README.md

transportation_mode_learning_framework

Nomenclature

	explanation
transportation modes	car, walk, cycle, underground, train, bus, etc.
GPS point	(longitude ,latitude, altitude, timestamp)
GPS data/sequence/trajectory/track	a sequence of GPS points
segment	the route between any two consecutive GPS points
stage	group of segments, each new stage defined when there is a change from one mode of transport to another, or where there is a change in vehicle of the same mode
trip	sequence of stages

Debugging of predicted mode based on accelerometer data

main class: eu.qrowd_project.wp6.transportation_mode_learning.Predict

prerequisites: the R project for the ML part, i.e.

git clone git@github.com:QROWD/TR.git

usage: eu.qrowd_project.wp6.transportation_mode_learning.Predict <$PATH_TO_R_PROJECT> <$PATH_TO_GPS_CSV> <$PATH_TO_ACCELEROMETER_CSV>

output: GeoJson lines and GPS points located at /tmp/trip{$id}_lines_with_points.json, e.g.

{
      "type": "Feature",
      "geometry": {
        "type": "LineString",
        "coordinates": [
          [
            11.10949,
            46.08808
          ],
          [
            11.10988246565158,
            46.088481810324325
          ]
        ]
      },
      "properties": {
        "timestamp-start": "2018-04-09 13:38:32.0",
        "timestamp-end": "2018-04-09 13:39:30.0",
        "stroke": "red",
        "mode": "\"bike\""
      }
    },

The properties include the mode of transportation as string value.

Color Mapping:

mode	color
bike	red
bus	green
car	blue
still	yellow
train	olive
walk	purple