PhD in Computer Science

Analysis of mobility data to study and optimise public transports

Analysis of mobility data to study and optimise public transports

Academic year 2013/2014

Sommario del corso

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Program

As the world becomes more urbanized, cities have evolved into one of our
most consummate and complex artifacts. As a result, urban transportation is
facing a grand challenge that is often called sustainable mobility: 
devising more efficient and adaptive urban transportation systems necessary
to accommodate urban dynamics while preserving and restoring the
environment. The general consensus is that congestion reduction is instead
better addressed through Intelligent Transportation Systems (ITS) that
leverage sensor networks, communications and computing technologies to
manage existing infrastructure and transportation systems more efficiently.
More recently, our growing reliance on smartphones and other pervasive
technologies is producing a wealth of digital information extremely valuable
to ITS systems because of its unprecedented level of spatio-temporal details
about many aspects of our daily lives and in particular our travelling
patterns. It also provides a medium through which it is possible to
reach-out to the travellers and engage them in adopting the most efficient
means of transport. In particular, in this seminar we present the analysis
of mobile phone traces to optimise the public transports in developing
countries.

Class schedule

Note

The seminar will be held by 

Dr. Fabio Pinelli, IBM Researcher - Ireland

SHORT BIO:
Fabio Pinelli is currently a research scientist at Smarter City Technology
Center at IBM research -- Ireland where he investigates new methods to
extract useful knowledge from urban related data with special focus on
Intelligent Transportation systems.
He earned his PhD in Information Engineering from the University of Pisa
where he studied new approaches for the analysis of trajectories of moving
objects. During this period, he was also visiting student at Senseable City
Lab -- M.I.T.
His main research interests include spatio-temporal data mining, pervasive
computing, intelligent transportation systems and urban dynamics.

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