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Development and application of subsoiling monitoring system based on edge computing using IoT architecture

文献类型： 外文期刊

作者： Yin, Yanxin 1 ; Zhao, Chunjiang 1 ; Zhang, Yawei 3 ; Chen, Jingping 1 ; Luo, Changhai 1 ; Wang, Pei 1 ; Chen, Liping 1 ; Meng, Zhijun 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Res Ctr Intelligent Equipment, Beijing 100097, Peoples R China

2.Natl Engn Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

3.China Agr Univ, Coll Engn, Beijing 100083, Peoples R China

关键词： Subsoiling; Monitoring system; Edge computing; Cloud computing; IoT

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：6.757； 五年影响因子：6.817 ）

ISSN： 0168-1699

年卷期： 2022 年 198 卷

页码：

收录情况： SCI

摘要： An edge computing based monitoring system using Internet of Things architecture (IoT) was proposed, aiming at automatically monitoring subsoiling parameters, counting subsoiling quantity, evaluating subsoiling quality, analyzing subsoiling efficiency and managing subsoiling operation. In this study, tillage depth computing algorithm based on motion attitudes of tractor and subsoiler was studied, and an edge computing device was developed to collect and process subsoiling data in real-time. A cloud-end data interaction mechanism was designed to provide a safe, stable and reliable way for data transmission between the device and cloud. Highperformance cloud computing was used to count indicators of subsoiling quantity such as total area, effective area and operation mileage, evaluate subsoiling quality indicators such as average tillage depth and area compliance rate, and analyze subsoiling efficiency indicators such as time utilization rate and effective mileage rate. Field tests showed that the error of tillage depth detection was less than 1.2 cm, and the error of subsoiling area detection was less than 1%. The subsoiling data in 2021 from a selected units in the system showed that the system could count the subsoiling quantity, analyze the subsoiling quality and efficiency, and meet the requirements of subsoiling monitoring and management by the friendly human-computer interaction interface. The subsoiling data collected for 7 years by the system was analyzed, and results showed that the total registered edge computing device number was 51,252, the peak value of annual cumulative on-line number was 20,560, the peak value of single-day on-line was 6,694, the peak data transmission rate was 0.034 GB/s, the peak value of single-day concurrent calculation subsoiling area was 43,900 ha, and the cumulative monitoring subsoiling area was 8.98 million hectares, which showed that the system has good concurrent calculation ability and stable and reliable operation. This paper provides an efficient monitoring, statistics, analysis and management tool for large-scale subsoiling, and has high practical value.

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