农机远程智能管理平台研发及其应用

doi:10.12133/j.smartag.2020.2.2.202004-SA006

Smart Agriculture ›› 2020, Vol. 2 ›› Issue (2): 67-81.doi: 10.12133/j.smartag.2020.2.2.202004-SA006

• 专题--农业传感器与物联网 • 上一篇下一篇

农机远程智能管理平台研发及其应用

朱登胜¹, 方慧²(), 胡韶明³, 王文权², 周延锁³, 王红艳⁴, 刘飞², 何勇²

^1.金华职业技术学院，浙江金华 321007
^2.浙江大学生物系统工程与食品科学学院，浙江杭州 310058
^3.浙江睿耘科技有限公司，浙江杭州 310053
^4.西部电子商务股份有限公司，宁夏银川 750002

收稿日期:2020-04-15 修回日期:2020-06-14 出版日期:2020-06-30
基金资助:
复杂农田环境下农机导航精准定位技术与装置(2017YFD0700401);宁夏回族自治区重点研发计划重大科技项目(2017BY067);浙江省“数字农机”资源库开发与研究(2017C02031)
作者简介:朱登胜（1962－），男，硕士，教授，研究方向为管理学。E-mail：jh8789@sina.com。
通信作者: 方慧（1973－），女，博士，副研究员，研究方向为农业工程，数字农业。电话：13588433933。E-mail：hfang@zju.edu.cn

Development and Application of an Intelligent Remote Management Platform for Agricultural Machinery

ZHU Dengsheng¹, FANG Hui²(), HU Shaoming³, WANG Wenquan², ZHOU Yansuo³, WANG Hongyan⁴, LIU Fei², HE Yong²

^1.Jinhua Polytechnic, Jinhua 321007, China
^2.College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
^3.Zhejiang Raisinn Technology Co. , Ltd. , Hangzhou 310053，China
^4.West Electronic Business Co. , Ltd. , Yinchuan 310053，China

Received:2020-04-15 Revised:2020-06-14 Online:2020-06-30
corresponding author: FANG Hui, E-mail：hfang@zju.edu.cn
About author:Zhu Dengsheng, E-mail：jh8789@sina.com
Supported by:
Precision Positioning Technology and Equipment for Agricultural Machinery Navigation in Complex Farmland Environments (2017YFD0700401); Ningxia Hui Autonomous Region Key Research and Development Program Major Science and Technology Project (2017BY067); Zhejiang Province "Digital Agricultural Machinery" Resource Development and Research (2017C02031)

摘要/Abstract

摘要：

本研究针对农机管理实时数据少、农机实时作业监管困难、服务信息不对称等问题，首先提出专业化远程管理平台设计时应具有五大原则：专业化、标准化、云平台、模块化以及开放性。基于这些原则，本研究设计了基于大田作业智能传感技术、物联网技术、定位技术、遥感技术和地理信息系统的可定制化的通用农机远程智能管理平台。平台分别为各级政府管理部门、农机合作社、农机手、农户设计并实现了基于WebGIS 的农机信息库及农机位置服务、农机作业实时监测与管理、农田基础信息管理、田间作物基本信息管理、农机调度管理、农机补贴管理、农机作业订单管理等多个实用模块。研究着重分析了在当前的技术背景下，平台部分关键技术的实现方法，包括采用低精度GNSS定位系统前提下的作业面积的计算方法、GNSS定位数据处理过程中的数据问题分析、农机调度算法、作业传感器信息的集成等，并提出了以地块为核心的管理平台建设思路；同时提出农机作业管理平台将逐步从简单作业管理转向大田农机综合管理。本平台对同类型管理平台的研发具有一定的参考与借鉴作用。

关键词: 传感技术, 数据融合, 管理平台, 大田农业机械, 物联网, GNSS

Abstract:

