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WaterIT: Intelligent Watering and Monitoring

Demo Screenshot

WaterIT is an automated plant watering system designed to optimize water usage and enhance plant health by utilizing real-time data and AI-generated insights. With a focus on sustainability, WaterIT helps conserve water in agriculture and household gardening through intelligent automation.

🌿 Problem Statement

Global agriculture consumes over 70% of freshwater, and inefficient irrigation leads to 60% water wastage. Meanwhile, 42% of household wastewater remains untreated. WaterIT aims to tackle these issues by automating plant watering based on environmental data.

🌟 Features

  • Automated watering based on real-time soil moisture levels.
  • Real-time monitoring of soil moisture, water usage, temperature, and humidity.
  • AI-powered insights for plant health using Google Generative AI.
  • Web dashboard for easy control and data visualization.

🚀 How It Works

  1. Hardware:

    • Arduino UNO: Manages the water pump, soil moisture sensor, and servo motor.
    • Soil Moisture Sensor: Continuously monitors soil moisture and sends readings to the Arduino.
    • Water Pump: Activated by the Arduino when the soil is dry and deactivated once optimal moisture is reached.
    • Servo Motor: Moves to simulate a mechanical action when the pump turns off, enhancing the interaction.
    • Relay: Controls the power to the water pump based on moisture sensor data.

  2. Software:

    • The Flask app communicates with the Arduino via USB to receive moisture data and control the water pump.
    • Data such as soil moisture levels and water usage is stored in SQLite databases (moisture_data.db and pump_data.db).
    • Real-time environmental data like temperature and humidity is fetched using the OpenWeatherMap API.
    • AI-generated insights on plant care are provided using Google Generative AI, offering actionable advice based on the plant’s condition and external factors.

  3. Water Usage Calculation:

    • The water used is calculated based on the duration the pump is active, with a flow rate of 0.0025 liters per second.
    • After watering, the system calculates and logs the total water consumption, helping monitor usage over time.

  4. Mechanical Movement:

    • When the pump turns off, the servo motor rotates 180 degrees, simulating a visual indicator of the water flow stopping.
    • After a short delay, the motor returns to its original position, ready for the next cycle.

💻 Installation

  1. Clone the repository:

    git clone https://github.com/ZephyrusBlaze/WaterIT.git
cd waterit

  2. Install dependencies:

    pip install -r requirements.txt

  3. Set up environment variables:

    • OpenWeatherMap API key
    • Google Gemini API key for AI insights

  4. Run the Flask app:

    python app.py

🏗️ Project Structure

.
├── LICENSE
├── README.md
├── app.py
├── arduino-code
│   └── code.ino
├── moisture_data.db
├── pump_data.db
├── requirements.txt
├── static
│   └── images
│       ├── ai.png
│       ├── dashboard.png
│       └── graphs.png
└── templates
    ├── ai.html
    ├── base.html
    ├── dashboard.html
    ├── graphs.html
    └── index.html

📚 Libraries & Tools

  • Flask: Web framework for the frontend and backend.
  • Datetime: For handling timestamps.
  • Requests: For fetching weather data from OpenWeatherMap.
  • PySerial: To communicate with the Arduino via USB.
  • Google Generative AI: For generating AI insights on plant care.

📈 Future Enhancements

  • Wireless Communication: Integrating wireless sensors for better scalability.
  • Plant Species Detection: Improving AI insights by factoring in specific plant needs.

📄 License

This project is licensed under the Apache 2.0 License.