In the world of IoT and smart agriculture, monitoring soil moisture is a key factor for optimizing water usage and ensuring the health of plants. Soil moisture sensors are essential tools that measure the amount of water present in the soil, and with the ESP32, these sensors can be integrated into automated systems to help manage irrigation, gardening, or agricultural processes. By using the ESP32 microcontroller and a soil moisture sensor, we can easily collect real-time data on the soil’s moisture levels and trigger alerts or automated actions based on predefined thresholds. This tutorial walks you through how to set up an Arduino-compatible soil moisture sensor module with the ESP32, leveraging MicroPython to read and interpret the data.

The Arduino Soil Moisture Sensor Module is a widely used component in various DIY projects. It works by measuring the conductivity between two electrodes, which changes with the moisture content of the soil. This analog reading is then processed by the ESP32 to determine if the soil requires watering. In this tutorial, you’ll not only learn how to wire the sensor to the ESP32 but also how to calibrate it for accurate readings. For more detailed specifications, you can refer to the Arduino Soil Moisture Sensor Datasheet for additional information on its technical features.

Table of Contents

Materials Needed:

1. ESP32 Development Board
   We’ll be using the ESP32 to read data from the soil moisture sensor. It’s a powerful board with Wi-Fi and Bluetooth capabilities, perfect for IoT applications.
2. Soil Moisture Sensor
   A common soil moisture sensor typically has two electrodes for measuring the soil’s conductivity, which varies with the moisture content.
3. Jumper Wires
   For connecting the sensor to the ESP32.
4. Breadboard (Optional)
   To make wiring simpler and more organized.
5. MicroPython installed on your ESP32.

Wiring the Soil Moisture Sensor to the ESP32:

1. Connect the Soil Moisture Sensor to the ESP32:
   • VCC (Sensor) → 3.3V (ESP32)
   • GND (Sensor) → GND (ESP32)
   • Analog Output (A0) → GPIO34 (ESP32) (Note: You can also use other GPIO pins with ADC functionality, but we’ll use GPIO34 here for simplicity.)
2. The soil moisture sensor typically outputs an analog signal that represents the moisture level. This is read by the ESP32’s ADC (Analog-to-Digital Converter) pins.

Setting Up MicroPython on the ESP32:

If you haven’t already, you’ll need to install MicroPython on your ESP32. Follow these steps to get it set up:

1. Download and install Thonny or uPyCraft IDE for MicroPython programming.
2. Flash the latest MicroPython firmware onto the ESP32 using the appropriate tool.
3. Connect your ESP32 to the computer via USB and configure it to communicate with the IDE.

Writing the MicroPython Code:

Pin It!

Now, let’s write a simple script to read the soil moisture level and print it to the console. We’ll also add a threshold and provide feedback via the serial monitor if the soil moisture is too low.

from machine import Pin, ADC
import time

# Set up the analog pin for the soil moisture sensor
moisture_sensor = ADC(Pin(34))  # Using GPIO34 for analog input
moisture_sensor.atten(ADC.ATTN_0DB)  # Set the ADC input range to 0-3.3V

# Threshold value for soil moisture (this can be adjusted based on your sensor)
MOISTURE_THRESHOLD = 1000  # Values may range between 0 and 4095, higher values indicate more moisture

while True:
    # Read the analog value from the sensor
    moisture_level = moisture_sensor.read()

    # Print the moisture level to the console
    print("Soil Moisture Level:", moisture_level)

    # Check if the moisture level is below the threshold
    if moisture_level < MOISTURE_THRESHOLD:
        print("Warning: Soil is too dry! Consider watering.")
    else:
        print("Soil moisture is sufficient.")

    # Wait for 2 seconds before taking the next reading
    time.sleep(2)

How the Code Works:

1. Setup ADC Pin:
   The moisture_sensor = ADC(Pin(34)) line sets GPIO34 as an analog input. The ESP32 has several ADC pins; in this case, we use GPIO34, which is often free and accessible.
2. Reading Sensor Values:
   The moisture_sensor.read() function reads the analog value from the soil moisture sensor. The sensor outputs a value between 0 and 4095, where a higher value typically indicates more moisture in the soil.
3. Moisture Level Check:
   The code checks if the moisture level is below a set threshold (MOISTURE_THRESHOLD). If the value is lower, it prints a warning message suggesting that the soil might need watering.
4. Delay:
   The time.sleep(2) command pauses the program for 2 seconds before reading the sensor again.

Testing and Calibration:

• You can test the sensor by inserting it into a pot of soil. The reading will fluctuate as the moisture content of the soil changes.
• To calibrate, you may want to check the sensor’s readings in both dry and wet soil and adjust the MOISTURE_THRESHOLD accordingly.

Optional Enhancement:

You can add an LED or a relay to trigger an alert when the soil moisture falls below the threshold. For example, you could connect an LED to GPIO2, which would light up when the soil is dry:

from machine import Pin

led = Pin(2, Pin.OUT)  # GPIO2 for the LED

while True:
    moisture_level = moisture_sensor.read()

    if moisture_level < MOISTURE_THRESHOLD:
        led.on()  # Turn the LED on when the soil is too dry
    else:
        led.off()  # Turn the LED off when the moisture level is sufficient

    time.sleep(2)

Conclusion:

By following this guide, you’ve learned how to set up a soil moisture monitoring system using the ESP32 and an Arduino-compatible soil moisture sensor module. This system can be integrated into smart gardening and agricultural projects, providing insights into the soil’s health and enabling efficient water management. With the ability to customize the moisture threshold and automate watering systems or send alerts when moisture levels are low, this project can help save water and promote healthier plant growth. Whether you’re a hobbyist looking to automate your garden or a farmer looking for a reliable system, this setup offers a flexible solution for monitoring soil conditions in real-time.