The purpose of this study is to determine the characteristics of individual human mobility based on daily mobility
patterns that are formed. The data used in this study is GPS data from one of the telecommunications service operators in
Indonesia. This data has a large size but not all of it can represent daily mobility as a whole. DBSCAN is used to group
location coordinates and label them in integer form. The combination of identical location and time will form a mobility
pattern in the mobility diary. Position slot represents the presence of an individual at a certain location and time which is
used to identify their mobility patterns. Meanwhile, to measure the similarity between the curves formed in the mobility
pattern, Frechet Distance is used. Position slots are effectively used to overcome data incompleteness and obtain complete
daily mobility patterns of an individual in a data set. The locations frequently visited by an individual and their frequency
in position slots can be known via a heatmap. Based on the similarity measure, we get varying values between two mobility
patterns at different dates. Analysis of individual mobility characteristics is carried out by observing the pattern, location
and frequency of visits to position and the similarity measure value. The results of the analysis show that there are
individuals with mobility patterns who are in certain position slots over a period of one week, even though they are in
different location clusters but in certain adjacent areas. This mobility pattern is one of the characteristics of individual
mobility.
Level
Internasional
Status
Dokumen Karya
No
Judul
Tipe Dokumen
Aksi
1
Characteristics of Individual Human Mobility Using.pdf
