How does Apple car crash detection work? — AI modeling analysis
Apple announced the Apple watch series 8 and iPhone 14 that has the capability to detect car crash and automatically connect emergency services, pass location details, and inform emergency contacts.
Apple said that they hope that we users do not need to use the feature but it will give a safety assurance while seating in a car that Apple crash detection will help in those scenarios. The company said it spent years studying vehicle impacts at crash test labs and focused on four main types of crashes: front, side, rear-end, and rollover crashes. This article covers how Apple may have applied machine learning modeling for car crash detection.
Task objective
We can articulate a problem as follows:
The machine learning model will make use of features such as accelerometer, gyroscope, and position data. Following that, it should run a binary classification algorithm to determine whether or not there was a car crash. It should be constantly monitored when driving a car.
Brainstorming framework structure
I have some thoughts on what Apple may have done to make the prediction model:
- Event trigger:
- It is critical to determine when iPhone should begin looking for…
