In this paper we analyze few GPS-based traces to infer human mobility patterns. We propose a clustering method to extract the main points of interest, called geo-locations, from GPS data. Starting from geo-locations we propose a definition of community, the geo-community, which captures the relation between a spatial description of human movements and the social context where users live. A statistical analysis of the principal characteristics of human walks provide the fitting distributions of distances covered by people inside a geo-location and among geo-locations and pause time. Finally we analyze factors influencing people when choosing successive location in their movement.
Extracting human mobility patterns from GPS-based traces / M. Zignani, S. Gaito - In: 2010 IFIP wireless days : Venice (Italy), october 20-22, 2010Piscataway : IEEE, 2010 Dec 03. - ISBN 9781424492305. (( convegno IFIP wireless days tenutosi a Venice, Italy nel 2010 [10.1109/WD.2010.5657695].
Extracting human mobility patterns from GPS-based traces
M. ZignaniPrimo
;S. GaitoUltimo
2010
Abstract
In this paper we analyze few GPS-based traces to infer human mobility patterns. We propose a clustering method to extract the main points of interest, called geo-locations, from GPS data. Starting from geo-locations we propose a definition of community, the geo-community, which captures the relation between a spatial description of human movements and the social context where users live. A statistical analysis of the principal characteristics of human walks provide the fitting distributions of distances covered by people inside a geo-location and among geo-locations and pause time. Finally we analyze factors influencing people when choosing successive location in their movement.Pubblicazioni consigliate
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