Mobility Profiling
| Title | Mobility Profiling |
| Publication Type | Book Chapter |
| Year of Publication | 2014 |
| Authors | Nanni, M, Trasarti, R, Cintia, P, Furletti, B, Renso, C, Gabrielli, L, Rinzivillo, S, Giannotti, F |
| Book Title | Data Science and Simulation in Transportation Research |
| Chapter | 1 |
| Pagination | 1-29 |
| Publisher | IGI Global |
| Abstract | The ability to understand the dynamics of human mobility is crucial for tasks like urban planning and transportation management. The recent rapidly growing availability of large spatio-temporal datasets gives us the possibility to develop sophisticated and accurate analysis methods and algorithms that can enable us to explore several relevant mobility phenomena: the distinct access paths to a territory, the groups of persons that move together in space and time, the regions of a territory that contains a high density of traffic demand, etc. All these paradigmatic perspectives focus on a collective view of the mobility where the interesting phenomenon is the result of the contribution of several moving objects. In this chapter, the authors explore a different approach to the topic and focus on the analysis and understanding of relevant individual mobility habits in order to assign a profile to an individual on the basis of his/her mobility. This process adds a semantic level to the raw mobility data, enabling further analyses that require a deeper understanding of the data itself. The studies described in this chapter are based on two large datasets of spatio-temporal data, originated, respectively, from GPS-equipped devices and from a mobile phone network. |
| DOI | 10.4018/978-1-4666-4920-0.ch001 |
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