A Context-Aware Incentive Mechanism for Mobile Crowd Sensing to Increase Participation of Users

Mobile crowd sensing is a new paradigm that uses the data sensed by mobile users to extract population data and then provides people-centered services. However, most users do not tend to participate voluntarily in this process. Therefore, availability of incentive mechanisms is mandatory to encourage users’ participation. In this paper, based on users-submitted data, a score-based incentive mechanism is proposed. This mechanism measures data quality via obtained contextual information from user data, and accordingly, gives score to the user. The fuzzy inference system is used in the center of the incentive mechanism to calculate the score. The proposed mechanism is evaluated via simulation and the effect of each parameter on the score acquired by user is shown. Simulation results show that this mechanism could be helpful in solving the problem of price imbalance in different areas of measurement and also is able to collect high-quality data at each measurement point with few number of participants.