Incentive and Quality Aware Participatory Sensing System

Participatory Sensing system (PSS) is being thought of as an alternative model in the pervasive computing environment, to collect effective data from mobile human agents, where deployment of sensor agents to collect data will be costly. One of the main difficulties in collecting data from the human agents is that, they are not willing to participate in this data collecting process. Several incentive schemes, based on the framework of auction theory, are proposed to motivate the users to participate in this interesting data collection model. However none of the incentive schemes used to judge the quality of the users along with their bid prices to select the human agents. If the quality of the agents is used, the data collection model may attract the bidders with slightly higher valuation but providing a good quality data. This scheme will make the PSS more realistic. In this paper, an efficient scheme is proposed not only to motivate users but also to restrict manipulation in the bidding substantially. The simulation study shows that the proposed economic model can maintain better participation of the agents compared to the existing schemes and also it will perform better when the agents are rational.