Some of those optimizations become irrelevant (or downright bad) with http2. Inlining CSS ans JS is no longer best practice when you can do a server push of those and avoid sending the extra bytes once the files have been cached by the browser.
Some optimizations can backfire. Adding async to the external JS is a great tip.. unless you have dependencies between your different scripts (i.e. you need one to be loaded before the other one gets executed)
Important note: so-called "live" air quality measurements are in reality never "live" due to the nature of the measuring stations (taking measures takes time) and the way data is compiled and shared by the monitoring agencies. As a result typical delays range from 1 to 6 hours, which means you end up using "old" data or signaling a peak when in reality the pollution peak is already over.
This is solved by using models that predict air quality levels down to the hour. One option is to use https://plume.io
Fun project. Wondering how the contributors classified their training set... by watching all the videos? :)
In any case I know there aren't many good labeled datasets out there. I worked on Sightengine (API to detect nudity and moderate images or videos: https://sightengine.com )
I am David, one of Plume Labs' founders. Thank you for all your feedback!
At Plume Labs we build tools to help people fend off pollution. This starts with an urban weather report (the Plume Air Report) that tells you when pollution will be high for a few hours or more in your city, and what you can do about it – timing your run, biking, activities with children – to take back control of your environment.
The map discussed here is a near realtime visualization of air pollution levels worldwide. The colors and the Plume Index are based on WHO recommendations. (Blue corresponds to levels below the W.H.O. yearly recommendations, light blue is below the W.H.O. daily recommendations etc.) The map takes into account the main pollutants (NO2, O3, PM10, PM2.5) and is based on measurements made in 11,000 monitoring stations worldwide along with air quality models for the areas that are not covered by monitoring stations.
More details as well as pollution predictions are available on the mobile version of the Plume Air Report