Big Data Solutions: Models and Algorithms in Smart City Domains

The connection, integration and analysis of the information produced by the various forms of data from smart cities, provides a more cohesive and smart understanding of the city that enhances efficiency and sustainability. This rich interconnection of data can be used to better depict, model and predict urban processes and simulate the likely outcomes of future urban development. All these needs express the creation of solutions capable of analyzing heterogeneous kinds of data, providing a multitude of nal applications based on the kind of users who requires a certain service, in particular through the use of real-time analytics to manage aspects of how a city functions is regulated. This thesis's purpose is to study and develop algorithms to improve services to citizens, making the city more knowable and controllable in new, dynamic and interconnected ways. To this aim, Smart City solutions related to urban mobility and environmental monitoring have been studied to improve the quality of citizens' lifestyle, Social Media data have been analyzed to understand the tendency of an information on Twitter to be widespread and to predict the audience of scheduled television programmes.