Effective Opportunistic Crowd Sensing IoT System for Restoring Missing Objects

One of the most important characteristics of the traditional approaches of searching a missing object is a societal and infrastructural participatory crowd sensing where the crowds/participants ´consciously´ opt to register the information in mind, and decide when, where, what, and how to sense and report. While the alert may extend to a broad community, the effectiveness of the crowd sensing doesn´t reach its potential, due to its active participation factor in sensing, reporting, and processing methods. Unless there are clear incentives and privacy protection methods for the crowd sensors, it is considered very hard to achieve its practical deployment in reality. In this paper, we propose to automate the crowd sensing process and radically improve the effectiveness in the IoT System through opportunistic crowd sensing (OCS). Sensing a missing object´s presence in proximity is automatically conducted by smartphones, as the application runs in the background and opportunistically collects and reports the data without active involvement of the user. We address the major technical challenges of privacy, security, sensing effectiveness, and user resource utilization, and validate its operation and effectiveness with the prototype system.