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...

詳細記述

書誌詳細

出版年:	IEEE Access
主要な著者:	Wenbin Liu, Yongjian Yang, En Wang, Leye Wang, Djamal Zeghlache, Daqing Zhang
フォーマット:	論文
言語:	英語
出版事項:	IEEE 2019-01-01
主題:	Sparse mobile crowdsensing reinforcement learning compressive sensing urban sensing
オンライン･アクセス:	https://ieeexplore.ieee.org/document/8743361/