English

中国农机化学报

中国农机化学报 ›› 2023, Vol. 44 ›› Issue (3): 149-155.DOI: 10.13733/j.jcam.issn.2095-5553.2023.03.021

• 农业信息化工程 • 上一篇    下一篇

基于SpringBoot框架的群养母猪饲喂站管理系统设计与试验

余鹏翔,石军锋   

  1. 西南大学工程技术学院,重庆市,400716
  • 出版日期:2023-03-15 发布日期:2023-03-22
  • 基金资助:
    重庆市重点产业共性关键技术创新专项重点研发项目(cstc2017zdcy—zdyfX0074)

Design and experiment of group sow feeding station management system based on Springboot framework

Yu Pengxiang, Shi Junfeng.   

  • Online:2023-03-15 Published:2023-03-22

摘要: 母猪的群体养殖是一种能保证动物福利,提高母猪生产性能的重要养殖管理模式。为实现母猪群养过程的数字化及智能化,基于自主研发的群养母猪饲喂站硬件平台,采用B/S模式设计一个群养母猪饲喂站管理系统。系统后端使用基于Java语言的SpringBoot框架作为系统组件管理和运行的主要框架;设计后端数据库中的数据结构,优化后台系统中持久层数据的操作访问;使用Netty实现饲喂站及客户端与后台间的实时通信;基于Spring事务管理,封装可复用的业务逻辑,设计母猪信息管理、饲喂计划专家系统、饲喂站实时监控等系统功能模块。系统前端采用渐进式Vue框架实现用户与各个功能模块的人机交互。试验表明:本系统能实现对群养母猪饲喂站的控制和状态监测,并根据母猪特性和专家知识库动态生成每天的饲喂计划;在基础实验条件下,系统的饲喂站并发量可超过120台,理论最大母猪容纳量超过5 400 头,能够满足大规模母猪饲喂的需求。

关键词: 母猪群体养殖, SpringBoot, Netty, 专家系统

Abstract: Group breeding of sows is an important breeding management modewhich can ensure animal welfare and improve sow production performance. In order to realize the digitalization and intelligence of the sow group breeding process, this paper designs a group breeding sow feeding station management system based on the selfdeveloped group breeding sow feeding station hardware platform with B/S mode. The backend of the system uses the SpringBoot framework based on Java language as the main framework for the management and operation of system components; the data structure in the backend database is designed to optimize the operation access of the persistent layer data in the backend system; Netty is used to realize the realtime communication between the feeding station and the client and the backend; based on Spring transaction management, the reusable business logic is encapsulated and sow information management, feeding plan expert system, feeding station realtime monitoring and other system function modules are designed. The frontend of the system adopts the progressive Vue framework to realize the humancomputer interaction between users and each functional module. Experiments show that the system can realize the control and status monitoring of group sow feeding stations, and dynamically generate daily feeding plans according to sow characteristics and expert knowledge base; under the basic experimental conditions, the concurrent capacity of feeding stations of the system can exceed 120 units, and the theoretical maximum sow capacity exceeds 5 400, which can meet the demand of largescale sow feeding.


Key words: sow group breeding, SpringBoot, Netty, expert system

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