南京林业大学学报(自然科学版) ›› 2025, Vol. 49 ›› Issue (2): 161-168.doi: 10.12302/j.issn.1000-2006.202304039

• 研究论文 • 上一篇    下一篇

基于LoRa组网的超低功耗径流含沙量检测系统

杨鹏城1(), 刘砚一1,*(), 陈书畅1, 沈奕聪1, 宋晨悦2   

  1. 1.南京林业大学信息科学技术学院,江苏 南京 210037
    2.南京林业大学林草学院、水土保持学院,江苏 南京 210037
  • 收稿日期:2023-04-28 接受日期:2023-09-03 出版日期:2025-03-30 发布日期:2025-03-28
  • 通讯作者: *刘砚一(yyliu@njfu.edu.cn),高级实验师。
  • 作者简介:

    杨鹏城(1223035252@qq.com)。

  • 基金资助:
    中国高校产学研创新基金项目(2020HYA02012);南京林业大学大学生创新训练计划项目(202210298118Y)

An ultra-low-power sediment concentration detecting system in runoff based on LoRa networking

YANG Pengcheng1(), LIU Yanyi1,*(), CHEN Shuchang1, SHEN Yicong1, SONG Chenyue2   

  1. 1. College of Information Science and Technology,Nanjing Forestry University,Nanjing 210037,China
    2. College of Forestry and Grassland,College of Soil and Water Conservation,Nanjing Forestry University,Nanjing 210037,China
  • Received:2023-04-28 Accepted:2023-09-03 Online:2025-03-30 Published:2025-03-28

摘要:

【目的】我国水土流失现象严重,通过对水土流失状况进行有效、可靠的检测,为研究人员提供可靠的数据依据,助力水土流失和水土保持效益定量评价,更好地掌握水土流失情况和治理效果。【方法】基于物联网架构,设计了一套基于远距离无线电(long range radio, LoRa)组网的坡面土壤侵蚀动态检测系统,该系统采用LoRa Standby-CAD工作策略实现超低功耗。【结果】与传统技术相比,本研究设计的径流含沙量检测系统可降低40%电耗,待机时长可提高8.5倍;基于ECharts框架和华为云平台设计可视化大屏,实现检测数据可视化。实地测试结果表明,与传统比重法相比,本系统检测数据相对误差均值为3.08%。【结论】本研究设计的径流含沙量检测系统能持续地实时检测野外坡面径流小区径流含沙量及降水量,相比传统物联网技术方案,该系统功耗低、测试精度高、数据可视化、投产建设及维护成本低,可为相关生产、研究工作提供真实有效的实测数据及解决方案。

关键词: 含沙量检测, 超低功耗, LoRa, 径流

Abstract:

【Objective】Soil erosion represents a critical issue in China. It is necessary to quantitatively evaluate soil erosion and the benefits of soil conservation, and to understand the situation of soil erosion and the effectiveness of treatment measures. This study involves effectively and reliably detecting the soil erosion status and providing a dependable data foundation for researchers. 【Method】The study used an internet of things (IoT) architecture to design an ultra-low-power sediment concentration detection system in runoff based on long range radio (LoRa) networking. The Standby-CAD with LoRa was employed to achieve ultra-low power consumption. 【Result】This system reduced energy consumption by 40% and increased standby time by 8.5 times compared to traditional techniques. The ECharts framework and Huawei cloud platform were utilized to design a visualization screen for data visualization. Through multiple tests, the average value of the relative error of data measured by this system was 3.08% compared to the traditional gravity method. 【Conclusion】This system can continuously detect the runoff sediment concentration and also rainfall in runoff plots on hillsides in real-time. Compared to traditional IoT technical solutions, this system demonstrates low power consumption, high testing accuracy, data visualization, and also reduced production and maintenance costs, providing accurate and effective measurement data and solutions for related production and research activities.

Key words: sediment concentration detection, ultra-low power consumption, long rang radio (LoRa), runofff

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