When Compressive Sensing Meets Mobile Crowdsensing
This book provides a comprehensive introduction to applying compressive sensing to improve data quality in the context of mobile crowdsensing. It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user pr
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ompressive Sensing Meets Mobile Crowdsensing
When Compressive Sensing Meets Mobile Crowdsensing
Linghe Kong Bowen Wang Guihai Chen •
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When Compressive Sensing Meets Mobile Crowdsensing
123
Linghe Kong Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai, China
Bowen Wang ByteDance Ltd. Beijing, China
Guihai Chen Department of Computer Science Nanjing University Nanjing, China
ISBN 978-981-13-7775-4 ISBN 978-981-13-7776-1 https://doi.org/10.1007/978-981-13-7776-1
(eBook)
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Preface
“I would recommend strongly this valuable and impactful monograph to researchers who are interested in the frontier of data management in mobile crowdsensing.” —Prof. Laurence Tianruo Yang St Francis Xavier University, Canada Fellow of the Canadian Academy of Engineering “An valuable book brings together systematic Compressive Sensing with Mobile Crowdsensing and shows a promising possible future direction.” —Prof. Meikang Qiu Columbia University, USA “This monograph presents strategic insights for data quality challenge in mobile crowdsensing by leveraging compressive sensing. I would sincerely invite you to read and comment this book.” —Prof. Jinjun Chen Swinburne University of Technology, Australia Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to join in data collection tasks using powerful mobile devices. However, date mobile crowdsensing platforms have yet to be widely adopted in practice. The major concern is the quality of the data collected by mobile crowdsensing. There are numerous causes: some locations may generate redu
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