Warning: Missing argument 4 for topImage(), called in /var/www/vhosts/policyvisuals.eu/httpdocs/wp-content/themes/knowhow-childtheme/single-post-dataset-type.php on line 23 and defined in /var/www/vhosts/policyvisuals.eu/httpdocs/wp-content/themes/knowhow-childtheme/helpers.php on line 2
Dataset Types

Mobile phone data

Description

Mobile Phone Data is data that is passively inferred from phone activities on mobile devices. Mobile devices are often related to human users but the data might also originate from machine to machine (M2M) interactions (for example from IOT devices). Mobile Phone Data can be collected by telecom operators from devices using their GSM, 3G, 4G or 5G network.

Raw Mobile Phone Data contains records for every time a device connects to the network. This might be a periodic update connection to the mobile network or it might concern interaction with another device. Using the geographic location, the range and the orientation of antenna stations a captured signal can be geolocated in a cellular network.

Processing and analyzing Mobile Phone Data must be executed with respect for privacy and data protection regulations.

The geographic precision of Mobile Phone Data is depending on the density of the network antenna stations. Regions with dense population or more human activity often have a denser coverage of network antennas (for example cities and highway trajectories on a macro level, commercial streets, parking garages or shopping malls on a micro and pico level). Signal reflection or interference, weather conditions and height of the device can influence the signal capture. The cellular network used to geolocate a device must, therefore, be consiTdered an approximation, this is especially the case for devices located on the cell edges (in the overlapping range of multiple antennas).

When best to use

Processed and analyzed Mobile Phone Data can provide information on spatio-temporal behavior and interaction patterns of the mobile devices. Devices that are used by humans (mainly smartphones) can provide information on human activities such as most likely lodging places, mobility patterns and even social interactions.

Main data elements:

The datasets contain the following elements

  • Timestamp
  • ID
  • Location (within a cell)

This information can be aggregated to identify the number of, e.g., students in a certain area at a certain point in time.


Leave a Review.

You must be logged in to post a comment.