A novel engine to underlie the data transmission of social urban sensing applications

Social urban sensing is a new paradigm which exploits human-carried 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 of a novel engine that uses Opportunistic Networks paradigm to underlie the data transmission of social urban sensing applications. It applies Situation awareness, Fuzzy logic and Machine Learning approaches to perform routing and decision-making process. As we know, this is the first paper to use such approaches in Smart Cities area with focus on social sensing application. As well as being original, the results from our simulations signals the way that further research can be carried out in this area.