Research on the Architecture and Key Technologies of Agricultural and Rural Data Fusion Service Platforms

  • HA XiaoLin ,
  • LI Jie ,
  • YUAN YuHui ,
  • ZHANG ZiYi ,
  • LIANG MinYan
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  • 1. Big Data Development Center, Ministry of Agriculture and Rural Affairs of People’s Republic of China, Beijing 100125, China
    2. Beijing Yihualu Information Technology Co., Ltd, University, 100043, China
    3. School of Social Sciences, Tsinghua University, Beijing 100083, China

Received date: 2025-08-22

  Revised date: 2025-10-09

  Online published: 2025-12-26

Abstract

With the advancement of the digital rural strategy, the agricultural and rural sectors are increasingly demanding data resource integration, business collaboration, and intelligent services. This paper proposes a design scheme for an agricultural and rural data fusion service platform based on Hadoop, emphasizing the aggregation and service needs of agricultural and rural data resources. It indicatively constructs a hybrid deployment platform model that combines "cloud-edge-end" with centralized management areas and its key technical solutions. The platform relies on advanced privacy protection and data security technologies, such as "blockchain + privacy computation," to build the technical foundation that supports the value realization of agricultural and rural data elements. It provides management capabilities and integrated services throughout the entire life cycle of data collection, governance, fusion, and application, targeting the value-added needs of agricultural and rural data elements. The platform has aggregated over 30 categories of agricultural and rural data, totaling approximately 500GB, covering multiple dimensions such as production, management, and services. Research has been conducted around the platform architecture, deployment architecture, key technologies, and application scenarios to build a data fusion service platform for agricultural and rural modernization. This explores solutions to challenges such as clear ownership of agricultural data, unambiguous value recognition, and trustworthy transaction processes. Leveraging the big data technology system, it promotes the circulation and sharing of agricultural data elements, deep value mining, and efficient asset transformation. In typical query scenarios, the platform achieves a performance of average response latency below 100 milliseconds for multi-dimensional data retrieval. The platform significantly enhances data security and full-chain traceability during the transaction process, effectively addressing the deficiencies in performance, capacity, and multi-purpose support of massive agricultural and rural data. It also provides a standardized paradigm for cross-departmental government collaboration and data sharing, accelerates the cultivation of the agricultural and rural data element market, and empowers the high-quality development of the rural digital economy.

Cite this article

HA XiaoLin , LI Jie , YUAN YuHui , ZHANG ZiYi , LIANG MinYan . Research on the Architecture and Key Technologies of Agricultural and Rural Data Fusion Service Platforms[J]. Journal of Agricultural Big Data, 2025 , 7(4) : 468 -484 . DOI: 10.19788/j.issn.2096-6369.000130

