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When Compressive Sensing Meets Mobile Crowdsensing

Af: Linghe Kong, Guihai Chen, Bowen Wang Engelsk Paperback

When Compressive Sensing Meets Mobile Crowdsensing

Af: Linghe Kong, Guihai Chen, Bowen Wang Engelsk Paperback
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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 privacy, and detecting false data.

Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices. However, mobile crowdsensing platforms have yet to be widely adopted in practice, the major concern being the quality of the data collected. There are numerous causes: some locations may generate redundant data, while others may not be covered at all, since the participants are rarely systematically coordinated; privacy is a concern for some people, who don''t wish to share their real-time locations, and therefore some key information may be missing; further, some participants may upload fake data in order to fraudulently gain rewards. To address these problematic aspects, compressive sensing, which works by accurately recovering a sparse signal using very few samples, has proven to offer an effective solution.

 


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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 privacy, and detecting false data.

Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices. However, mobile crowdsensing platforms have yet to be widely adopted in practice, the major concern being the quality of the data collected. There are numerous causes: some locations may generate redundant data, while others may not be covered at all, since the participants are rarely systematically coordinated; privacy is a concern for some people, who don''t wish to share their real-time locations, and therefore some key information may be missing; further, some participants may upload fake data in order to fraudulently gain rewards. To address these problematic aspects, compressive sensing, which works by accurately recovering a sparse signal using very few samples, has proven to offer an effective solution.

 


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Produktdetaljer
Sprog: Engelsk
Sider: 127
ISBN-13: 9789811377785
Indbinding: Paperback
Udgave:
ISBN-10: 9811377782
Kategori: Informationsteori
Udg. Dato: 14 aug 2020
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer Verlag, Singapore
Oplagsdato: 14 aug 2020
Forfatter(e): Linghe Kong, Guihai Chen, Bowen Wang
Forfatter(e) Linghe Kong, Guihai Chen, Bowen Wang

Kategori Informationsteori

ISBN-13 9789811377785

Sprog Engelsk

Indbinding Paperback

Sider 127

Udgave

Længde 0mm

Bredde 155mm

Højde 235mm

Udg. Dato 14 aug 2020

Oplagsdato 14 aug 2020

Forlag Springer Verlag, Singapore

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