We spent about 90% of our lives in doors, yet there is barely any data about the air quality in enclosed areas. CO2 is in most locations a very good proxy for the amount of exhaled air in a room which correlates with infection risks. High CO2 levels also can increase the aerostability of viruses so high levels are there is also a direct effect of CO2 as well. Aside from infection risks, high CO2 levels also can decrease cognitive abilities (during exposure, not permanently) and cause dizziness and headaches etc.
Most existing studies are small size and focus on homes, hospitals or schools. During the beta test the community already took more than 10000 measurements (each between 5 and 120 minutes long), which to my knowledge already makes it the largest dataset of its kind. Currently most users are from german speaking regions which is a result of me being german and my social graph being mostly german.
The App does not require any user registration and works with most of the common portable CO2-Monitors (Aranet4, Airvalent, Inkbird-IAM-T1, Airspot Health). For some of them I had to reverse engineer the Bluetooth messages and to make things worse the Airvalent’s data isn’t byte aligned.
The App is built using C# MAUI and cross-compiles to both android and Apple. I use it because C# is the Language I am most comfortable in but also because it can be deployed to local iPhones without having to own a Mac. The Backend is using a queue server, serverless functions (also C#) and a postgresql Database, all hosted on AWS. The website is using maplibre, deck.gl and chart.js - I have no clue about websites so just tried to keep things simple. Expanding to other Indoor Air Quality indicators like PM2.5 would be trivial but currently the amount of people having mobile sensors is too small to be worth the effort.