Abstract:
Mobile phones are increasingly equipped with sensors, such as accelerometers, GPS receivers, proximity sensors and cameras, which 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 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 the scenarios that are opened by the emergence of this new paradigm of mobile anticipatory computing and I will present our ongoing work in this area.
Bio:
Mirco Musolesi is a Readerin Networked Systems and Data Science at the School of Computer Science at the University of Birmingham. He received a PhD in Computer Science from University College London in 2007. Before joining Birmingham, he held research positions at Dartmouth College and Cambridge and a Lectureship at the University of St Andrews. His research interests lie at the interface of different areas, namely ubiquitous computing, large-scale data mining, and network science. More information about his research profile can be found at the following URL: http://www.cs.bham.ac.uk/~musolesm