From Participatory Sensing to Mobile Crowd Sensing

TL;DR

This paper reviews the evolution of Mobile Crowd Sensing (MCS), highlighting its unique features, system framework, and potential for integrating human and machine intelligence, while discussing future research directions.

Contribution

It provides a comprehensive overview of MCS, introduces a reference framework, and explores the fusion of human and machine intelligence in this sensing paradigm.

Findings

MCS involves implicit and explicit participation.

Data is collected from social networks and sensing.

Future trends include human-machine intelligence integration.

Abstract

The research on the efforts of combining human and machine intelligence has a long history. With the development of mobile sensing and mobile Internet techniques, a new sensing paradigm called Mobile Crowd Sensing (MCS), which leverages the power of citizens for large-scale sensing has become popular in recent years. As an evolution of participatory sensing, MCS has two unique features: (1) it involves both implicit and explicit participation; (2) MCS collects data from two user-participant data sources: mobile social networks and mobile sensing. This paper presents the literary history of MCS and its unique issues. A reference framework for MCS systems is also proposed. We further clarify the potential fusion of human and machine intelligence in MCS. Finally, we discuss the future research trends as well as our efforts to MCS.