Hands-On Edge Analytics with Azure IoT
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Soil moisture sensor

If you wanted to build an automated smart garden system, having a soil moisture sensor is required. The name of this sensor is pretty self-explanatory: it measures the moisture level in the soil. The following is a photograph of a soil moisture sensor:

As you can see in the photograph, the sensor is made up of two parts. The bottom piece is the part that is actually inserted into the soil. It connects to the other piece, the controller, via a wire. The four pins in the controller are as follows:

  • VCC: Used to provide power to the sensor
  • GND: For ground
  • D0: For digital output (either high or low) from the sensor
  • A0: For analog output from the sensor

The following diagram is an example of an edge analytics application using a soil moisture sensor. As you can see, one end of the moisture sensor is inserted into the soil of our plant pot. The other end of the sensor is connected to our Raspberry Pi computer. This allows our Raspberry Pi access to the soil moisture data:

Our Raspberry Pi uses this data to determine when to open the valve and add more water to our plant. Our Raspberry Pi also sends data to the cloud to which we would connect our computer or device. This data may be as simple as the soil level, or it may be modified in some way by our Raspberry Pi before it is sent to the cloud.

It is the logic programmed into our Raspberry Pi that makes our application an edge analytics one as opposed to a standard IoT application that would just send the reading.