References

[1] 王小兵, 刘洋, 梁栋, 等. 强力推进智慧农业建设加快形成农业新质生产力. 农业大数据学报, 2024, 6 (4): 469-475.
  WANG X B, LIU Y, LIANG D, et al. Vigorously Promoting the Construction of Smart Agriculture to Accelerate the Formation of New Quality Agricultural Productivity. Journal of Agricultural Big Data, 2024, 6(4): 469-475.
[2] 王庆福. 算力驱动下的智慧农业技术升级与发展模式创新. 农业经济, 2025 (6): 7-9.
  WANG Q F. Innovation in technology upgrade and development model of smart agriculture driven by computing power. Agricultural Economy, 2025 (6): 7-9.
[3] 孔繁涛, 赵仁杰, 张鑫蕊, 等. 推动现代农业转型:智慧农业发展的思考与展望. 农业大数据学报, 2025, 7(2):155-160.
  KONG F T, ZHAO R J, ZHANG X R, et al. Promoting the transformation of modern agriculture: Reflections and prospects on the development of smart agriculture. Journal of Agricultural Big Data, 2025, 7(2): 155-160.
[4] 薛鹏珍, 贾君枝, 索传军, 等. 面向公共数据资源登记流程的标准体系建设研究. 图书情报工作, 2025, 69(16):29-39.
  XUE P Z, JIA J Z, SUO C J, et al. Research on the standard system construction for public data resource registration process. Library and Information Service, 2025, 69(16): 29-39.
[5] 贾君枝, 薛鹏珍, 索传军. 数据资产元数据标准体系整合应用研究. 图书情报工作, 2025, 69(16):40-47.
  JIA J Z, XUE P Z, SUO C J. Research on the integration and application of data asset metadata standard system. Library and Information Service, 2025, 69(16): 40-47.
[6] 赵子晨, 杨锋, 郭玉辉, 等. 基于Hadoop技术的加速器大数据安全存储与高效分析系统设计. 现代电子技术, 2024, 47(8):9-17.
  ZHAO Z C, YANG F, GUO Y H, et al. Design of accelerator big data security storage and efficient analysis system based on Hadoop technology. Modern Electronics Technique, 2024, 47(8): 9-17.
[7] 黄先海, 黄雨晗, 虞柳明. 人工智能赋能农业新质生产力:实现逻辑、运行机制与跃升路径. 中国农村经济, 2025(7):3-22.
  HUANG X H, HUANG Y H, YU L M. Artificial intelligence empowers new quality agricultural productivity: Implementation logic, operation mechanism, and leapfrog path. Chinese Rural Economy, 2025 (7): 3-22.
[8] 王枭婷. “互联网+”背景下的农产品销售大数据平台的构建和应用. 中国农业资源与区划, 2023, 44(10):39+51.
  WANG X T. Construction and application of big data platform for agricultural product sales under the background of "Internet+". Chinese Journal of Agricultural Resources and Regional Planning, 2023, 44(10): 39+51.
[9] 张洪奇, 张艳, 张晨, 等. 设施智慧农场大数据平台开发与应用. 山东农业大学学报(自然科学版), 2024, 55(3):295-303+475.
  ZHANG H Q, ZHANG Y, ZHANG C, et al. Development and application of big data platform for facility smart farm. Journal of Shandong Agricultural University (Natural Science Edition), 2024, 55(3): 295-303+475.
[10] 钱小龙, 葛黄雅, 黄蓓蓓. 基于云平台的高校数据安全治理体系构建与应用研究. 科技管理研究, 2024, 44(17):122-128.
  QIAN X L, GE H Y, HUANG B B. Research on the construction and application of university data security governance system based on Cloud platform. Science and Technology Management Research, 2024, 44(17): 122-128.
[11] 单珂, 孔祥龙, 张一鸣, 等. 基于Hadoop的区域健康大数据平台研究与设计. 计算机应用与软件, 2025, 42(4):8-12.
  SHAN K, KONG X L, ZHANG Y M, et al. Research and design of regional health big data platform based on Hadoop. Computer Applications and Software, 2025, 42(4): 8-12.
[12] 文佳, 吴舒霞, 于正欣, 等. 基于多目标优化的大规模Hadoop集群虚拟机放置[J/OL]. 计算机科学,1-13[2025-09-04]. https://link.cnki.net/urlid/50.1075.TP.20250401.1426.004.
  WEN J, WU S X, YU Z X, et al. Multi-objective optimization based virtual machine placement in large-scale Hadoop clusters[J/OL]. Computer Science, 1-13[2025-09-04]. https://link.cnki.net/urlid/50.1075.TP.20250401.1426.004.
