This post is just an introduction to a series of publications about a custom indoor air quality device connected to IoT back-end.
(I hope, I'll be able to manage my laziness and procrastination)
The publications will describe a whole ecosystem which includes a sensing device, IoT cloud service, back-end and Telegram bot to get aware about your indoor air quality. Also maybe I'll ad something about the analysis of data.
Look at the picture below, this is a better explanation of the ecosystem than description by words.
In the next posts I'll explain how to build your own sensing device to measure the quality of indoor air, what are the most relevant air quality parameters compared to well-known outdoor air quality, which sensors available on mass market are most suitable to measure those parameters. There are many tricky questions here. How the optical particulate sensors measure the weight of particles? Why it seems to make not that much sense to measure nitrogen and sulphur oxides which are taken into account for outdoor air quality? How reliable the carbon dioxide measuements provided by famous "CO2-equivalent" metal-oxide sensors? And many others.
I'm gonna discuss what platform I selected to host the sensors (Arduino board with two MCUs) and what cloud Interner of Things service is suitable for private use. Currently this project is running on MS Azure IoT. Also I'll share an option how to receive information from the air quality device to a smarthone through deploying a bot in Telegram.
Finally, having air quality data collected for some period it's possible to think about a machine learning models that can classify typical events a home, predict air quality, advise how make the air more healthy and so on.
I hope this series will be usefull for those who are interested in the quality of air we breathe, in DIY activities with sensors, communication protocols and hardware platforms, in software development and air quality data analysis. Stay tuned!
I'm gonna discuss what platform I selected to host the sensors (Arduino board with two MCUs) and what cloud Interner of Things service is suitable for private use. Currently this project is running on MS Azure IoT. Also I'll share an option how to receive information from the air quality device to a smarthone through deploying a bot in Telegram.
Finally, having air quality data collected for some period it's possible to think about a machine learning models that can classify typical events a home, predict air quality, advise how make the air more healthy and so on.
I hope this series will be usefull for those who are interested in the quality of air we breathe, in DIY activities with sensors, communication protocols and hardware platforms, in software development and air quality data analysis. Stay tuned!
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