Chinese Journal on Internet of Things ›› 2020, Vol. 4 ›› Issue (4): 26-31.doi: 10.11959/j.issn.2096-3750.2020.00202

• Topic:IoT+Energy • Previous Articles     Next Articles

CSI-based underground personnel behavior identification method

Lei ZHANG1,Yue ZHANG2(),Mingxue LI3,Xinguo SHI4,Bo ZHAI4,Weilong WANG4   

  1. 1 School of Information Engineering (School of Big Data),Xuzhou University of Technology,Xuzhou 221000,China
    2 IoT (Perception Mine) Research Center,China University of Mining and Technology,Xuzhou 221000,China
    3 School of Electrical and Power Engineering,China University of Mining and Technology,Xuzhou 221000,China
    4 Information Center,Shandong Energy Zibo Mining Group Co.,Ltd.,Zibo 225100,China
  • Revised:2020-10-08 Online:2020-12-30 Published:2020-12-14
  • Supported by:
    The National Key R&D Program of China(2017YFC0804400)

Abstract:

To solve the problem of personnel behavior identification under the condition of dust environment and shielding and to promote the coal mine safety production,a personnel identification method based on the Wi-Fi channel state information (CSI) was proposed.The system used Hampel filter and median filter to process the raw CSI data,and utilized the phase information through a linear correction method.The recognition process was divided into the offline stage and online stage.In the offline stage,different activities data was collected to establish the recognition model.While in the online stage,current actions were recognized according to the recognition model.8 different human activities were set in the experiments and the result indicated that the recognition accuracy of this system could reach 95%.

Key words: coal mine safety, channel state information, underground personnel behavior identification, Wi-Fi, principal component analysis

CLC Number: 

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