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

Abstract

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 paper, 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, and then formulate Maximize Coverage Angle under a Limited Budget(MCALB) problem. The goal of this paper 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 (CAC) algorithm to calculate the coverage angle of each uploaded photo. Then two incentive mechanisms: Guidance based Incentive Mechanism (GIM) and Coverage Prediction Incentive Mechanism (CPIM) are designed to encourage mobile users to upload photos with coverage angle that are not provided by other mobile users. Finally, we design a mobile app called I-share in android system to implement system. Meanwhile, we have recruited students to install I-share and simulated the information interaction between mobile users and server. We have conducted experiments by using I-share without/with embedded CAC algorithm to validate the efficiency of two incentive mechanisms. The experimental 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 CPIM outperforms the GIM, offering a higher coverage ratio with lower rewards.