Trajectory Reconstruction and Mobility Pattern Analysis Based on Call Detail Record Data
Name
Annett Saarik
Abstract
Up until now, GPS data has been greatly used for collecting highly
precise locational data from moving objects including humans. In contrast, mobile phone data is becoming more and more popular in the last few years. The usage of mobile phone data, that is also known as CDR data, has many benefits over the widely used GPS. This means that the methods used for example in GPS trajectory reconstruction, need to have modifications made be compatible with CDR data.
The fact that telecommunication companies have started to cooperate more
and share the CDR data with the public is also a boost to the usage of CDR
data. The processed and analyzed CDR data can be used to get an overview of
crowd movement in different scales, for example traveling inside a city as opposed to between countries. Extracting trajectories from CDR data has numerous complications.
This is due to the fact that the data might not be continuous and
discovering of the starting point of the object in motion is complicated.
The goal of this thesis is to use CDR data in the reconstruction of trajectories
made by an anonymous user and to validate the results with GPS data generated in parallel to the CDR data. Reconstructed trajectories can be used for movement analysis and population displacement and would help city planning by optimizing the infrastructures.
Outcomes of this thesis are the reconstructed trajectories based on CDR data
and the precisions of final paths. Also, the frequency of CDR events is analyzed
in addition to distance distribution. After that the areas that the user visits most frequently are extracted, such as home and work locations.
precise locational data from moving objects including humans. In contrast, mobile phone data is becoming more and more popular in the last few years. The usage of mobile phone data, that is also known as CDR data, has many benefits over the widely used GPS. This means that the methods used for example in GPS trajectory reconstruction, need to have modifications made be compatible with CDR data.
The fact that telecommunication companies have started to cooperate more
and share the CDR data with the public is also a boost to the usage of CDR
data. The processed and analyzed CDR data can be used to get an overview of
crowd movement in different scales, for example traveling inside a city as opposed to between countries. Extracting trajectories from CDR data has numerous complications.
This is due to the fact that the data might not be continuous and
discovering of the starting point of the object in motion is complicated.
The goal of this thesis is to use CDR data in the reconstruction of trajectories
made by an anonymous user and to validate the results with GPS data generated in parallel to the CDR data. Reconstructed trajectories can be used for movement analysis and population displacement and would help city planning by optimizing the infrastructures.
Outcomes of this thesis are the reconstructed trajectories based on CDR data
and the precisions of final paths. Also, the frequency of CDR events is analyzed
in addition to distance distribution. After that the areas that the user visits most frequently are extracted, such as home and work locations.
Graduation Thesis language
English
Graduation Thesis type
Master - Computer Science
Supervisor(s)
Amnir Hadachi, PhD
Defence year
2017