Crowd-Machine Hybrid Urban Sensing and Computing

Jiangtao Wang; Leye Wang; Yanhui Song

doi:10.1109/MC.2020.3023931

Crowd-Machine Hybrid Urban Sensing and Computing

Jiangtao Wang
, Leye Wang
, Yanhui Song

Research output: Contribution to journal › Article › peer-review

Abstract

With progress in the Internet of Things, artificial intelligence, and cloud/edge computing, urban sensing and computing (USC) has become a promising solution to address the challenges in modern cities. This article investigates how to combine the power of human/crowd and machine intelligence to enable more innovative USC applications.

Original language	English
Pages (from-to)	26 - 34
Number of pages	9
Journal	Computer
Volume	54
Issue number	4
DOIs	https://doi.org/10.1109/MC.2020.3023931
Publication status	Published - 9 Apr 2021
Externally published	Yes

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Cite this

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title = "Crowd-Machine Hybrid Urban Sensing and Computing",

abstract = "With progress in the Internet of Things, artificial intelligence, and cloud/edge computing, urban sensing and computing (USC) has become a promising solution to address the challenges in modern cities. This article investigates how to combine the power of human/crowd and machine intelligence to enable more innovative USC applications. ",

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AB - With progress in the Internet of Things, artificial intelligence, and cloud/edge computing, urban sensing and computing (USC) has become a promising solution to address the challenges in modern cities. This article investigates how to combine the power of human/crowd and machine intelligence to enable more innovative USC applications.

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DO - 10.1109/MC.2020.3023931

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VL - 54

SP - 26

EP - 34

JO - Computer

JF - Computer

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Crowd-Machine Hybrid Urban Sensing and Computing

Abstract

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