Social urban sensing is a new paradigm which exploits humancarried or vehicle-mounted sensors to ubiquitously collect data for large-scale urban sensing. A challenge of such scenario is how to transmit sensed data in situations where the networking infrastructure is intermittent or unavailable. In this context, this paper outlines our researches on an engine that uses Opportunistic Networks paradigm to underlie the data transmission of social urban sensing applications. It also applies Situation awareness, Fuzzy Logic and Neural Networks to perform routing, adaptation and decision-making process. We carried out simulations using a simulator environment, achieving positive results. As we know, this is the first paper to use such approaches in Smart Cities area with focus on social sensing application.