# Sensors for soil and water

This page compiles examples of sensors for soil and water monitoring, developed during the GROW project.

The following research has been funded by the Grow Observatory project under European Community’s H2020 Programme under Grant Agreement No. 690199.

The Chirp Sensor is a low cost moisture and temperature sensor developed by WeMakeThings: a hackers and engineers collective based in Vilnius, Lithuania. Their hardware and software are fully open-source, and it can be easily integrated but also replicated and customized for new projects.

The sensor uses capacitive sensing to measure soil's moisture. A 1MHz square wave is output from the chip through a resistor into a big pad that, together with the surrounding ground plane, it forms a parasitic capacitor. The resistor and the capacitor create a low pass filter which cut-off frequency changes with changing capacitance. The soil around the sensor acts as an electrolyte whose dielectric constant changes depending on the amount of moisture in it, so the capacitance of our makeshift capacitor changes too. The filtered square wave is then fed into a peak detector formed of out a diode and a capacitor. An ADC measures this voltage in the microcontroller. The sensor also includes a temperature sensor with a calculated absolute measurement accuracy around 2%.

There are different versions of the Chirp sensor, and for this application we chose the Chirp I2C sensor. The sensor was integrated on to the SCK's firmware, and it is automatically recognized by the board once it is plugged into the SCK using the Aux sensor connector. A Grove 4 pin Female Jumper to Grove will need to be used with the sensor to connect it to the SCK. The original Chirp sensors come coated with PRF202 - a moisture resistant varnish for electronics, but it is not enough for actual deployment. For such, one must add additional protection to the whole sensor. We suggest polyester or epoxy resin. However, you must note that sensitivity of the sensor will decrease depending on how thick the layer you are going to apply and might need to be recalibrated. We also recommend covering the electronics with heat shrink to fully waterproof the sensor. Some versions already include a pre-ruggedized sensor, which is a recommended solution for a faster use.

The soil moisture sensor can be used for schedule irrigations (i.e. determine when to water the plants); or for calculating soil water deficit to work out how much water to apply. Depending on the application, the sensor would need to be calibrated in with different procedures, but as a general guideline, we need to normalise its readings. Without this process, the raw sensor readings will be meaningless to the user and only some trends could be analysed. This section is a digest of some of these procedures, and more information is given in the notes below.

In case of irrigation scheduling, it is generally sufficient to simply match the raw readings from each sensor at both 0% (held in air) and 100% water levels (submerged in water). This is, of course, an approximation and will need some further analysis from the user to determine when to irrigate. When a more accurate measurement is required, the sensor needs to be calibrated with the actual soil where it's going to be deployed, since different types of soil will have different capacities. A valid approach is to prepare different samples of the soil with different levels of saturation, and adapt the sensor readings for it.

Image Source: Edaphic Scientific

If we are not aiming to get a full-fledged sensor reading, we will only need to measure the sensor in dry air and fully submerged in water. For that, we will use:

• A laptop with a serial interface. For instance, the Arduino IDE
• Our sensor
• A cup filled up with water and a napkin

The sensor can be calibrated using the shell interface. The process is as follows:

1. Connect your kit to a computer and open the terminal for the SCK. If you use the Arduino IDE, go to Tools > Serial Monitor and select 115200 baud at the bottom right corner
2. If you use the IDE type sensor on the top and click Send
3. Check if the output has something like Soil Moisture Raw (60 sec) after Enabled
4. If it's Enabled, dry the sensor and type in: read soil moisture raw. Repeat this command 5-10 times until you get an stable output (repeat command with arrow up)
5. Put the sensor in a cup of water (until the line). Then read the value again read soil moisture raw several times.
6. Once you have both values, type in: control moisture cal XXX YYY where XXX and YYY are the dry and wet values that you just measured
7. Check that the reading is OK by: read soil moisture percent. You should receive an answer in rh%
8. Now you should see the data online (if in network mode):

Find out more

Check the project source code files.

Three Chirp sensors were compared to the Parrot Flower Power (now discontinued). The Flower Power can measure several metrics, such as light, temperature, fertilizer and soil moisture. In this test, we compared the soil moisture readings for three Flower Parrot sensors, compared to three Chirp sensors. Both sensors show a good behaviour and the values can be correlated with good R2 scores. The approach for this low-cost sensors, in general, should be more qualitative than quantitative (analyse the trends rather than the absolute values), since their values appear to differ between sensors, even when normalised. In the particular case of the Chirp sensor, the sensor seems to be fairly normalised with simply a two calibration values (water and air) as a first approach.

Full analysis here

Find the full analysis here!

## Calibrated soil and water probesLink

Having a robust portfolio of the sensor for measuring soil and water characteristics is a need found by many farming communities, primarily when they are working on new ways of growing crops. In this direction, we include a collection of sensors that despite not being low cost or open source, they are still affordable and well documented when compared to other commercial solution. From a cost perspective, they are not aimed at being massively deployed but instead used individually in a specific site for specific needs.

The sensors selected are from Atlas Scientific, a New York-based company that converts devices that were originally designed to be used by humans into devices that are specifically designed to be used by robots. As already mentioned the sensors are not entirely open source as the other sensors documented on this section. However, they are modular and exceptionally well documented by the manufacturer. That includes documentation on how to install, calibrate and integrate them with additional existing hardware. In this direction, we developed a full library for the SCK to support the sensors via the Auxiliary sensor connector. We also developed a Python script to simplify the calibration process of the sensors. As the sensors can be configured in different ways, we do not provide a full step-by-step guide. Instead, we refer to the documentation on the project's repository.

The setup is built out of the following main components:

• Atlas Scientific Sensor Probe: The physical probe we will insert on to the soil (or water).
• Atlas Scientific EZO Circuit: The driver that will read the analog signal coming from the Sensor Probe and turn it into a meaningful numeric value by applying the different calibration operations.
• Whitebox Labs Tentacle T3: The motherboard that puts everything together and hosts up to 3 Atlas Scientific Probes. It connects to the SCK via the Aux sensor connector. This boards can be chained to support more sensors, but this is not documented at the moment.
• SEEED Grove - 4 pin Female Jumper to Grove 4 pin Conversion
• Cable needs to be used to connect the board to the SCK.

Different sensor probes can be selected for different needs. For example the setup shown above is designed for soil measurements and includes Atlas Scientific temperature, conductivity and PH probes. It also consists of a Chirp Moisture Sensor as described in the above section. As an additional example the setup in the figure below is designed for water monitoring on aquaponics systems and includes Atlas Scientific probes for PH, conductivity and dissolved oxygen.

Available metrics

A list of the sensors available is shown below:

Metric Usage Probe Driver Calibration Kit
Temperature Soil and water PT-100 + PT-1000 EZO-RTD Not required
PH Soil and water ENV-40-PH EZO-PH CHEM-PH
Specific Gravity Soil and water ENV-40-EC-K EZO-EC CHEM-EC
Electrical Conductivity Soil and water ENV-40-EC-K EZO-EC CHEM-EC
Dissolved Oxygen Water ENV-40-DO EZO-DO CHEM-DO
Oxygen Saturation Water ENV-40-DO EZO-DO CHEM-DO