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

Changhai Luo, Jingping Chen, Shuxia Guo, Xiaofei An, Yanxin Yin, Changkai Wen, Huaiyu Liu, Zhijun Meng () and Chunjiang Zhao ()
Additional contact information
Changhai Luo: Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
Jingping Chen: Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
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

Agriculture, 2022, vol. 12, issue 9, 1-22

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.

Keywords: conservation tillage; subsoiling operation; operation quality; tillage depth; corn straw cover rate; operation remote monitoring (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2077-0472/12/9/1460/pdf (application/pdf)
https://www.mdpi.com/2077-0472/12/9/1460/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:12:y:2022:i:9:p:1460-:d:914358

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().