and early alerts to build climate resilience.

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🏗️ System Architecture

graph TD
    A[🌱 ESP32 Sensors] -->|Soil Moisture, Temp, Humidity, Rainfall, Distance| B[(📡 Flask API)]
    B --> C[🤖 ML Model – Random Forest]
    C --> D[(📊 Data Storage)]
    D --> E[🖥️ Next.js + Tailwind Dashboard]
    E --> F[🌍 Globe with Heatmap + Graphs]
    C --> G[⚠️ Flood Risk Prediction Engine]
    G --> E

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✨ Features

• 🌱 IoT Sensor Network → Soil moisture, humidity, temperature, rainfall, water level
• ⚡ Real-time Data Processing → ESP32 → Flask → ML model
• 🤖 Machine Learning → Random Forest predicts flood risk severity
• 🖥️ Interactive Dashboard → Next.js + Tailwind + Shadcn UI
• 🌍 3D Rotating Globe Heatmap → Weather across India (OpenWeather API)
• 📊 Historical Trends → Graphs for past 24h & 7d
• ⚠️ Risk Analysis → "View Risk" button shows flood probability

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⚙️ Tech Stack

Hardware → ESP32, DHT11, Soil Moisture, Rain Sensor, Ultrasonic
Backend → Flask + Python (Random Forest ML Model)
Frontend → Next.js, TailwindCSS, Shadcn UI, Recharts, Framer Motion
API → OpenWeather API
Database → Pandas (logs), PostgreSQL (scalable option)

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📊 Workflow

1. ESP32 Sensors collect environmental data.
2. Flask Backend stores & forwards to ML model.
3. ML Model predicts flood risk levels.
4. Next.js Dashboard displays:
   • 🌍 Rotating globe with heatmap
   • 📊 Weather + API insights
   • ⏳ Historical 24h & 7d graphs
   • ⚠️ Flood Risk prediction card

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👥 Team & Collaborators

• 👨‍🔬Aryan Ghosh
• 👨‍🔬Surajit Ray
• 👨‍🔬Anshley Mukherjee
• 👨‍🔬Debnanda Datta

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🚀 Getting Started

🔹 Backend (Flask)

cd Flood Predictor Model ML
pip install -r requirements.txt
python app.py

🔹 Frontend (Next.js)

cd frontend
npm install
npm run dev

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🔑 API Keys

• Get your OpenWeather API Key → OpenWeather
• Add it to .env.local:

NEXT_PUBLIC_OPENWEATHER_API_KEY=your_api_key_here

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📈 Example Prediction Log

====================================================================================================
[2025-08-28 10:15:32]  Prediction Log
====================================================================================================
 No  Soil Moisture (%)  Temperature (°C)  Humidity (%)  Rainfall (mm)  Distance (cm)  Prediction
  1              45.00              29.5         72.0          120.0          30.4     FLOOD LIKELY
====================================================================================================

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🗺️ Roadmap

• ESP32 IoT sensor integration
• Flask API + ML Model
• Next.js Dashboard + Globe Visualization
• SMS / WhatsApp Flood Alerts
• Cloud Deployment (AWS/GCP)
• Mobile App (React Native)

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📜 License

MIT License © 2025 DripTect Team

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⭐ If you find this project useful, consider giving it a star on GitHub to support us!

🌍 Together for flood awareness & climate resilience 💧 ✨ DripTect – Because every drop counts, and every life matters. 🌊