By me VVIJK (jb225ps)
In this tutorial, you will learn how to create a soil moisture sensor IoT device using a Raspberry Pico W microcontroller, a soil moisture sensor, a DHT-11 sensor, a breadboard, MicroPython, and some jumper wires. By the end of this tutorial, you'll have a functioning device that can measure soil moisture levels and send the data to a remote server for analysis and monitoring.
Estimated time of the project is about 5 hrs (depending on your level of knowledge ofc)
The purpose of this IoT device is to measure and monitor soil moisture levels, humidity, and temperature in real-time. By placing the sensor within the soil, it continuously provides readings that indicate the moisture content. This information can be further analyzed to optimize the conditions for the plant and improve its health.
For this project, you will need the following materials:
Description: The Raspberry Pi Pico WH is a microcontroller board based on the RP2040 chip. The Pico WH variant includes pre-soldered headers, making it convenient for a breadboard-based project like this. It can be programmed using MicroPython, C/C++, or other compatible programming languages.
- RP2040 CPU
- ARM Cortex-M0+ 133MHz
- 256kB RAM
- 30 GPIO pins
- 2MB on-board QSPI Flash
- CYW43439 wireless chip
- IEEE 802.11 b/g/n wireless LAN
Description: A breadboard is a versatile prototyping tool used for building and testing electronic circuits. It consists of a grid of holes into which electronic components can be inserted and interconnected without the need for soldering. The breadboard is used as a platform to connect the Raspberry Pi Pico and the sensors using jumper wires.
Description: The DHT-11 sensor is a low-cost sensor that measures temperature and humidity. The sensor operates within a specific temperature and humidity range and provides reasonable accuracy for most general-purpose applications.
| Item | Cost (SEK) | Link (Not affiliated) |
|---|---|---|
| Raspberry Pi Pico WH | 109:- | ElectroKit |
| Breadboard | 69:- | ElectroKit |
| DHT-11 Sensor | 49:- | ElectroKit |
| Capacitive Soil Moisture Sensor | 68:- | Amazon |
| Jumper Wires | 29:- | ElectroKit |
| Micro USB Cable | 120:- | Kjell&Co |
This tutorial is for Windows but is pretty similar on other operating systems.
Download and install Node.js from HERE.
Download and install VS Code from HERE.
Open VS Code and go to the extensions manager. Search for the Pymakr plugin and install it.
Download the Micropython firmware for Raspberry Pi Pico WH from HERE. Make sure to download the latest uf2 file under releases.
Connect the micro-USB cable to your Raspberry Pi Pico. (Don't put the other end in the PC yet..)
- While holding down the BOOTSEL button on the RPi Pico (the small button close to the micro-USB port), connect the other end of the USB cable to your computer.
- Release the button after you see your device pop up on your computer.
- In your file system, you will see a new drive called RPI-RP2 which is your RPi Pico device. Paste the uf2 file you previously downloaded and add it to the device.
- The Raspberry Pi Pico will automatically disconnect from your computer and reconnect. Now your RPi Pico is flashed with Micropython and ready to go.
Start by connecting the Raspberry Pi Pico and the sensors to the breadboard, then connect all the wires. You can arrange the components as desired, but make sure to connect everything correctly. Here is a circuit diagram showing how I did it:
The project's code consists of four Python files. You can either use the git pull command to fetch the files or manually copy them from this directory and paste them into your IDE. Here is a brief overview of what each file contains:
- boot.py: This is where the Pico connects to Wi-Fi. It imports the Wi-Fi credentials from the keys.py file and sets up a connection to the Wi-Fi network.
- keys.py: This file holds all your crucial credentials, including Wi-Fi credentials and Adafruit credentials.
- mqtt.py: This file contains the MQTT library used for sending data to Adafruit.
- main.py: This is the main program file. It starts and runs the program, collects data from the sensors, and sends it to Adafruit.
I have chosen Adafruit as the platform to display the data. Adafruit provides a simple and easy way to display data in real-time online. They offer a free plan that allows 10 feeds with 30 entries per minute and a storage period of 30 days, which is suitable for this project.
To transmit data to the Adafruit platform, Wi-Fi is used since the device will be connected at home with stable Wi-Fi connectivity. The MQTT (Message Queuing Telemetry Transport) protocol is chosen for data transmission due to its lightweight and secure nature.
Data is collected every 20 seconds, but you can easily change this interval in the main.py file by modifying the RANDOMS_INTERVAL variable.
# Variables
RANDOMS_INTERVAL = 20000 # (milliseconds). How often data is sent to Adafruit
last_random_sent_ticks = 0 # (milliseconds). Used to keep track of the last time data was sent to Adafruit IO
temp_sensor = dht.DHT11(machine.Pin(27)) # DHT11 Constructor
soil_sensor = ADC(machine.Pin(26)) # Capacitive Soil Moisture Sensor v1.2
moist_wet=13347 # Moisture sensor calibration.
moist_dry=42986In the code block above, which is from the main.py file, you can see two variables: moist_wet and moist_dry. These variables are used for calibrating and fine-tuning the soil moisture sensor.
I recommend calibrating your "moisture-guardian" before using it. To do this, start by placing the soil sensor in a glass of water and read the data. Then, adjust the moist_wet variable so that when the sensor is in the water, the printed data is as close to 100 as possible. Next, dry off the sensor and adjust the moist_dry variable so that it's as close to 0 as possible.
For presenting the data, three line graphs and a matching gauge are used. The temperature has two limits: 21°C and 26°C. The temperature range between these limits is shown in green, indicating an optimal temperature. If the temperature exceeds 26°C, it turns red to indicate that it's too hot, and if it goes below 21°C, it turns blue to indicate that it's too cold.
Here is the final design of the project.
