Author(s)

Shengken Lin ¹, Honggang Wu ², Tianshun Zhang ³, Jiajie Fei ¹, Shaokun Lu ⁴

Affiliation(s)

¹ Yunnan Agricultural University, Postgraduate Group, Institute of Big Data, Panlong, Kunming, Yunan, China
² Yunnan University of Finance and Economics, Associate Professor, Further Education College, Panlong, Kunming, Yunan, China
³ Yunnan Agricultural University, Associate Professor, Social Service Center, Panlong, Kunming, Yunan, China
⁴ Yunnan Agricultural University, Associate Professor, Big Data College, Panlong, Kunming, Yunan, China

Corresponding Author

Shaokun Lu

ABSTRACT

Place a camera on the agricultural machinery, the video collected by the camera is transmitted by means of a wireless network to enable the operator to monitor the operation of the machinery and provide decisions accordingly when necessary. As video data contains large capacity, and the farmlands are distributed widely and remotely, it is difficult to ensure the stability of the transmission network. In this research, a binary recompression method was proposed to perform a secondary compression on the video sequence compressed by the encoder, which solved the problem of video transmission in dynamic network by reducing the number of bytes of data on the communication channel. The core idea is to change the distribution of the original sequence of "0" and "1" symbols in binary by designing mapping rules and compression rules through the idea of binary rearrangement, so that the same symbols can be gathered together as much as possible, thereby increasing the probability of compression. In the end, a test system was set up to verify that the recompressed transmission scheme proposed in this paper was able to effectively improve the quality of video transmission in farmlands.

KEYWORDS

Video Compression, Network Transmission, Agricultural Machinery Monitoring

CITE THIS PAPER

Shengken Lin, Honggang Wu, Tianshun Zhang, Jiajie Fei, Shaokun Lu, A Streaming Media Recompression Transmission Scheme for Agricultural Machinery Monitoring. Journal of Engineering Mechanics and Machinery (2022) Vol. 7: 75-82. DOI: http://dx.doi.org/10.23977/jemm.2022.070109.

REFERENCES

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Sponsors, Associates, and Links

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