Recently, the massive prevalence of mobile devices has led to the development of mobile social sensing systems where humans are enlisted to act as social sensors to perform geo-located tasks that require human intelligence or intervention. Social sensing from ubiquitous users can provide significant benefits particularly during crisis management and emergency scenarios. However, an important problem during such emergencies is how to exploit social sensors to accurately determine the location, extent and severity of the event. In this paper we develop a social sensing system that uses humans as social sensors where we apply particle filtering to iteratively determine the spatial areas to be investigated to accurately detect the location and state of the target event. Our experiments illustrate that our approach can accurately identify critical real-world events using feedback from the social sensors.
['Ioannis Boutsis', 'Vana Kalogeraki']
Using Human Social Sensors for Robust Event Location Detection