KUCUR (Kontrol Ultracerdas Curah dan Rembes)

IoT-Based Smart Irrigation System with Real-Time Monitoring and Automation

KUCUR is a comprehensive IoT smart irrigation system designed to monitor soil conditions and automate watering schedules. The system provides real-time monitoring, intelligent automation, remote control via a Web Dashboard, Telegram Bot integration, and a dedicated Chatbot for user interaction.

🚀 Features

• Real-Time Monitoring: Monitor sensor data and pump status in real-time via MQTT protocol.
• Smart Automation & Scheduling: Set up rule-based automation or time-based watering schedules.
• Web-Based Dashboard: A responsive user interface to control and monitor the entire irrigation system.
• Telegram Bot Integration: Receive alerts and control the irrigation system directly from Telegram.
• AI/Chatbot Assistant: Built-in chatbot interface to interact with the system easily.
• Irrigation History: Logs all watering activities and sensor metrics for historical analysis.
• IoT Simulator: Built-in simulator (iot-simulator.js) to test the backend and UI without requiring physical hardware.

🛠️ Technology Stack

• IoT Hardware: ESP8266 / ESP32 (C++ / Arduino IDE)
• Backend: Node.js, Express.js
• Communication Protocol: MQTT (Message Queuing Telemetry Transport)
• Frontend: HTML5, CSS3, Vanilla JavaScript
• Integrations: Telegram Bot API

📂 Project Structure

KUCUR/
├── backend/                # Node.js server API, MQTT client, and Bot
│   ├── src/
│   │   ├── controllers/    # API business logic
│   │   ├── database/       # Database configuration (db.js)
│   │   ├── models/         # Database models (IrrigationHistory.js)
│   │   ├── routes/         # Express routes (auth, schedule, chat, etc.)
│   │   ├── server.js       # Main entry point for the backend
│   │   ├── mqttClient.js   # MQTT connection handler
│   │   ├── telegram-bot.js # Telegram bot logic
│   │   └── iot-simulator.js# Hardware simulator for testing
├── web-ui/                 # Frontend Web Dashboard
│   ├── css/, js/           # Styling and frontend logic
│   ├── index.html          # Login / Landing page
│   ├── dashboard.html      # Main monitoring dashboard
│   ├── automation.html     # Scheduling and automation settings
│   ├── chatbot.html        # Smart assistant interface
│   └── history.html        # Irrigation data logs
└── EspClient/              # Microcontroller source code
    └── EspClient.ino       # ESP8266/ESP32 sketch for MQTT and sensors

⚙️ Setup & Installation

1. Backend Setup

1. Navigate to the backend directory:

   cd backend/src

2. Install dependencies:

   npm install

3. Configure environment variables: Copy .env.example to .env and fill in your configuration details (MQTT Broker, Telegram Token, Database URI, etc.).

   cp .env.example .env

4. Start the server:

   npm start
   # or run "node server.js"

2. Frontend Setup

The frontend uses standard web technologies. You can serve the web-ui directory using any web server (e.g., VS Code Live Server, Nginx, or a simple Python server).

cd web-ui
python3 -m http.server 8080

Access the dashboard via http://localhost:8080.

3. IoT Hardware Setup

1. Open EspClient/EspClient.ino using the Arduino IDE.
2. Install the necessary libraries (e.g., PubSubClient for MQTT, WiFi/ESP8266WiFi).
3. Update the WiFi credentials and MQTT Broker details in the .ino file.
4. Flash the code to your ESP8266 or ESP32 board.

4. Running the Simulator (Optional)

If you don't have the hardware ready, you can test the system using the built-in IoT Simulator:

cd backend/src
node simulator-cli.js

📡 MQTT Topics Architecture

(Adjust the topics below based on your actual mqttClient.js and EspClient.ino configuration)

• kucur/sensor/data - Publishes soil moisture, temperature, etc.
• kucur/pump/status - Publishes the current state of the water pump.
• kucur/pump/control - Subscribed by the ESP to trigger the pump manually.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page if you want to contribute.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.