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I have billions of anonymized location coordinates of people movement collected from app. I want to improve user experience by using location data.

  1. For example identify if user is at home or at office so that what they view in app changes.

  2. Where will they be tomorrow at particular hour - so that I can suggest to secure their homes from IOT device if they are out.

Regarding the first point, I tried to use the following rule: at night they are at home, and at day they are at work or school. Regarding the 2nd point, I have no idea how to proceed. Is there any way I could use AI to predict future location and home location?

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  • $\begingroup$ point 1 really doesn't need machine learning, you can just ask the user to set their home address (they probably already have that in their address book anyway). From code you can match if the current location is close to the home address. $\endgroup$ – Kokodoko Apr 1 at 12:59
  • $\begingroup$ @Kokodoko the app don't have this function. $\endgroup$ – kinkajou Apr 3 at 7:34
  • $\begingroup$ Point 1 you can still solve just by analyzing the data. You assume they are home at night and work during the day. So you can always compare their current location with those locations. $\endgroup$ – Kokodoko Apr 3 at 8:13
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Your problem is often called (in the literature) human mobility prediction. There has been some research in this area. Have a look at it on the web.

In general, you might want to use any statistical or machine learning model that uses the historical data to predict the future. For example, you could try to use an hidden Markov model (for both point 1 and 2). However, before that, you might also need to do some feature engineering, if you only have locations (and not e.g. the time of the day when those locations were recorded).

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  • $\begingroup$ I will try to find some materials. $\endgroup$ – kinkajou Apr 3 at 7:34

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