For an app as popular as Transit this is a purely academic exercise—25% of the most popular models is way too low to be worth building their detection around, even if they could assume that all of their customers use the most popular models (which they obviously can't).
25% of popular models doesn't mean 25% of phones currently in circulation. If the iPhone has a barometer (which it does), that's already a huge share of phones out there.
It may be too low, but I'd imagine the app could also look for other Transit users nearby and as long as one of them has the appropriate sensor, this might be sufficient. Probably still not something you want to rely on since it would be pretty annoying to have a feature not work when you're alone on a train.
> the app could also look for other Transit users nearby
That seems unlikely in an environment with no cellular / wifi signal. Theoretically possible, but expensive for battery and probably disallowed by the OS.
Does the current version of their app run on 25% of the most popular models? This update runs a classifier on your phone. I imagine that would be no less restrictive than the barometer requirement.
Most classifiers are nowhere near as heavy as the LLMs that are trending right now. The article doesn't specify, but I would be surprised if the resource requirements are especially onerous.
