Volume 50 Issue 5
May  2024
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CHEN Jia, WANG Qi, WANG Peng. SEI based intelligent monitoring video transmission method for coal mines[J]. Journal of Mine Automation,2024,50(5):93-98.  doi: 10.13272/j.issn.1671-251x.2023100025
Citation: CHEN Jia, WANG Qi, WANG Peng. SEI based intelligent monitoring video transmission method for coal mines[J]. Journal of Mine Automation,2024,50(5):93-98.  doi: 10.13272/j.issn.1671-251x.2023100025

SEI based intelligent monitoring video transmission method for coal mines

doi: 10.13272/j.issn.1671-251x.2023100025
  • Received Date: 2023-10-10
  • Rev Recd Date: 2024-05-18
  • Available Online: 2024-06-13
  • Currently, there is a high latency problem in the transmission of video surveillance data in coal mines, and the main cause of video transmission delay is encoding delay. In order to solve the above problems, a intelligent monitoring video transmission method for coal mines based on media supplemental enhancement information(SEI) without video encoding is proposed. This method caches a copy of the compressed video frame obtained by demultiplexing the video stream, and decodes the compressed video frame to obtain the decoded video frame. The method stores the AI model analysis results in the decoded video frame through SEI, writes the custom SEI into the network extraction layer unit corresponding to the compressed video frame copy of the decoded video frame based on the timestamp correspondence. The method multiplexes the compressed video frame copy to achieve real-time transmission of coal mine intelligent monitoring videos. Experimental testing of this method is conducted on a 24 core CPU. The results show that for videos with a resolution of 1280×720, the overall CPU utilization rate for video processing using this method decreases from 24.7% to 36.3% when using traditional methods to 20.3% to 23.9%. The end-to-end delay decreases from 1946 ms to 345 ms. For videos with a resolution of 1920×1080, the overall CPU utilization rate for video processing using this method decreases from 29.2% to 41.8% using traditional methods to 18.5% to 26.3%. The end-to-end latency decreases from 6204 ms to 479 ms. This method reduces the transmission delay of coal mine intelligent monitoring videos by avoiding the video encoding process, saves CPU or GPU resources required for video encoding, and reduces the hardware cost of the intelligent video monitoring system.

     

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