Multi-Dimensional Urban Sensing in Sparse Mobile Crowdsensing

Multi-Dimensional Urban Sensing in Sparse Mobile Crowdsensing

Sparse mobile crowdsensing (MCS) is a promising paradigm for the large-scale urban sensing, which allows us to collect data from only a few areas (cell selection) and infer the data of other areas (data inference). It can significantly reduce the sensing cost while ensuring high data quality. Recent...

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Bibliographic Details
Main Authors: Wenbin Liu, Yongjian Yang, En Wang, Leye Wang, Djamal Zeghlache, Daqing Zhang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Sparse mobile crowdsensing
reinforcement learning
compressive sensing
urban sensing
Online Access:https://ieeexplore.ieee.org/document/8743361/

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