Recent studies suggest that, contrary to what we used to believe, the urban population worldwide is over 80%, reaching up to 90% in developing countries. This leads to a large variety of urban configurations, generating a wide range of social, mobility, health, education, and infrastructure problems and challenges. Recent Advances in IoT-related technologies, as well as Big Data, Machine Learning, and Visualization give computer scientists the opportunity to apply their knowledge to improve the life of citizens in small towns, cities, and big metropolises. This can be achieved with the development of innovative systems that can collect vast amounts of data from city sensors and mobile devices, analyze these data, generate models, and provide information about what’s happening as well as make predictions for the future. These systems can help citizens, companies, NGOs, city governments, and urban planners to better understand and manage their cities. In this talk, we will present some of the ongoing projects in this area carried out at the University of São Paulo and the MIT Senseable City Lab in collaboration with city governments.


Fabio Kon is a Full Professor of Computer Science at the University of São Paulo and a Fulbright Visiting Professor at the MIT Senseable City Lab. His research interests include Smart Cities, Big Data Processing, Middleware, Computer Music, and Startup Ecosystems. Fabio is an ACM Distinguished Scientist, the Editor-in-Chief of the SpringerOpen Journal of Internet Services and Applications, and he leads InterSCity, a national research project on Smart Cities in Brazil (http://interscity.org).

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