One thing I wanted to try with OpenPaths data is to reconstruct the paths I have taken. I’m using the as yet unreleased iPhone app, which records a point every time there is a “significant” location change, as determined by the iOS API (this runs in the background without much battery drain — the reason we aren’t using continuous GPS is that such an app would quickly burn through it).
This image shows all of my points around the city in a given time period (without a base map, to preserve some privacy, and it’s kind of more interesting that way). The lines are determined by grouping series of points that are within 10 minutes of each other and inferring the start point.
Additionally, I estimated the maximum speed of each path by looking at the fastest few segments. By clustering the speeds, using the k-means algorithm, the paths are classified by mode of transportation. Red is car or Amtrak, purple is bike (my primary mode), and green is walking.
The arc of my frequent rides between Brooklyn and midtown are pretty clear, and in general you get a sense of the areas that I habitually cover with the different modes. Note Prospect Park at the bottom. One thing that’s a significant omission is the bulk of my subway travel — any ideas on how I could infer this would be appreciated. And I certainly walk around more than is reflected here, but the location changes aren’t big or sustained enough to register.