Building human-machine intelligence in mobile crowd sensing

Bin Guo; Chao Chen; Zhiwen Yu; Daqing Zhang; Xingshe Zhou

doi:10.1109/MITP.2015.50

Building human-machine intelligence in mobile crowd sensing

Bin Guo
, Chao Chen
, Zhiwen Yu
, Daqing Zhang
, Xingshe Zhou

Northwestern Polytechnical University
Chongqing University
Institut Mines-Télécom

Résultats de recherche: Contribution à un journal › Article › Revue par des pairs

Résumé

Mobile crowd sensing and computing (MCSC) is a large-scale sensing and collective knowledge discovery paradigm that fuses human and machine intelligence. This article describes the content of human and machine intelligence, their complementary roles, and their potential collaboration modes in MCSC. The authors also discuss the challenges that arise from using human intelligence in MCSC systems. They further present several applications to demonstrate the power and usage of human-machine intelligence in MCSC.

langue originale	Anglais
Numéro d'article	7116427
Pages (de - à)	46-52
Nombre de pages	7
journal	IT Professional
Volume	17
Numéro de publication	3
Les DOIs	https://doi.org/10.1109/MITP.2015.50
état	Publié - 1 mai 2015
Modification externe	Oui

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10.1109/MITP.2015.50

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title = "Building human-machine intelligence in mobile crowd sensing",

abstract = "Mobile crowd sensing and computing (MCSC) is a large-scale sensing and collective knowledge discovery paradigm that fuses human and machine intelligence. This article describes the content of human and machine intelligence, their complementary roles, and their potential collaboration modes in MCSC. The authors also discuss the challenges that arise from using human intelligence in MCSC systems. They further present several applications to demonstrate the power and usage of human-machine intelligence in MCSC.",

keywords = "collaborative sensing, human-machine intelligence, mobile crowd sensing and computing, participatory sensing",

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AB - Mobile crowd sensing and computing (MCSC) is a large-scale sensing and collective knowledge discovery paradigm that fuses human and machine intelligence. This article describes the content of human and machine intelligence, their complementary roles, and their potential collaboration modes in MCSC. The authors also discuss the challenges that arise from using human intelligence in MCSC systems. They further present several applications to demonstrate the power and usage of human-machine intelligence in MCSC.

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Building human-machine intelligence in mobile crowd sensing

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