[13] 郭致远, 李健, 汪薇, 等. 城市更新大数据平台研究及应用, 清华大学学报(自然科学版), 2025, 65 (1): 2-34.
  GUO Z Y, LI J, WANG W, et al. Research and application of big data platform for urban renewal. Journal of Tsinghua University (Science and Technology), 2025, 65(1): 2-34.
[14] 张璐. 农机数字化大数据管理平台的设计——基于电子商务平台重复客户预测模型. 农机化研究, 2025, 47(4):127-131.
  ZHANG L. Design of Agricultural Machinery Digital Big Data Management Platform: Based on e-commerce platform repeat customer prediction model. Journal of Agricultural Mechanization Research, 2025, 47(4): 127-131.
[15] 易兰丽, 赵丽丽, 魏娜. 机理与路径:区块链技术如何赋能政务服务“跨省通办”?. 电子政务, 2025(2): 45-56.
  YI L L, ZHAO L L, WEI N. Mechanism and path: How does Blockchain technology empower cross-provincial handling of government services?. E-Government, 2025(2): 45-56.
[16] 敦帅, 柳恒超. 可信数据空间建设:制度、技术与治理[J/OL]. 科学学研究, 1-11[2025-08-18]. https://doi.org/10.16192/j.cnki.1003-2053.20250527.001.
  DUN S, LIU H. Construction of Trusted Data Space: Institution, Technology and Governance[J/OL]. Studies in Science of Science, 1-11[2025-08-18]. https://doi.org/10.16192/j.cnki.1003-2053.20250527.001.
[17] 刘涛雄, 尹德才. 大数据在农业经济问题研究中的应用展望. 农业经济问题, 2024 (8): 4-12.
  LIU T X, YIN D C. Application prospects of big data in agricultural economic research. Issues in Agricultural Economy, 2024 (8): 4-12.
[18] 张旭艺, 孙晓, 杨鹏, 等. 农业数字孪生概念内涵、技术框架与应用进展[J/OL]. 中国农业资源与区划, 1-14[2025-08-18]. https://link.cnki.net/urlid/11.3513.S.20250217.1153.004.
  ZHANG X Y, SUN X, YANG P, et al. Agricultural digital twin: conceptual connotation, technical framework and application progress[J/OL]. Chinese Journal of Agricultural Resources and Regional Planning, 1-14[2025-08-18]. https://link.cnki.net/urlid/11.3513.S.20250217.1153.004.
[19] 李沐纯, 毛明晨. 区块链赋能智慧农业发展的研究热点、演进势态和未来展望. 江苏农业科学, 2025, 53 (5): 1-12. DOI:10.15889/j.issn.1002-1302.2025.05.001.
  LI M C, MAO M C. Research hotspots, evolution trends and future prospects of Blockchain empowering smart agriculture development. Jiangsu Agricultural Sciences, 2025, 53(5): 1-12. DOI:10.15889/j.issn.1002-1302.2025.05.001.
[20] 汤敏睿, 何亮, 顾生浩, 等. 联邦学习在智慧农业系统中的应用研究综述. 中国农业科技导报(中英文), 2025, 27 (6): 1-15. DOI:10.13304/j.nykjdb.2024.0002.
  TANG M R, HE L, GU S H, et al. A review on the application of federated learning in smart agriculture systems. Journal of Agricultural Science and Technology, 2025, 27(6): 1-15. DOI:10.13304/j.nykjdb.2024.0002.
[21] 雷浩然. 生成式人工智能赋能数字乡村治理:理论阐释与实现机制. 西北民族大学学报(哲学社会科学版), 2024 (6): 81-90.
  LEI H R. Artificial intelligence empowers digital rural governance: Theoretical interpretation and implementation mechanism. Journal of Northwest Minzu University (Philosophy and Social Sciences), 2024 (6): 81-90.
[22] 吴政娴, 文娟. 农业大数据与隐私计算技术研究综述[J/OL]. 农业机械学报, 1-23[2025-08-18]. https://link.cnki.net/urlid/11.1964.s.20250724.1822.002.
  WU Z X, WEN J. A review of agricultural big data and privacy computing technologies[J/OL]. Transactions of the Chinese Society for Agricultural Machinery, 1-23[2025-08-18]. https://link.cnki.net/urlid/11.1964.s.20250724.1822.002.
[23] 马亮亮, 贾国强, 雷骁勇. 辽宁省数字农业全链条服务管理对策研究. 农业经济, 2023 (11): 28-31.
  MA L L, JIA G Q, LEI X Y. Research on countermeasures for whole-chain service management of digital agriculture in Liaoning Province. Agricultural Economy, 2023 (11): 28-31.
[24] 王小兵, 唐文凤, 梁栋, 等. 数据要素驱动农业高质量发展的管理机制研究. 中国农业资源与区划, 2024, 45 (10): 59-64.