In order to solve problems such as the lack of real-time data in agricultural machinery management, the difficulty in real-time machine operation supervision and the asymmetry of machine service information, an intelligent remote management platform was developed in this research. Firstly, five design principles of a specialized remote agricultural machinery management system: specialization, standardization, cloud platform, modularity and openness were proposed. Based on these principles, a customizable general-purpose intelligent remote management system for agricultural machinery based on intelligent sensing technology, Internet of Things technology, positioning technology, remote sensing technology and geographic information system was designed. Practical modules, including agricultural machinery information-based and location-based services using WebGIS, real-time monitoring and management of machinery operation, basic information management of farmland, basic information management of crops in the field, dispatching management of machinery, subsidy management of machinery, order management of machinery operation were designed and implemented in the platform for users of government agencies, agricultural machinery corporations, machine operators, and farmers. Besides, some key technologies of the platform under the current technical background, including the calculation method of the working area with low-precision GNSS positioning receivers, the analysis of anomality data during the processing of GNSS positioning data, the machine scheduling algorithm development, the integration of sensors were focused， analyzed and implementd. The idea of building the machinery management platform with each individual field as the building block was developed. It can be predicted that the agricultural machinery operation management platform would gradually change from simple operation management to field-level comprehensive management. The research and development of this platform can not only solve current machinery management problems, but also provide basic functions for development of similar machinery management platforms.

Key words: sensing technology, data fusion, management platform, farm machinery, IoT, GNSS

中图分类号:

朱登胜, 方慧, 胡韶明, 王文权, 周延锁, 王红艳, 刘飞, 何勇. 农机远程智能管理平台研发及其应用[J]. 智慧农业(中英文), 2020, 2(2): 67-81.

ZHU Dengsheng, FANG Hui, HU Shaoming, WANG Wenquan, ZHOU Yansuo, WANG Hongyan, LIU Fei, HE Yong. Development and Application of an Intelligent Remote Management Platform for Agricultural Machinery[J]. Smart Agriculture, 2020, 2(2): 67-81.

