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024 7 _a10.1007/978-981-13-7776-1
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082 0 4 _a004.167
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100 1 _aKong, Linghe.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aWhen Compressive Sensing Meets Mobile Crowdsensing
_h[electronic resource] /
_cby Linghe Kong, Bowen Wang, Guihai Chen.
250 _a1st ed. 2019.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2019.
300 _aXII, 127 p. 39 illus., 35 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction -- Mathematical Theory of Compressive Sensing -- Basic Compressive Sensing for Data Reconstruction -- Bayesian Compressive Sensing for Task Allocation -- Adaptive Compressive Sensing for Incentive Mechanism -- Encoded Compressive Sensing for Privacy Preservation -- Iterative Compressive Sensing for Fault Detection -- Conclusion.
520 _aThis 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. .
650 0 _aMobile computing.
650 0 _aComputer networks .
650 0 _aData structures (Computer science).
650 0 _aInformation theory.
650 1 4 _aMobile Computing.
650 2 4 _aComputer Communication Networks.
650 2 4 _aData Structures and Information Theory.
700 1 _aWang, Bowen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aChen, Guihai.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811377754
776 0 8 _iPrinted edition:
_z9789811377778
776 0 8 _iPrinted edition:
_z9789811377785
856 4 0 _uhttps://doi.org/10.1007/978-981-13-7776-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
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