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Remote video monitoring system is a comprehensive technology integrating multimedia image processing technology, network communication technology, automatic control technology and intelligent alarm technology. It is one of the important equipment to realize the automation of traction substation. Remote video monitoring system involves video compression standard selection, video acquisition, encoding / decoding, image real-time display, video error control and recovery, video equipment control and other video technologies, as well as network structure design, multi-threaded synchronous control, fault-tolerant coding, network protocol selection and other network communication technologies. With the emergence of 3D technology, high-definition technology and high-definition video (Liu, 2021), people have obtained richer visual experience (Yadav, 2021). HD video technology is widely used in various fields, such as HD video conference, video on demand and home video monitoring (Liddo et al., 2020). The amount of video data increases with the improvement of program source quality, and the bandwidth increases gradually in the transmission process. Video definition increases with the increase of temporal resolution and spatial resolution (Moghaddam et al., 2019). Under the above background, the parallel decoding method of remote video monitoring system has become a research hotspot. At present, the parallel decoding method of remote video monitoring system has the problems of high video distortion rate and low decoding efficiency. It is necessary to study the parallel decoding method of remote video monitoring system (Chen et al., 2021).
Zhou adopts the software-based MPEG-4 (Moving picture expert group-4) compression coding method based on software is adopted, and a simple camera is used to realize real-time acquisition and wireless transmission of video signals. The self-developed ActiveX control is embedded in the web page, which has the function of video decoding to realize the real-time dynamic display of video information in the computer browser of the monitoring terminal. Secondly, in order to realize the intelligent control of wireless networks, the attitude planning based on reverse motion is studied. The linkage coordinate system of wireless network remote monitoring is established by DH parameter method, and the kinematics formula is deduced. The geometric analysis method is used to calculate the motion trajectory of remote monitoring, accurately locate each angle of remote monitoring, and obtain the best motion path. The permanent magnet angle control method based on fuzzy neural network combines RBF neural network, fuzzy control and permanent magnet control, and uses the self-learning ability and fuzzy reasoning ability of neural network to carry out fuzzy control. Adjust the end effector to the target position. Finally, the mathematical model is simulated by MATLAB to verify the characteristics of wireless network remote monitoring. Masuda et al. have proposed a three-dimensional magnetic recording technology using microwave-assisted magnetic recording and spin torque oscillator as reading sensors has been proposed as a candidate technology for future recording technology. The read / write channel of envelope model is constructed to evaluate various signal processing of three-dimensional magnetic recording. The low density parity check coding and iterative decoding system (including Turbo Equalization) is applied to the three-dimensional magnetic recording channel model with point position fluctuation, and its bit error rate performance is evaluated by computer simulation. Enyu et al. proposed a new TWDR selection scheme for joint decoding, partial decoding, bit level XOR and overlay coding schemes of bidirectional decoding and forward relay.