参考文献

1	WANG N, ZHANG N, WANG M. Wireless sensors in agriculture and food industry—Recent development and future perspective[J]. Computers and Electronics in Agriculture, 2006, 50: 1-14.
2	刘碧贞, 黄华, 祝诗平, 等. 基于北斗/GPS的谷物收割机作业综合管理系统[J]. 农业工程学报, 2015， 31（10）: 204-210.
2	LIU B, HUANG H, ZHU S, et al. Integrated management system of grain combine harvester based on Beidou & GPS [J]. Transactions of the CSAE, 2015, 31(10): 204-210.
3	刘振宇, 梁建平. 基于BDS的农机精确调度和高效作业平台设计与应用[J]. 中国农机化学报, 2018, 39(10): 97-102.
3	LIU Z, LIANG J. Design and application of precision scheduling and efficient operation platform for agricultural machinery based on BDS [J]. Journal of Chinese Agricultural Mechanization, 2018, 39(10): 97-102.
4	叶文超, 张小花, 廖东东, 等. 基于Android的农机调度与管理平台设计与应用[J]. 仲恺农业工程学院学报, 2019, 32(3): 53-57.
4	YE W, ZHANG X, LIAO D, et al. Design and application of agricultural machinery scheduling and management platform based on Aandroid [J]. Journal of Zhongkai University of Agriculture and Engineering, 2019, 32(3): 53-57.
5	张俊艺, 冯泽佳, 高磊, 等. 基于Android系统的农机调度管理平台的设计与开发[J]. 中国农机化学报, 2018, 39(5): 91-96.
5	ZHANG J, FENG Z, GAO L, et al. Design and development of agricultural machinery dispatching management platform based on Android system [J]. Journal of Chinese Agricultural Mechanization, 2018, 39(5): 91-96.
6	刘娜. 农机信息化综合服务平台设计——基于智慧城市嵌入式快递系统[J]. 农机化研究, 2020, 42(5): 196-200.
6	LIU N. Design of agricultural machinery information integrated service platform based on intelligent express delivery system of smart city [J]. Journal of Agricultural Mechanization Research, 2020, 42(5): 196-200.
7	王春山, 张璠, 滕桂法, 等. 智慧农机调配管理平台设计与实现[J]. 中国农机化学报, 2018, 39(1): 61-68.
7	WANG C, ZHANG F, TENG G, et al. Design and implementation of smart agricultural machinery platform[J]. Journal of Chinese Agricultural Mechanization, 2018, 39(1): 61-68.
8	姚强, 郭彩霞, 吕斌. 农业机械远程管理信息系统研究[J]. 农业网络信息, 2018 (2): 26-32.
8	YAO Q, GUO C, LYU B, et al. Research on the remote management information system of agricultural machinery[J]. Agriculture Network Information, 2018 (2): 26-32.
9	刘文娜. 农业机械远程控制管理与农机化信息服务[J]. 河北农机, 2015(4): 35.
9	LIU W. Agricultural machinery remote control management and agricultural mechanization information service [J]. Hebei Agricultural Machinery, 2015(4): 35.
10	刘阳春, 苑严伟, 张俊宁. 深松作业远程管理系统设计与试验[J]. 农业机械学报, 2016, 47(S1): 43-48.
10	LIU Y, YUAN Y, ZHANG J, et al. Design and experiment of remote management system for subsoiler [J]. Transactions of the CSAM, 2016, 47(S1): 43-48.
11	蒋浩. 基于RTK技术的农业机械自动导航系统研究[D]. 杭州: 浙江大学, 2019.
11	JIANG H. Research on automatic navigation system of agricultural machinery based on RTK technology[D]. Hangzhou: Zhejiang University, 2019.
12	GAO W, PAN S, GAO C, et al. Tightly combined GPS and GLONASS for RTK positioning with consideration of differential inter-system phase bias[J]. Measurement Science and Technology, 2019, 30(5): ID 054001.
13	庄晓霖. 基于机器视觉的路径识别及避障导航系统[D]. 广州: 华南农业大学, 2016.
13	ZHUANG X. Path recognition and obstacle avoidance navigation system based on machine vision [D]. Guangzhou: South China Agricultural University, 2016.
14	HARIK E C, KORSAETH A. Combining hector slam and artificial potential field for autonomous navigation inside a greenhouse[J]. Robotics, 2018, 7(2): ID 22.
15	孟庆宽, 张漫, 杨耿煌, 等. 自然光照下基于粒子群算法的农业机械导航路径识别[J]. 农业机械学报, 2016(6): 356-360.
15	MENG Q, ZHANG M, YANG G, et al. Guidance line recognition of agricultural machinery based on particle warm optimization under natural illumination[J]. Transactions of the CSAM, 2016(6): 356-360.
16	王雪阳, 苑侗侗, 苑迎春, 等. 带时间窗的农机调度方法研究[J]. 河北农业大学学报, 2016, 39(6): 117-123.
16	WANG X, YUAN T, YUAN Y, et al. A study on method of agricultural scheduling with time-window [J]. Journal of Agricultural University of Hebei, 2016, 39(6): 117-123.
17	EDWARDS G T C, HINGE J, SKOU-NIELSEN N, et al. Route planning evaluation of a prototype optimised infield route planner for neutral material flow agricultural operations[J]. Biosystems Engineering, 2017, 153: 149-157.
18	CONESA-MU?OZ J, BENGOCHEA-GUEVARA J M, ANDUJAR D, et al. Route planning for agricultural tasks: A general approach for fleets of autonomous vehicles in site-specific herbicide applications[J]. Computers and Electronics in Agriculture， 2016, 127: 204-220.
19	SETHANAN K, NEUNGMATCHA W. Multi-objective particle swarm optimization for mechanical harvester route planning of sugarcane field operations[J]. European Journal of Operational Research, 2016, 252(3): 969-984.
20	SEYYEDHASANI H, DVORAK J S. Reducing field work time using fleet routing optimization[J]. Biosystems Engineering， 2018, 169: 1-10.
21	SPINGAEL J, PATERNOSTER A, BRAET J. Reducing postharvest losses of apples: Optimal transport routing (while minimizing total costs)[J]. Computers and Electronics in Agriculture, 2018, 146: 136-144.
22	SEYYEDHASANI H, DVORAK J S. Using the vehicle routing problem to reduce field completion times with multiple machines[J]. Computers and Electronics in Agriculture, 2017, 134: 142-150.
23	王文权. 带时间窗农机调度问题模型及算法研究[D]. 杭州: 浙江大学, 2019.
23	WANG W. Research on models and algorithms for agricultural machinery scheduling problem with time window[D]. Hangzhou: Zhejiang University, 2019.

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农机远程智能管理平台研发及其应用

Development and Application of an Intelligent Remote Management Platform for Agricultural Machinery

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