农业大数据学报 ›› 2021, Vol. 3 ›› Issue (4): 10-19.doi: 10.19788/j.issn.2096-6369.210402

• 应用研究 • 上一篇    下一篇

云农场智慧服务大数据平台设计与实现

凌诺娟1,2(), 饶元1,2()   

  1. 1.安徽农业大学 信息与计算机学院,合肥 230036
    2.智慧农业技术与装备安徽省重点实验室,合肥 230036
  • 收稿日期:2021-06-20 出版日期:2021-12-26 发布日期:2022-01-28
  • 通讯作者: 饶元 E-mail:1807147837@qq.com;raoyuan@ahau.edu.cn
  • 作者简介:凌诺娟,女,硕士,研究方向:农业物联网、农业信息学;E-mail:1807147837@qq.com
  • 基金资助:
    安徽省自然科学基金(2008085MF203);安徽省重点研究和开发计划面上攻关项目(201904a06020056)

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

Nuojuan Ling1,2(), Yuan Rao1,2()   

  1. 1.College of Information and Computer Science, Anhui Agricultural University, Hefei 230036, China
    2.Anhui Provincial Key Laboratory of Smart Agricultural Technology and Equipment, Hefei 230036, China
  • Received:2021-06-20 Online:2021-12-26 Published:2022-01-28
  • Contact: Yuan Rao E-mail:1807147837@qq.com;raoyuan@ahau.edu.cn

摘要:

随着现代信息技术在农业领域的广泛应用,海量农业数据得以收集、分析用于促进农业现代化发展。本文以大别山区连片特色农产品生产经营全产业链为研究背景,在系统分析该区域农产品生产加工销售等各产业链环节数据特征、有机整合农产品生产经营数据资源等需求的基础上,采用包含基础设施层、数据资源层、数据处理分析层、数据显示层等四层大数据平台总体架构的设计模式,搭建了基于Hadoop大数据技术的农产品全产业链数据资源库与大别山区云农场智慧服务大数据平台,面向产业区相关农业从业人员所需业务主题进行平台功能的开发,对农业数据资源库中数据实施数据清洗、数据挖掘、数据建模等技术处理,寻找农产品生产经营过程动态变化规律,实现了信息共享、智能预警与辅助决策等智慧服务功能。其中,信息共享功能用于提供大数据平台各子系统平台数据资源共享服务;智能预警功能用于提供农产品全产业链生产经营过程中农产品生产环境、价格等关键指标信息的预警服务;辅助决策功能用于提供农业从业者产业区农产品生产经营情况变化通知,辅助经营过程决策服务等。研发的云农场智慧服务大数据信息管理中心和数据可视化系统,可为促进大别山区特色农产品全产业链信息化与智能化水平提供参考。

关键词: 云农场, Hadoop, 智慧服务, 大数据平台

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

中图分类号: 

  • TP311.1