  WANG X B, TANG W F, LIANG D, et al. Research on the management mechanism of data factor driving high-quality agricultural development. Chinese Journal of Agricultural Resources and Regional Planning, 2024, 45(10): 59-64.
[25] 李佳乐, 林佳, 贺子康, 等. 农业科学数据在线分析挖掘平台设计与应用. 农业大数据学报, 2025, 7(2):183-192.
  LI J L, LIN J, HE Z K, et al. Design and application of an online analysis and mining platform for agricultural scientific data. Journal of Agricultural Big Data, 2025, 7(2): 183-192.
[26] 王嵩立, 荆一楠, 何震瀛, 等. 支持混合事务和分析处理的数据库管理系统综述. 软件学报, 2024, 35(1):405-429.
  WANG S L, JING Y N, HE Z Y, et al. A survey of database management systems supporting hybrid transactional and analytical processing. Journal of Software, 2024, 35(1): 405-429.
[27] 赵一帆, 张嘉伟, 杨颜博, 等. 云边端环境中的分布式数据双边访问控制方案[J/OL]. 西安电子科技大学学报, 1-16[2025-09-04]. https://doi.org/10.19665/j.issn1001-2400.20250201.
  ZHAO Y F, ZHANG J W, YANG Y B, et al. A distributed data bilateral access control scheme in cloud-edge-end environments[J/OL]. Journal of Xidian University, 1-16[2025-09-04]. https://doi.org/10.19665/j.issn1001-2400.20250201.
[28] 白宏宇, 汪成军, 王榆楗, 等. 基于多源异构数据融合的电网调度防误大数据仓库构建方法. 半导体光电, 2025, 46 (4): 750-756.
  BAI H Y, WANG C J, WANG Y J, et al. Construction method of anti-error big data warehouse for power grid dispatch based on multi-source heterogeneous data fusio. Semiconductor Optoelectronics, 2025, 46(4): 750-756.
[29] 彭成. 基于地质信息编码的地震数据分布式存储. 计算机应用与软件, 2025, 42 (8): 55-62.
  PENG C. Distributed storage of seismic data based on geological information coding. Computer Applications and Software, 2025, 42(8): 55-62.
[30] 乔鼎, 陈靓, 梁久祯. 键值对与对象存储在分布式存储系统中的应用. 计算机工程与设计, 2023, 44(6):1914-1920.
  QIAO D, CHEN L, LIANG J Z. Application of key-value pair and object storage in distributed storage systems. Computer Engineering and Design, 2023, 44(6): 1914-1920.
[31] 高扬, 张琪, 王琛, 等. 新型可组合的认证分布式数据结构模型研究. 信息网络安全, 2025, 25 (7): 1111-1125.
  GAO Y, ZHANG Q, WANG C, et al. Research on a novel composable authenticated distributed data structure model. Netinfo Security, 2025, 25(7): 1111-1125.
[32] 艾志成, 曹炳尧, 王演祎. 基于哈希增强技术的分布式系统数据分片技术[J/OL]. 计算机应用研究, 1-7[2025-09-04]. https://doi.org/10.19734/j.issn.1001-3695.2025.01.0018.
  AI Z C, CAO B Y, WANG Y Y. Data sharding technology in distributed systems based on hash enhancement technology[J/OL]. Application Research of Computers, 1-7[2025-09-04]. https://doi.org/10.19734/j.issn.1001-3695.2025.01.0018.
[33] 陈滨林, 唐小勇. 基于动态时间窗格的数据仓库流批一体优化方法. 计算机应用研究, 2025, 42 (8): 2460-2466.
  CHEN B L, TANG X Y. A stream-batch integrated optimization method for data warehouse based on dynamic time panes. Application Research of Computers, 2025, 42(8): 2460-2466.
[34] 熊京京. 基于嵌入式终端的智慧农业系统应用研究. 中国农业资源与区划, 2024, 45 (8): 265-266.
  XIONG J J. Application research of smart agriculture system based on embedded terminal. Chinese Journal of Agricultural Resources and Regional Planning, 2024, 45(8): 265-266.
[35] 李远征, 龙信鑫, 周纯杰, 等. 高比例新能源电网-分布式数据中心集群协同优化运行研究. 中国科学:技术科学, 2024, 54 (1): 119-135.
  LI Y Z, LONG X X, ZHOU C J, et al. Research on cooperative optimal operation of high-penetration renewable energy grid and distributed data center clusters. Scientia Sinica Technologica, 2024, 54(1): 119-135.
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