湖北农业科学 ›› 2024, Vol. 63 ›› Issue (8): 171-175.doi: 10.14088/j.cnki.issn0439-8114.2024.08.029

• 系统与平台 • 上一篇    下一篇

基于多传感器的可视化智慧农业数据管理系统设计

万青松1, 罗晓姣2   

  1. 1.成都文理学院,成都 610499;
    2.四川锦兴国试书业有限公司,成都 610041
  • 收稿日期:2022-08-01 出版日期:2024-08-25 发布日期:2024-09-05
  • 作者简介:万青松(1981-),男,四川广汉人,助理研究员,硕士,主要从事农业管理、新媒体运营管理、乡村振兴研究,(电话)17398888847(电子信箱)wqs963111@126.com;罗晓姣(1988-),女,四川资阳人,主要从事风景园林、休闲农业研究,(电子信箱)wanqs0209@163.com。

Design of visualization smart agricultural data management system based on multi-sensor

WAN Qing-song1, LUO Xiao-jiao2   

  1. 1. Chengdu College of Arts and Sciences, Chengdu 610499, China;
    2. Sichuan Jinxing Guoshi Book Industry Co., Ltd., Chengdu 610041, China
  • Received:2022-08-01 Published:2024-08-25 Online:2024-09-05

摘要: 基于WSNs、MQTT的协议系统农业数据采集结果精准,但受到快速膨胀数据的影响,导致数据管理效果不佳,针对该问题,提出了基于Spring Boot的可视化智慧农业数据管理系统设计。从表现层、业务逻辑层和数据层3个层次上实现Spring Boot微服务,通过使用空气温湿度传感器、光照强度传感器、土壤湿度传感器能够传输空气温湿度、光照强度和土壤湿度数据;在Spring Boot微服务模式下处理并访问数据,避免数据过度膨胀;计算两个传感器间的观测距离,融合环境参数,完成智慧农业数据管理系统设计。由试验结果可知,该系统能够精准采集空气温度、空气湿度、土壤湿度、光照强度数据,且数据可视化方面性能良好,说明使用该系统具有良好的数据管理效果。

关键词: Spring Boot, 多传感器, 可视化, 智慧农业, 数据管理, 系统设计

Abstract: The protocol system based on WSNs and MQTT had accurate agricultural data collection results, but it was affected by rapid expansion data, resulting in poor data management effect. Aiming at this problem, a visual smart agricultural data management system based on Spring Boot was proposed. The Spring Boot micro service was implemented from three levels of presentation layer, business logic layer and data layer. The air temperature and humidity, light intensity and soil moisture data could be transmitted by using sensors of air temperature and humidity, light intensity and soil moisture. Processing and accessing data in Spring Boot micro service mode could avoid excessive data inflation. The observation distance between the two sensors was calculated, and the environmental parameters were fused to complete the design of a smart agricultural data management system. The experimental results showed that the system could accurately collect data of air temperature, air humidity, soil moisture and light intensity. The data visualization performance was good, indicating that the use of the system had good data management effects.

Key words: Spring Boot, multi-sensor, visualization, smart agriculture, data management, system design

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