Mobility Data

Published: 10 March 2021| Version 1 | DOI: 10.17632/ft37z7d5cp.1
Rigzin Angmo,


This Spatio-temporal dataset is collected from 24 users over 9 months (dating 12 September 2018 to 23 May 2019). A GPS trajectory of this dataset is represented by sequential time-stamped points, each comprising of latitude, longitude, timestamps, and 33 other different sensor attributes. This dataset contains 41,51,237 trajectories with a total distance of about 3124.66 kilometres and a total duration of 389+ hours. These trajectories are recorded using AndroSensor App which is an absolute all-in-one diagnostic tool that lets user know virtually everything about their device status and allows them to record everything from their sensors into a CSV file according to their preferences. So, we let volunteers choose what attribute of themselves they want to record and share with us. This dataset recorded a broad range of users’ outdoor movements, including not only life routines like go home and go to work but also some entertainments and sports activities, such as shopping, sightseeing, dining, hiking, and cycling and also includes some fieldwork movements. This trajectory dataset can be used in many research fields, such as mobility pattern mining, user activity recognition, location-based social networks, location privacy, and location recommendation.


Steps to reproduce

Step 1. Install the AndroSensor app to the android based smartphone device. Step 2. Open the AndroSensor app, click the record button (red dot) in the left panel of the opened app. Step 3. Go to the file manager, under this you can find the AndroSensor file, open it and select the files that you want to send or share either through email or any other electronic means.


Panjab University


Computer Science, Global Positioning Systems, Spatiotemporal Database, Information Privacy, Spatio-Temporal Computation, Spatio-Temporal Statistics, Trajectory Planning