Junqin Huang, Linghe Kong, Hong-Ning Dai, Weiping Ding, Long Cheng, Guihai Chen, Xi Jin, Peng Zeng
IEEE Transactions on Industrial Informatics, vol. 16, no. 10, pp. 6553-6563, Oct. 2020
Publication year: 2020

Abstract

The smart factory is a representative element reshaping conventional computer-aided industry to data-driven smart industry while it is non-trivial to achieve cost effectiveness, reliability, mobility and scalability of smart industrial systems. Data-driven industrial systems mainly rely on sensory data collected from statically-deployed sensors. However, the spatial coverage of industrial sensor networks is constrained due to the high deployment and maintenance cost. Recently, mobile crowd sensing (MCS) has become a new sensing paradigm owing to its merits such as cost effectiveness, mobility and scalability. Nevertheless, traditional MCS systems are vulnerable to malicious attacks and single point of failure due to the centralized architecture. To this end, we integrate MCS with industrial systems without introducing any additional dedicated devices. To overcome the drawbacks of traditional MCS systems, we propose a blockchain-based MCS system.

Keywords

  • Mobile crowd sensing
  • blockchain
  • mobility
  • smart factory
  • scalability
  • security

Bibtex

@ARTICLE{JHuang:TII2020,
  author={J. {Huang} and L. {Kong} and H. {Dai} and W. {Ding} and L. {Cheng} and G. {Chen} and X. {Jin} and P. {Zeng}},
  journal={IEEE Transactions on Industrial Informatics}, 
  title={Blockchain Based Mobile Crowd Sensing in Industrial Systems}, 
  year={2020},
  volume={16},
  number={10},
  pages={6553 - 6563},
}

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