Crowd Sensing Applications: A Distributed Flow-Based Programming Approach

摘要

Over the past few years, there has been an increasing demand for crowd sensing applications. While existing mobile app designers greatly facilitate the development of crowd sensing applications for non-ICT experts, they do not yet provide technological support for other aspects required to manage crowd sensing applications, such as support for data gathering campaigns, advanced forms of data aggregation, and participant coordination. In this paper, we present DisCoPar, a novel platform for designing crowd sensing applications, which utilises a distributed flow-based programming approach to facilitate the development of mobile applications and their matching server-side logic. The data-driven nature of our approach enables users to contribute data and receive feedback in real-time, which greatly facilitates user collaboration. We demonstrate the features of our prototype platform by creating a noise measuring application with a corresponding collaborative data collection campaign.