Leveraging communities to boost participation and data collection in mobile crowd sensing

Mobile Crowd Sensing (MCS) is a technique that aims to obtain the participation of volunteers willing to use their smartphones to harvest large quantities of data as they move in urban areas. Those volunteers typically move inside a limited area and can encounter other volunteers during their day activity. From the number and duration of their encounters, it is possible to categorize relations between volunteers. From this knowledge, we classified volunteers in communities that will cooperate to complete a data collection. The main idea is that users inside a cooperation group are more willing to participate in a sensing campaign. The paper presents results of an implementation of our solution in a real testbed, an ongoing experiment that involves more than 170 students from Bologna University campus. In particular, this article focuses on community identification and cooperative task execution. Shown results confirm the feasibility of the proposed approach and report how user activity can be increased leveraging cooperation among them.