Mobile phones are increasingly equipped with sensors, such as accelerometers, GPS receivers, proximity sensors and cameras, which, together with social media infromation can be used to sense and interpret people behaviour in real-time. Novel user-centered sensing applications can be built by exploiting the availability of these technologies. Moreover, data extracted from the sensors can also be used to model and predict people behaviour and movement patterns, providing a very rich set of multi-dimensional and linked data, which can be extremely useful, for instance, for marketing applications, real-time support for policy-makers and health interventions.

In this talk I will discuss some recent projects in the area of large-scale scale data mining and modelling of mobile data, with a focus on human mobility prediction and epidemic spreading containment. I will also overview other possible practical applications of this work, in particular with respect to the emerging area of anticipatory computing and the challenges ahead for the research community.

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