基于北斗的农机作业大数据系统构建  

Construction of big data system of agricultural machinery based on BeiDou

作　　者：吴才聪[1,2] 陈瑛 杨卫中[1,2] 杨丽丽 乔鹏[1,2,3] 马钦 翟卫欣[1,2] 李冬 张晓强 万传峰[1,2] 李光远 黄嘉华 田伟泽 范雪枫 谈陆军 苏春华 Wu Caicong;Chen Ying;Yang Weizhong;Yang Lili;Qiao Peng;Ma Qin;Zhai Weixin;Li Dong;Zhang Xiaoqiang;Wan Chuanfeng;Li Guangyuan;Huang Jiahua;Tian Weize;Fan Xuefeng;Tan Lujun;Su Chunhua(College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China;Key Laboratory of Agricultural Machinery Monitoring and Big Data Applications,Ministry of Agriculture and Rural Affairs,Beijing 100083,China;College of Engineering,Peking University,Beijing 100871,China;Agricultural Mechanization General Station,Ministry of Agriculture and Rural Affairs,Beijing 100122,China)

机构地区：[1]中国农业大学信息与电气工程学院,北京100083 [2]农业农村部农机作业监测与大数据应用重点实验室,北京100083 [3]北京大学工学院,北京100871 [4]农业农村部农业机械化总站,北京100122

出　　处：《农业工程学报》2022年第5期1-8,共8页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家精准农业应用项目(No.JZNYYY001)。

摘　　要：针对全国范围农机作业动态监测和量化统计的应用需求,该研究通过在农业机械上安装北斗终端,制订数据传输规范,完成了基于北斗的农机作业大数据系统建设。该系统由农业机械及北斗终端、农机制造企业物联网平台和农机作业大数据管理服务平台3部分组成。系统共接入农机290153辆。经数据清洗、轨迹分割和参数提取3个数据处理步骤,可获得农机的工作时长、行驶里程和作业面积等基本统计量。以2021年夏小麦机械化收割为例,利用该系统进行数据获取、处理和统计分析,输出收割机分布热力图和作业重心转移图,进行了收割时长、收割效率与收割面积等统计,分析了小麦主产区对跨区作业的依赖程度。麦收期间在线收割机累计35243辆,日均18568辆,收割时长中位数均值为8.3 h/d,收割面积中位数均值为5.5 hm^(2)/d,约75%的小麦收割机进行了跨区作业,跨区距离中位数约为597 km。应用结果表明,农机作业大数据系统可准确开展数据处理和作业统计,可以向农业农村部门、农机制造企业、农机合作社和农机手提供作业动态监测和数据分析服务。Big data analysis has offered much greater statistical power around the world in recent years,particularly with the ever-increasing information technology,such as positioning,sensing,and mobile communication.In the field of agriculture,big data has also presented the promising potential to promote the terminals of the BeiDou Navigation Satellite System on agricultural machinery in China.However,the current management can be decentralized fail to form the nationwide operation of agricultural machinery using the big data system and service scheme,due mainly to the rapid increase of the data.In this study,a new big data system of BeiDou terminals was developed to compile,the data transmission specifications of platform-to-platform for the nationwide dynamic monitoring and quantitative statistical analysis of agricultural machinery operations in China.Three parts of the big data system were also installed in the agricultural machinery of the manufacturers.The first part was involved the agricultural machinery and the BeiDou/GNSS terminals.The second part was the Internet of Things(IoTs)platform for agricultural machinery for manufacturers.The third part was the big data management and service platform for the agricultural machinery operation by the BeiDou Team of China Agricultural University.Specifically,the BeiDou terminals were used to collect the position and working condition data of agricultural machinery.The gathered information was forwarded in real time to the manufacturers,then to the big data management and service platform.There were 290153 sets of agricultural machinery in the big data system.Data mining and statistical analysis were performed on the big data management and service platform.The information products were generated to process the operation data on the big data management and service platform using three major procedures,including data cleaning,trajectory segmentation,and parameter extraction.In addition,the basic statistics were achieved,such as the working hours,driving mileage,and workin

关 键 词：农业机械 大数据 北斗 跨区作业 

分 类 号：S24[农业科学—农业电气化与自动化]