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Aiming at the common problems of water waste and sloppy management in traditional sugarcane irrigation, this study develops an IoT intelligent irrigation system based on LoRa technology. The system adopts STM32L051C8T6 as the core processor and LoRa wireless communication module to build a distributed sensor network, and realizes data interaction with the cloud platform through 4G communication module to monitor the key environmental parameters of the sugarcane field in real time, including soil humidity, temperature and light intensity. The intelligent algorithm based on crop growth model is used to dynamically adjust the irrigation scheme based on real-time environmental data and historical trend analysis. Experimental results from field tests in three soil types (sandy loam, clay, and red soil, each covering 50 mu) demonstrate superior performance: the intelligent system reduces the mean squared error of soil moisture content to 3.31, which is 52% lower than that of 6.92 in the traditional way. The LoRa network achieves reliable long-distance communication, maintaining a 97.7% packet delivery rate at 5,000 m. effectively solving the problem of water waste in the traditional irrigation method, realizing the fine management of sugarcane cultivation, and providing a reliable technical solution for the development of intelligent agriculture.

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Research and Application of Intelligent Sugarcane Irrigation System of the Internet of Things Based on LoRa Technology

  • 会议论文

  • 发表日期：

    2026年

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  • Zeen Qiu,
  • Zhenghong Yin,
  • Shanshan Tu,
  • Peng Tang

摘要

Aiming at the common problems of water waste and sloppy management in traditional sugarcane irrigation, this study develops an IoT intelligent irrigation system based on LoRa technology. The system adopts STM32L051C8T6 as the core processor and LoRa wireless communication module to build a distributed sensor network, and realizes data interaction with the cloud platform through 4G communication module to monitor the key environmental parameters of the sugarcane field in real time, including soil humidity, temperature and light intensity. The intelligent algorithm based on crop growth model is used to dynamically adjust the irrigation scheme based on real-time environmental data and historical trend analysis. Experimental results from field tests in three soil types (sandy loam, clay, and red soil, each covering 50 mu) demonstrate superior performance: the intelligent system reduces the mean squared error of soil moisture content to 3.31, which is 52% lower than that of 6.92 in the traditional way. The LoRa network achieves reliable long-distance communication, maintaining a 97.7% packet delivery rate at 5,000 m. effectively solving the problem of water waste in the traditional irrigation method, realizing the fine management of sugarcane cultivation, and providing a reliable technical solution for the development of intelligent agriculture.