Achieving Panoramic View Coverage in Visual Mobile Crowd-Sensing Networks for Emergency Monitoring Applications

Visual Mobile Crowd-Sensing (VMCS) collects photos by leveraging camera embedded in mobile users’ phones. There are two important issues in VMCS: determining whether photos collected by mobile users meet the requirements or not and designing an appropriate mechanism to attract mobile users to provide photos that meet the requirements. In this article, we address those two issues when VMCS is applied to emergency monitoring applications. We first model an emergency scene as a disk region and define a coverage angle metric that quantifies the coverage ratio provided by each photo, then formulate a Maximize Coverage Angle with Limited Budget problem. The goal of this work is to recruit mobile users to provide panoramic view coverage for a disk while the total reward paid to participants does not exceed the budget. In our solution, we first propose a Coverage Angle Computation algorithm to calculate the coverage angle of each uploaded photo. Then two incentive mechanisms—the Guidance-based Incentive Mechanism and the Coverage Prediction Incentive Mechanism—are designed to encourage mobile users to upload photos with a coverage angle that are not provided by other mobile users. Finally, we design a mobile app called I-share in the Android system to implement the system. Meanwhile, we recruited students to install I-share and simulated the information interaction between mobile users and the server. We conducted experiments by using I-share without and with an embedded Coverage Angle Computation algorithm to validate the efficiency of the two incentive mechanisms. The experiment results demonstrate that our proposed incentive mechanisms effectively attract mobile users to provide panoramic view coverage of emergency scenes when the budget allows. Additionally, the Coverage Prediction Incentive Mechanism outperforms the Guidance-based Incentive Mechanism, offering a higher coverage ratio with lower rewards.