Intention is the main method of crowdsourcing service in Crowd Sensing (CS), in view of the existing methods in the process of service without fully considering the effects on CS which are from the number of participants and malicious competition, a kind of Incentive Mechanism based on Reverse Vickrey Auction model (RVA-IM) method was proposed. Firstly, incentive mechanisms of crowdsourcing were studied in this paper, in combination with reverse auction and Vickrey auction, a reverse auction model oriented to task covering was built. Secondly, the in-depth analysis and research on the key technical problems involved in the model were conducted, such as task covering, reverse auction selection and reward implementation. Finally, the effectiveness of RVA-IM method was analyzed in five ways:computational efficiency, individual rationality, budget-balance, truthfulness and honesty. The simulation results show that, compared with IMC-SS (Incentive Mechanism for Crowdsourcing in the Single-requester Single-bid (SS)-model) and MSensing (Myerson Sensing) method, RVA-IM method is more effective and feasible. It can solve the problem of malicious competition in the existing methods, and improves the average rate of service completion by 21%.