IoT Smart Greenhouse Monitoring and Automatic Control System

10 jumper wires 150mm male

Node-red

ESP32 DevKit V1 / ESP32-WROOM-32 Development Board

LDR Light Sensor Module

DHT22_Temperature and Humidity Sensor

Wokwi Simulator

Box 525 1% precision resistors - 17 values

OLED Display 0.96-inch I2C SSD1306 128×64

Corrosion-Resistant Soil Moisture Sensor

<html><body>Overview This project presents a simulated IoT smart greenhouse monitoring and automatic control system using an ESP32, MQTT, Wokwi, and Node-RED. The system continuously monitors temperature, air humidity, soil moisture, and light intensity. Based on these sensor values, the ESP32 can automatically control a ventilation fan, a water pump, and a grow light. A Node-RED dashboard displays real-time sensor data and allows users to switch between automatic and manual control modes. MQTT is used for communication between the ESP32 simulation and the Node-RED dashboard. <div id="gallery"><img id="gallery" src="https://projects.arduinocontent.cc/885f7210-fd24-4e4d-8ab9-9dd546c6b2a6.png"/><figcaption></figcaption></div> Main Features <ol><li>Automatic fan control based on temperature and air humidity. </li><li>Automatic water pump control based on soil moisture. </li><li>Automatic grow light control based on light intensity. </li><li>Manual control of the fan, pump, and grow light. </li><li>Automatic and manual operating modes. </li><li>Real-time MQTT communication. </li><li>Two-way synchronization between ESP32 and Node-RED. </li><li>A responsive Node-RED dashboard for desktop and mobile devices. </li></ol>System Architecture The system consists of four main layers: 1. Sensor Layer The DHT22 sensor measures temperature and air humidity. A soil moisture sensor provides the soil moisture value, while a photoresistor or light sensor measures the light intensity. 2. Controller Layer The ESP32 reads the sensor values, applies the automatic control rules, and updates the states of the fan, water pump, and grow light. 3. Communication Layer MQTT is used to transfer sensor data, device commands, and device status messages between the ESP32 and Node-RED. 4. Application Layer Node-RED receives MQTT data and displays it on a real-time dashboard. The dashboard also provides control switches for the greenhouse devices. <div id="gallery"><img id="gallery" src="https://projects.arduinocontent.cc/e9c02bd4-ba81-4ac5-ae13-70581e40f34e.png"/><figcaption></figcaption></div> Hardware Simulation The greenhouse circuit is simulated in Wokwi. The main controller is an ESP32 DevKit V1. The simulated hardware includes: - ESP32 DevKit V1. - DHT22 temperature and humidity sensor. - Soil moisture sensor. - Photoresistor or light sensor. - Fan output. - Water pump output. - Grow light output. - Breadboard and jumper wires. The fan, pump, and grow light can be represented by LEDs or other output components in the Wokwi simulation. <div id="gallery"><img id="gallery" src="https://projects.arduinocontent.cc/b68960f7-46b6-45c6-b00c-b20748a621ab.png"/><figcaption></figcaption></div> Automatic Control Rules The fan is controlled by temperature and air humidity. - The fan turns ON when the temperature is at least 30°C or the air humidity is at least 80%. - The fan turns OFF when the temperature is at most 27°C and the air humidity is at most 70%. The water pump is controlled by soil moisture. - The pump turns ON when soil moisture is at most 35%. - The pump turns OFF when soil moisture is at least 55%. The grow light is controlled by light intensity. - The grow light turns ON when light intensity is below 30%. - The grow light turns OFF when light intensity is above 50%. Node-RED Dashboard <div id="gallery"><img id="gallery" src="https://projects.arduinocontent.cc/df6ad85d-0612-4064-84b1-b6bd946ca656.png"/><figcaption></figcaption></div>Installation and Setup Prerequisites Before running the project, prepare the following software and files: Software: - Node.js LTS. - Node-RED. - FlowFuse Dashboard 2. - A modern web browser. - A Wokwi account. - Access to an MQTT broker. Project files: - ESP32 source code. - diagram.json. - libraries.txt. - Node-RED flow JSON file. Step 1: Install Node-RED npm install -g node-red node-red Open http://localhost:1880. Step 2: Install Dashboard 2.0 In Node-RED, open Manage Palette and install: @flowfuse/node-red-dashboard Step 3: Import the Node-RED Flow Select Menu → Import, upload the provided Node-RED JSON file diagram.json, then click Deploy. Step 4: Set Up the Wokwi Project Add the source files, diagram.json, and libraries.txt. Verify that the GPIO pins match the circuit. Step 5: Run the System Start Node-RED, open the dashboard at <a href="http://localhost:1880/dashboard/greenhouse">http://localhost:1880/dashboard/greenhouse </a>, and then run the Wokwi simulation. </body></html>

IoTGreenHouse

IoT Smart Greenhouse Monitoring and Automatic Control System

A simulated smart greenhouse that monitors environmental conditions and automatically or manually controls a fan, water pump, and grow light using ESP32, MQTT, Wokwi, and Node-RED.