Estudo em larga escala da dinâmica de cidades e do comportamento social urbano usando redes de sensores participativos

Abstract

The ubiquitous availability of computing technology such as smartphones, and the worldwide adoption of social networking sites make it increasingly possible for one to be connected and continuously contribute to this massively distributed information publishing process called participatory sensor network (PSN). In this scenario, people act as social sensors, voluntarily providing data that capture their daily life experiences, and offering diverse observations on both the physical world and the online world. In this thesis, we argue that PSNs can act as valuable sources of large scale sensing, providing access to important characteristics of urban social behavior. We study properties of PSNs derived from different systems, and show how to model and extract knowledge from them, individually and concurrently. Our results show that PSNs have the potential to become fundamental tools to support the better understanding of city dynamics and urban social behavior.