I develop a self-hosted service designed to do exactly this! It’s not quite finished yet, but it’s at the point where enough functionality works that it can be used for testing.
https://github.com/connervieira/HealthBox
The docs/USAGE.md file gives an overview of how HealthBox works. Feel free to poke around in the other docs/ files as well.
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Understanding of the “normalcy bias” changed the way I think a lot. The general idea is that you’ll tend to explain away and dismiss unusual things you see. In other words, people are hesistant to acknowledge when something isn’t normal.
When you see something that strikes you as odd, I think it’s good to understand that this bias exists. Avoid saying “oh, it’s probably just XYZ”, and actually try to work out an explanation. You may end up solving a situation you otherwise wouldn’t have even realized was about to be a problem.
In the worst case, you’ll just realize your initial instinct was right, and move on. In the best case, you’ll be able to help with a situation that otherwise would have been neglected, and been allowed to become a serious problem.
I’ve had good luck with FitoTrack in F-droid. I was looking for a drop in replacement for the workout app on Apple Watch, and that seems to do well.
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I maintain a program called Assassin that has an ALPR camera database as a headlining feature. You install it on a low-power SBC (like a Raspberry Pi) in your car, and it notifies you before passing ALPR cameras (among other threats). I only personally maintain the database in my states, but I like to think it’s fairly comprehensive.
With some technical experience, you can create a pretty elegant system with concealed status LEDs, configurable audio alerts, and more.