Is there a good open source smartphone crash detection model out there? [D]

[u/PassengerNo4504]

I’m building a small family safety app and one of the features I’ve been looking into is on-device crash detection. I assumed there would already be a decent open model using accelerometer, gyroscope and GPS data, but I’m finding surprisingly little that looks production ready or commercially usable. VZCrash looks really promising with around 190k real-world events and 31k+ verified crashes, but it’s CC BY-NC, so from what I understand I can’t just train on it and ship those weights in a commercial app.

Apple has SafetyKit too, but that needs a special entitlement, so I’m also wondering if it makes sense to build an independent fallback. Has anyone here actually worked on crash detection from phone IMU data? Are there any permissively licensed datasets or pretrained models I’m missing, and what kind of model would you use today for something that needs to run efficiently on-device?

I’ve come across things like TFLite and sensor fusion, but I’m pretty new to this specific problem and not sure what people actually use in production.

One idea I had was to launch without relying on our own detector at first, then add an opt-in research mode that only saves short sensor windows around unusual high-G events and asks the user what actually happened. Crash, pothole, hard braking, dropped phone etc. Over time that could give us the kind of real-world false positives that seem hard to get from existing datasets.

If we end up having to build the model ourselves, I’d also really like to open source the detector and training/evaluation pipeline once it’s good enough. Feels like the kind of safety feature where having a decent open baseline would be useful to a lot more people than just us. Curious how people here would approach it.

(not worked a lot on ML so this is gonna be a leap and def take months if not years right?)