Air Quality sensors: first steps to set them up

A previous post announced the arrival of our first two #airquality sensors. These two sensors measure particulate matter (PM); we are still waiting on delivery of two more sensors, which will measure nitrogen dioxide.

Now we’ve got these sensors, the first steps in our project plan are about setting them up before they are ready for use by volunteer participants. We also need to do some proper testing, but more on that in another post.

Below is a picture of our two AirBeams to measure PM:

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For the technically-minded the AirBeam is based upon the Arduino Leonardo. In addition to the particulate matter sensor inside the case, there is also a sensor to measure temperature and relative humidity. The AirBeams are battery powered and charged using a USB cable. These AirBeam needs to be used with an Android smartphone and a specific “app” has been developed for their use – the “aircasting” app is found here.

The AirBeam connects to the Android smartphone using bluetooth technology. The Android smartphone is primarily needed to provide a GPS location for the data that is recorded by the sensors. Additionally the microphone of the phone can be used to record local noise levels – potentially providing some insights into local noise pollution levels, although this is not the immediate focus of our project.

The screenshot below shows the aircasting app and the readings from the sensor. So, at this point in time (readings are taken every few seconds) PM was 6 micrograms (one millionth of a gram) per cubic meter. At the same time, relative humidity was 51%, temperature 60F and the sound level was 81dB. The colour coding can be configured and is designed to give a quick idea about current levels.

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These readings update continuously and can be recorded on the smartphone for mapping or analysis. More on this in a later post.

Michael has been using this AirBeam for the last year or two and so is very familiar with its use. They are great devices, but of course have their limitations. One limitation is the need for an Android smartphone and so volunteers will need to have an appropriate phone for the sensor to work. This is a constraint, but we feel we can still learn a lot during the project.

More information to follow on the progress of our tests with these sensors and how the data can be used.

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