From Participatory Sensing to Mobile Crowd Sensing

被引：0
|
作者：
Guo, Bin [1 ]
Yu, Zhiwen [1 ]
Zhou, Xingshe [1 ]
Zhang, Daqing [2 ]
机构：
[1] Northwestern Polytech Univ, Sch Comp Sci, Xian 710072, Peoples R China
[2] Inst TELECOM SudParis, Telecommun Network & Serv Dept, Evry, France
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS (PERCOM WORKSHOPS) | 2014年
基金：
中国国家自然科学基金;
关键词：
Hybrid human-machine intelligence; mobile crowd sensing; participatory sensing; heterogeneous/cross-space data;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：593 / 598
页数：6
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