Mobile crowd sensing and computing: when participatory sensing meets participatory social media

Bin Guo (1) , Chao Chen (2) , Daqing Zhang (3, 4, 5, 6) , Zhiwen Yu (1) , Alvin Chin (7)

1 NPU - Northwestern Polytechnical University [Xi'an]
2 Chongqing University [Chongqing]
3 ACMES-SAMOVAR - Architecture, Cloud continuum, formal Models, artificial intElligence and Services in distributed computing
4 TSP - RST - Département Réseaux et Services de Télécommunications
5 SAMOVAR - Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux
6 CNRS - Centre National de la Recherche Scientifique
7 Microsoft Research Asia

With the development of mobile sensing and mobile social networking techniques, mobile crowd sensing and computing (MCSC), which leverages heterogeneous crowdsourced data for large-scale sensing, has become a leading paradigm. Built on top of the participatory sensing vision, MCSC has two characteristic features: it leverages heterogeneous crowdsourced data from two data sources: participatory sensing and participatory social media; and it presents the fusion of human and machine intelligence in both the sensing and computing processes. This article characterizes the unique features and challenges of MCSC. We further present early efforts on MCSC to demonstrate the benefits of aggregating heterogeneous crowdsourced data

Domaines: Réseaux et télécommunications [cs.NI]

Bin Guo, Chao Chen, Daqing Zhang, Zhiwen Yu, Alvin Chin. Mobile crowd sensing and computing: when participatory sensing meets participatory social media. IEEE Communications Magazine, 2016, 54 (2), pp.131 - 137. ⟨hal-01346705⟩