Distinguishing between motorized and non-motorized
transportation mode is not a difficult problem. However, with
multiple motorized transportation modes, the problem becomes
more difficult since buses, cars and trains may have similar GPS or
accelerometer readings. We show that using a transportation
network with real time and static spatial data, we can obtain high
detection accuracy for various motorized and non-motorized
transportation modes.