# From Participatory Sensing to Mobile Crowd Sensing

arXiv: https://arxiv.org/abs/1401.3090 · HTML: https://mlsanity.com/paper/1401.3090/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Jan 2014.

## Built on by (most cited first, 3 of 3)

- [Artificial Collective Intelligence Engineering: a Survey of Concepts and Perspectives](https://mlsanity.com/paper/2304.05147/) (2023)
- [Citizen participation: crowd-sensed sustainable indoor location services](https://mlsanity.com/paper/2310.16496/) (2023)
- [Energy Minimization for Participatory Federated Learning in IoT Analyzed via Game Theory](https://mlsanity.com/paper/2503.21722/) (2025)

## Abstract (arXiv)

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.