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Mobile Crowdsensing

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When Compressive Sensing Meets Mobile Crowdsensing

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Abstract

Supported by the large quantity of mobile devices embedded with rich sensors, Mobile Crowdsensing (MCS) leverages these devices to sense and contribute data in order to extract intelligence and provide corresponding services. Since most MCS applications rely on high-quality sensing data, plenty of quality-aware incentive mechanisms, authentications mechanisms, preprocessing algorithms, or outlier detection on sensed data are proposed for quality management in MCS projects. In this chapter, we will introduce the data quality problem in MCS, together with existing solutions except compressive sensing.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

    Linghe Kong

  2. ByteDance Ltd., Bei**g, China

    Bowen Wang

  3. Department of Computer Science, Nan**g University, Nan**g, China

    Guihai Chen

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  1. Linghe Kong
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  2. Bowen Wang
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  3. Guihai Chen
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Correspondence to Linghe Kong .

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Kong, L., Wang, B., Chen, G. (2019). Mobile Crowdsensing. In: When Compressive Sensing Meets Mobile Crowdsensing. Springer, Singapore. https://doi.org/10.1007/978-981-13-7776-1_2

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  • DOI: https://doi.org/10.1007/978-981-13-7776-1_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-7775-4

  • Online ISBN: 978-981-13-7776-1

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