Author
Listed:
- Fuqiang Li
(College of Sciences, Henan Agricultural University, Zhengzhou 450002, China)
- Zhe Li
(College of Sciences, Henan Agricultural University, Zhengzhou 450002, China)
- Lisai Gao
(College of Sciences, Henan Agricultural University, Zhengzhou 450002, China)
- Chen Peng
(School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China)
Abstract
To enable remote and automatic monitoring of the farmland soil information, this paper has developed a soil monitoring system based on the Internet of Things (IoT), which mainly involves the development of a gateway server node, wireless sensor nodes, a remote monitoring platform, and photovoltaic (PV) modules. The Raspberry Pi 5-based gateway server periodically sends data acquisition commands to wireless sensor nodes via LoRa, receives soil data returned by sensor nodes, and stores them in a MySQL database. Using a remote monitoring platform, Internet users can monitor real-time and historical soil data stored in the database. The STM32F103C8T6-based wireless sensor node receives data acquisition commands from the gateway server, uses soil temperature and humidity sensors as well as a pH sensor to collect soil status, and then sends sensor data back to the gateway server via LoRa. The system is powered by both PV energy and batteries, which enhances the endurance capability. Experimental results show that the designed system works well in remotely monitoring soil information. Using the proposed query attempt dynamic adjustment (QADA) method, the wireless sensor node dynamically adjusts the number of query attempts, which reduces the data acquisition failure rate from 21–25% to no more than 0.33%. Using the obtained qualitative relationship that the data acquisition delay varies inversely with the LoRa transfer rate, the data acquisition delay can be reduced to less than 67 ms.
Suggested Citation
Fuqiang Li & Zhe Li & Lisai Gao & Chen Peng, 2025.
"Design of an Improved IoT-Based PV-Powered Soil Remote Monitoring System with Low Data Acquisition Failure Rate,"
Future Internet, MDPI, vol. 17(12), pages 1-20, November.
Handle:
RePEc:gam:jftint:v:17:y:2025:i:12:p:538-:d:1802480
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