Improved Huffman coding-based data transmission and compression method for agricultural machinery operation

Abstract: In order to solve the poor communication environment problem of agricultural machinery operation state data transmission caused by the unbalanced coverage of a mobile communication base station, a data filtering and data compression method based on an improved Huffman coding technique was proposed for data selecting, compression, transmission, parsing, and extracting in this paper. First, the agricultural machinery operation data types, exchange mode, and compression mode were defined. Then, data collection and exchange were realized based on a Compass/GPS dual-mode state data collection terminal. Finally, an improved Huffman coding technique was proposed. At present, most of the data transmission is using a compression-decompression method to ensure data integrity of data transmission, which can reduce the data traffic and save many communication costs, but its disadvantages are also obvious. The disadvantages are fewer on the terminal in the data transmission, and are mainly manifested in the need to compress the data of each group, leading to delayed transmission time, which will affect the platform performance. Considering the common problem of an agricultural machinery state data collection terminal and monitoring platform, a driving state data optimization method combined with platform data recognition was proposed in this paper, whose research has practical significance for the platform designing of data collection, transmission, and monitoring. To achieve data transmission and access, the design of a monitoring platform necessarily must use data extraction methods combined with terminal data optimization. That is, adding the terminal data processing optimization algorithm while designing a terminal data transmission module to overcome the pressure of the data management system for wireless communications and the corresponding pressure for a backstage management system. At the same time, adding data extraction and recognition algorithms while monitoring platform receiving data could optimize the expression of data and reduce the amount of data, so as to improve the efficiency of the whole system. Data compression and decompression testing results showed that it could obtain a 55.08% compression ratio with 412.56 kb transmission operation data length by the data acquisition cycle of 5 seconds, and the error rate of data transmission and data transmission packet loss rate were 2.47% and 4.18% respectively, while the error rate of data transmission and data transmission packet loss rate fell to 2.06% and 0.78% respectively at the same screening requirements of the selecting compression and transmission. This method can achieve the requirements of agricultural machinery operation state data compression and transmission. In the compression and transmission mode of single data packet with less data and short transmission time, it could obtain a lower transmission error rate and transmission packet loss rate. Moreover, the method has less computation and high compression efficiency characteristics, which are suitable for data transmission in the agricultural machinery operation area.