I have a dataset consisting of location (latitude and longitude) and timestamp.

The amount of data is relatively massive, and what I need to do is a type of clustering of the regions where the most time has been spent. There may be more than one region, and the result might be a circle.

I thought about dividing the data into quadrants because the idea is to have this processed in BigQuery and calculated once a day, so quadrants could help, maybe…

What algorithms could I use for this?

If you use an iPhone, it has something similar—after spending a certain amount of time in a location, it loosens the security and allows you to use the PIN code if Face ID fails.