Wireless Network Data Sources: Tracking and Synthesizing Trajectories
Mobility, Data Mining and Privacy, 2008
Due to inexpensive modern sensing technologies and extensive use of wireless communication, locat... more Due to inexpensive modern sensing technologies and extensive use of wireless communication, location information about moving objects is increasing rapidly. Some positioning technologies are based on GPS-equipped devices, while others utilize the infrastructure of the underlying communication network. This opens new opportunities for offering, monitoring, and decision-making novel applications in a variety of fields. To name a few, we have location-based services (LBS), fleet management and traffic control applications, emergency, navigation, and geocoding services. These compose a subset of existing applications where such kind of data comprise the core of the underlying business. Nevertheless, a new class of applications will take advantage from GeoPKDD approach, where the core information is the movement of people, i.e., sequences of positions of users over time. Therefore, starting from the analysis of people’s movements, a novel class of services, denoted movement-based services (MBS), can be enabled. LBS can be rephrased as Give me some service depending on where I am now, whereas MBS can be rephrased as Give me some service depending on where I and other people have been in the past. Movement data to be analyzed can be real or synthetic. Indeed, real movements come from collecting trajectories of people; these can be represented as synthetic trajectories that simulate specific kinds of movements. Having synthetic data sets is extremely useful for correct development, verification, and testing of data analysis algorithms such as data mining [10]. Indeed, having a predictable data set allows developers to test algorithms on extreme situations and to verify the correctness of results.
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Papers by Fabrizio Pini