云农场智慧服务大数据平台设计与实现

doi:10.19788/j.issn.2096-6369.210402

Abstract

Abstract:

With the wide use of modern information technology in the field of agriculture, a massive amount of agricultural data can now be collected and analyzed to promote the development of agricultural modernization. This paper considers the existing research of the whole industry chain of production and management of the special agricultural products of the Dabie Mountain region. Systematical analysis was conducted to determine the characteristics of the data of various industry value chains, such as the production, processing, and marketing of agricultural products in this region. Moreover, the data resources of agricultural production and management were effectively integrated. Subsequently, the design pattern of a big data platform architecture, which includes four layers, an infrastructure layer, a data resource layer, a data processing and analysis layer, and a data display layer, was adopted. The data resource database was built for the whole industry chain of Dabie Mountain agricultural products. This database was based on the Hadoop big data framework and a big data platform for the smart services of a cloud server farm. Specifically, the platform’s functions were developed for the business tasks required by the relevant agricultural employees in the industrial area. The data in the developed database were successively processed by data cleaning, data mining, and data modeling to explore the regular dynamic changes in agricultural product production and management. Smart service functions such as information sharing, smart early warnings, and auxiliary decision-making were realized. In particular, the information sharing function offers data resource sharing services for each subsystem of the big data platform; the smart early warning function provides early warning services for production environment, price, and other key indices of agricultural products during the production and operation of the overall agricultural product industry value chain; the auxiliary decision-making function notifies agricultural practitioners of changes in the production and operation of agricultural products within the industry’s region and provides services such as auxiliary business decision-making services. The research and development of the cloud-based smart service big-data management center and data visualization system will be a useful reference for promoting the development of information and intelligence of the whole industry chain of special agricultural products in the Dabie Mountain region.

Key words: cloud farm, Hadoop, smart service, big data platform

CLC Number:

TP311.1

Nuojuan Ling, Yuan Rao. Design and Implementation of a Big Data Platform for Cloud Server Farm Smart Services[J].Journal of Agricultural Big Data, 2021, 3(4): 10-19.

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序号	功能需求	需求描述	建设内容
1	数据资源录入存储	针对大别山区农产品全产业链各环节数据资源的整体录入，根据数据录入方案配置，完成录入数据整合汇总等功能。同时，支持农业物联网等设备装配农产品生产经营过程的数据传输方式。	云农场智慧服务大数据录入系统
2	数据加工处理	将汇聚到平台中的数据资源进行抽取、降噪、计算和聚合。主要功能是对农产品数据资源的维护管理、数据集成整合、统计聚合以及数据的共享。	云农场智慧服务大数据信息集成共享平台
3	数据分析应用与可视化	通过整合农产品的数据资源，满足生产经营主体对多个业务领域的数据管理分析功能需要，实现数据结果的可视化展现。建立大数据分析模型分析农产品全产业链经营情况变化，并深度挖掘数据资源的潜在价值，从而寻找农产品生产经营过程动态变化规律。	云农场智慧服务大数据综合服务平台
4	数据服务	满足农业数据资源分析结果的集中展示，提供对大别山区农产品全产业链生产经营情况的综合查询、智能预警、决策支持、产业链分析报告等智慧服务。	云农场智慧服务大数据综合服务平台

数据主题	数据内容	数据来源	数据处理
天	遥感图像、气象数据、地理位置数据等	与气象、遥感等信息网站接口获取	采集、清洗、分类、聚合、分析、存储等
地	传感器测量数据、视频监控数据、生长图像等	由传感器等物联网设备采集
人	农产品全产业链各环节生产经营数据、生态图像数据、文本解释数据等	人工采集、人工录入
网	网络端历史图像及文本数据等	应用客户端反馈、网络服务端存储

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[4]	Chunjiang Zhao. Big Data of Plant Phenomics and Its Research Progress [J]. Journal of Agricultural Big Data, 2019, 1(2): 5-14.

Design and Implementation of a Big Data Platform for Cloud Server Farm Smart Services

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