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Methods of analysis of episodic movement data

Abstract
 
: Liebig, Thomas; Andrienko, Gennady; Andrienko, Natalia

University of Tartu:
Mobile Tartu 2012. Mobile Phones, Geography, LBS : 22-25 August 2012 in Tartu, Estonia
Tartu, 2012
S.24-25
Conference "Mobile Tartu" <2012, Tartu>
Englisch
Abstract
Fraunhofer IAIS ()
spatiatemporal data; Global Positioning System (GPS); cell based tracking

Abstract
Our approach is analysis of episodic movement data. This data contains some uncertainties among time (continuity), space (accuracy) and number of recorded objects (coverage). Prominent examples of episodic movement data are spatiotemporal activity logs, cell based tracking data and billing records. To give one detailed example, Bluetooth tracking monitors presence of mobile phones and intercoms within the sensors footprints. Usage of multiple sensors provides flows among the sensors. Most existing data mining algorithms use interpolation and therefore are infeasible for this kind of data. For example, speed and movement direction cannot be derived from episodic data; trajectories may not be depicted as a continuous line; and densities cannot be computed. Though this data is infeasible fo r individual movement or path analysis, it bares lots of information on group movement. Our approach is to aggregate movement in order to overcome the uncertainties. Deriving number of objects for spatio-temporal compartments and transitions among them gives interesting insights on spatio-temporal behavior of moving objects. As a next step to support analysts, we propose clustering of the spatio-temporal presence (Figure 2) and flow situations. This work focuses as well on creation of a descriptive probability model for the movement based on Spatial Bayesian Networks. We present our methods on a real world data set (see Figure 1) collected during a football game in Nîmes, France in June 2011. Episodic movement data are quite frequent and more methods for its analysis are needed. To facili tate method development and exchange of ideas, we are willing to share the collected data and our findings.

: http://publica.fraunhofer.de/dokumente/N-221233.html