Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 603-607.doi: 10.11896/jsjkx.201000035

• Interdiscipline & Application • Previous Articles     Next Articles

Application of Edge Computing in Flight Training

QIAN Ji-de1,2, XIONG Ren-he1,2, WANG Qian-lei1,2, DU Dong1,2, WANG Zai-jun1,2, QIAN Ji-ye3   

  1. 1 Civil Aviation Flight University of China,Guanghan,Sichuan 618307,China
    2 Key Laboratory of Flight Technology and Flight Safety,CAAC,Guanghan,Sichuan 618307,China
    3 State Grid Chongqing Electric Power Research Institute,Chongqing 400000,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:QIAN Ji-de,born in 1988,Ph.D,research assistant professor,is a member of China Computer Federation.His main research interests include flight operation safety,computer vision,deep learning and edge computing.
    WANG Qian-lei,born in 1996,postgraduate.His main research interests include deep learning and computer vision.
  • Supported by:
    Civil Aviation Flight University of China General Project(J2021-113,J2018-58),United Funds of the Civil Aviation Administration of China and the National Natural Science Foundation of China(U2033213),Special Key Project of Chongqing Technology Innovation and Application Development(cstc2019jscx-mbdxX0027),2019 Civil Aviation Administration Educational Projects(27) and College Students' Innovative Entrepreneurial Training Plan Program(S202010624016).

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Abstract: Eye is an important manifestation of human psychological activities and thoughts in appearance.This paper analyzes the psychological behavior of pilots by using high-speed image acquisition system to track their eye movements,to study the attention of pilots during training.With the gradual maturity of low-power embedded devices and high-speed 5G networks,it has gradually entered a new era of "Internet of Everything".Based on this,this paper proposes a solution to use edge computing devices to evaluate flight training effects.This paper introduces a real-time eye-tracking system based on edge computing architecture,which uses high-speed CMOS image sensors to capture eye images,and proposes a lightweight network structure based on MobileNet to quickly locate the pupil position,and then uses the NVIDIA Jetson Nano board to achieve the function of locating pupil coordinates in continuous video images and calculating the gaze point,to obtain the eye movement visual focus track.The experimental results show that the edge computing system is simple in structure and can meet the requirements of real-time eye tracking.It provides a new and effective method for real-time psychological behavior analysis and provides a reference for improving the effect of flight training.

Key words: Attention distribution, Deep learning, Edge computing, Eye-tracking, Flight training

CLC Number: 

  • TP391
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