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Development and Application of a Remote Monitoring System for Agricultural Machinery Operation in Conservation Tillage

Author

Listed:
  • Changhai Luo

    (Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
    These authors contributed equally to this work.)

  • Jingping Chen

    (Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
    These authors contributed equally to this work.)

  • Shuxia Guo

    (Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China)

  • Xiaofei An

    (Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China)

  • Yanxin Yin

    (Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China)

  • Changkai Wen

    (Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China)

  • Huaiyu Liu

    (Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China)

  • Zhijun Meng

    (Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China)

  • Chunjiang Zhao

    (National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China)

Abstract
There is an increasing demand for remote monitoring and management of agricultural machinery operation in conservation tillage. Considering the problems of large errors in detecting operation quality parameters, such as tillage depth and corn straw cover rate, in complex farmland environments, this paper proposes a tillage depth measurement method based on the dual attitude compound of a tractor body and three-point hitch mechanism with lower pull rod and an online measurement method based on K-means clustering of the corn straw cover rate on farmland surface. An operation monitoring terminal was developed for the remote collection of quality parameters of conservation tillage field operation. A remote monitoring system of agricultural machinery operation was constructed and applied over a large area. The field tests showed that the static mean error and root-mean-square error of this method were 0.16 and 0.67 cm for uphill and 0.36 and 0.57 cm for downhill, respectively. For the 28 and 33 cm tillage depth tests, the mean dynamic measurement errors of this method were 0.55 and 0.61 cm, and the root means square errors were 0.64 and 0.73 cm, respectively, and the coefficient of variation of tillage depth did not exceed 3%. The correlation coefficient between the corn straw cover rate detection algorithm based on K-means clustering and the manual image marking method reached 0.92, with an average error of 9.69%, and the accuracy filled the demand for straw cover rate detection. The detection accuracy of tillage depth and straw cover rate was high and thus provides an effective means of information technology support for the quality monitoring and production management of conservation tillage farming operations.

Suggested Citation

  • Changhai Luo & Jingping Chen & Shuxia Guo & Xiaofei An & Yanxin Yin & Changkai Wen & Huaiyu Liu & Zhijun Meng & Chunjiang Zhao, 2022. "Development and Application of a Remote Monitoring System for Agricultural Machinery Operation in Conservation Tillage," Agriculture, MDPI, vol. 12(9), pages 1-22, September.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:9:p:1460-:d:914358
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    References listed on IDEAS

    as
    1. Marco Pittarello & Francesca Chiarini & Cristina Menta & Lorenzo Furlan & Paolo Carletti, 2022. "Changes in Soil Quality through Conservation Agriculture in North-Eastern Italy," Agriculture, MDPI, vol. 12(7), pages 1-12, July.
    2. Ping Xue & Xinru Han & Yongchun Wang & Xiudong Wang, 2022. "Can Agricultural Machinery Harvesting Services Reduce Cropland Abandonment? Evidence from Rural China," Agriculture, MDPI, vol. 12(7), pages 1-15, June.
    3. Yucui Ning & Xu Wang & Yanna Yang & Xu Cao & Yulong Wu & Detang Zou & Dongxing Zhou, 2022. "Studying the Effect of Straw Returning on the Interspecific Symbiosis of Soil Microbes Based on Carbon Source Utilization," Agriculture, MDPI, vol. 12(7), pages 1-16, July.
    4. Shuzhen Yang & Bocai Jia & Tao Yu & Jin Yuan, 2022. "Research on Multiobjective Optimization Algorithm for Cooperative Harvesting Trajectory Optimization of an Intelligent Multiarm Straw-Rotting Fungus Harvesting Robot," Agriculture, MDPI, vol. 12(7), pages 1-24, July.
    Full references (including those not matched with items on IDEAS)

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