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.