Privacy and incentive mechanisms in people-centric sensing networks

Leveraging on the ubiquity and increasing number of smartphone users, people-centric sensing is a new computing paradigm that enables distributed data collection by voluntary participants, using the rich sensing capabilities of smartphones. In this article we identify the challenges on two important issues for a successful people-centric sensing system, i.e., privacy and incentives, because if either there is no incentive to participate or participants' privacy is invaded, smartphone owners will be reluctant to participate. Then we review some recent works that address these two issues. Finally, we suggest directions for future work on people-centric sensing by describing several open issues.