EFusion: correcting unreliable labels with expert knowledge for mobile crowdsensing

With technological advances in mobile devices, mobile crowdsensing (MCS), a special crowd sourcing paradigm, has attracted unprecedented interest. Traditionally, MCS recruits a crowd of mobile users to capture data of interest and input their own judgment (i.e., intelligence) to facilitate the processing of big data. Recently, there is a surge of interest in another form of MCS where the sensing crowd consists of “smart” devices/programs that possess machine intelligence. One example is the smart cameras that recognize human faces or detect urgent events such as a car collision.