湖北农业科学 ›› 2022, Vol. 61 ›› Issue (14): 165-170.doi: 10.14088/j.cnki.issn0439-8114.2022.14.030

• 信息工程 • 上一篇    下一篇

基于NB-IoT的农田环境监测系统设计与实现

雷娟   

  1. 杨凌职业技术学院信息工程学院,陕西 杨凌 712100
  • 收稿日期:2021-08-13 出版日期:2022-07-25 发布日期:2022-08-25
  • 作者简介:雷娟(1983-),女,陕西合阳人,讲师,硕士,主要从事模式识别与智能系统研究,(电话)15209182509(电子信箱)leijuan226@163.com。
  • 基金资助:
    杨凌职业技术学院院内自然科学基金项目(ZK21-51)

Design and implementation of farmland environment monitoring system based on NB-IoT

LEI Juan   

  1. College of Information Engineering, Yangling Vocational & Technical College, Yangling 712100, Shaanxi, China
  • Received:2021-08-13 Online:2022-07-25 Published:2022-08-25

摘要: 农田环境信息是制定农田管理策略的重要依据,为了实时稳定地采集农田环境信息,结合窄带物联网(Narrow Band Internet of Things,NB-IoT)的优势,设计并开发了基于NB-IoT的农田环境信息远程监测系统。该系统利用STM32F103RCT6单片机和传感器终端实时采集温度、湿度、光照强度、二氧化碳浓度、土壤湿度等农田环境数据,并通过NB-IoT 网络将采集的数据传输至基于OneNET平台的农田环境监测云平台,用户可通过农田环境监测App或PC端访问农田环境监测云平台以获取农田环境监测数据。系统测试结果表明,该系统可实时获取温度、湿度、光照度、二氧化碳浓度、土壤湿度等农田环境信息,温度控制精度保持在±0.2 ℃,相对误差为0.57%;湿度控制精度保持在±2% RH,相对误差为1.66%;光照度控制精度保持在±63 lx,相对误差为0.24%;二氧化碳浓度控制精度保持在±45.46 μmol/L,相对误差为0.34%;土壤湿度控制精度保持在±2%,相对误差为1.44%。该系统运行稳定,数据传输实时、准确,功能实用,操作简单,可大规模部署,为农业监控和物联网应用研究提供有效参考。

关键词: NB-IoT, 农田, 远程监测, 环境监测

Abstract: Farmland environmental information is an important basis for formulating farmland management strategies. In order to collect farmland environmental information in real time and stably, this paper designed and developed a remote monitoring system for farmland environmental information based on NB-IoT combining the advantages of NB-IoT. The system used STM32F103RCT6 MCU and sensor terminal to collect real-time farmland environmental data such as temperature, humidity, light intensity, carbon dioxide concentration, soil humidity, etc., and transmitited the collected data to the OneNET platform-based farmland environmental monitoring cloud platform through NB IoT network. Users can access the farmland environmental monitoring cloud platform through the farmland environmental monitoring App or PC to obtain the farmland environmental monitoring data. The system test results showed that the system could obtain real-time farmland environment information, such as temperature, humidity, light intensity, carbon dioxide concentration, soil humidity, etc. The temperature control accuracy was kept at a high level of ±0.2 ℃, and the relative error was 0.57%. The humidity control accuracy was kept at ±2% RH, and the relative error was 1.66%. The accuracy of light intensity control was kept at ±63 lx, and the relative error was 0.24%. The control accuracy of carbon dioxide concentration was kept at ±45.46 μmol/L, and the relative error was 0.34%. The accuracy of soil moisture control was kept at ±2%, and the relative error was 1.44%. The system has stable operation, real-time and accurate data transmission, practical function, and simple operation, and can be deployed on a large scale, which provides an effective reference for agricultural monitoring and internet of things application research.

Key words: NB-IoT, farmland, remote monitoring, environmental monitoring

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