Reliable crowdsourced event detection in smartcities

In recent years crowdsourcing systems have shown to provide important benefits to Smartcities, where ubiquitous citizens, acting as mobile human sensors, assist in responding to signals and providing real-time information about city events, to improve the quality of life for businesses and citizens. In this paper we present REquEST, our approach to selecting a small subset of human sensors to perform tasks that involve ratings, which will allow us to reliably identify crowdsourced events. One important challenge we address is how to achieve reliable event detection, as the information collected from the human crowd is typically noisy and users may have biases in the answers they provide. Our experimental evaluation illustrates that our approach works effectively by taking into consideration the bias of individual users, approximates well the output result, and has minimal error.