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          Mobile phone air quality monitor (AqiSDS011)


          Probably the cheapest and most resource-aware approach to measure air quality is to combine your mobile phone with an affordable air quality sensor.

          To make that possible I created an open-source mobile application for that purpose and here is a short story about its development.

          Forget the story, how can I use this?

          The optional step would be to create a proper home for your new sensor, here is one idea using the simple although a bit oversized solution. A 3D printer could create a more streamlined solution.

          SDS011 AQI sensor in a wooden box

          Looks interesting, tell me more about it

          A few years ago I started to notice that the air we breathe is not everywhere the same and that it is not even each day the same. My wife was more aware of this fact and even find out quite a few places where she can compare our subjective experience with the scientific measurements.

          Every now and then we checked the publicly available data, mostly using the IQAir AirVisual application.

          However, we were not able to find out the air quality for micro-locations we were interested in.

          At the beginning of the 2021st, we decided to buy our own measuring device that could help us to investigate this a bit more. We ordered the handheld measuring device from the Amazon but our order was slowed down because of “Brexit issues”:

          Hello, Due to the problems with Brexit, the UK and EU governments have not agreed on tariffs and our large consignment of parcels are being held up at customs unable to enter the EU or be returned to the sender. We are anxious every day and hope that we can resolve the problem with this shipment of parcels quickly.

          After receiving this message, I did some research and realized that I could buy an air quality sensor SDS011 from a local electronic components store. There is an open source Python application that can measure AQI based on PM2.5 or PM10 with a Raspberry Pi and an SDS011 particle sensor. Well, I thought a bit about that and decided that if a tiny Linux machine can do it, my laptop should be able to use that sensor too 🤞

          It did work but was a bit “impractical” to use but I realized that I carry a much smaller computer in my pocket wherever I go (my smartphone, of course). There were some out-of-the-box solutions that were not easy to install nor easy to use so I decided that after 20 years of writing all kinds of applications, there is one more application to write 💡

          The the result of this effort is an open source application available on the GitHub and installable from the Google Play.

          The app with sensor is quite straightforward to use:

          • connect the SDS011 sensor to your phone using the OTG cable
          • confirm on your phone to open the AqiSDD011 app for USB device
          • (optional)change the app default settings
          • press the START ▶ button to start measuring the air quality

          For longer measuring periods it is better to use the PERIODIC mode of measuring and for quick measurements it is best to use CONTINUOUS measurements. The measuring period for periodic measurements can be configured as the number of continuous measurements (to average into a single history entry).

          You can easily check the history of your measurements and from there you can even check the location for each measurement or export all history data to a location on your phone or your Google Drive.

          For more details, you can check the old blog about AqiSDS011.

          Cover image by Reimund Bertrams from Pixabay

          Vedran Vidović is a proactive and experienced software developer. Since 2001, he works in IT industry, and has gained extensive experience in development, analysis, design, and architecture, applying different technologies on many projects from various business domains. He has broad experience in J2EE technologies on projects of various complexity. Since 2009, he gathered extensive experience in the enterprise integration projects, using mostly IBM DataPower Gateway and IBM API Connect.


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