Research and Development of an IoT Smart Irrigation System for Farmland Based on LoRa and Edge Computing
In response to the current key issues in the field of smart irrigation for farmland, such as the lack of data sources and insufficient integration, a low degree of automation in drive execution and control, and over-reliance on cloud platforms for analyzing and calculating decision making processes,...
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MDPI AG
2025-01-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/15/2/366 |
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| author | Ying Zhang Xingchen Wang Liyong Jin Jun Ni Yan Zhu Weixing Cao Xiaoping Jiang |
| author_facet | Ying Zhang Xingchen Wang Liyong Jin Jun Ni Yan Zhu Weixing Cao Xiaoping Jiang |
| author_sort | Ying Zhang |
| collection | DOAJ |
| description | In response to the current key issues in the field of smart irrigation for farmland, such as the lack of data sources and insufficient integration, a low degree of automation in drive execution and control, and over-reliance on cloud platforms for analyzing and calculating decision making processes, we have developed nodes and gateways for smart irrigation. These developments are based on the EC-IOT edge computing IoT architecture and long range radio (LoRa) communication technology, utilizing STM32 MCU, WH-101-L low-power LoRa modules, 4G modules, high-precision GPS, and other devices. An edge computing analysis and decision model for smart irrigation in farmland has been established by collecting the soil moisture and real-time meteorological information in farmland in a distributed manner, as well as integrating crop growth period and soil properties of field plots. Additionally, a mobile mini-program has been developed using WeChat Developer Tools that interacts with the cloud via the message queuing telemetry transport (MQTT) protocol to realize data visualization on the mobile and web sides and remote precise irrigation control of solenoid valves. The results of the system wireless communication tests indicate that the LoRa-based sensor network has stable data transmission with a maximum communication distance of up to 4 km. At lower communication rates, the signal-to-noise ratio (SNR) and received signal strength indication (RSSI) values measured at long distances are relatively higher, indicating better communication signal quality, but they take longer to transmit. It takes 6 s to transmit 100 bytes at the lowest rate of 0.268 kbps to a distance of 4 km, whereas, at 10.937 kbps, it only takes 0.9 s. The results of field irrigation trials during the wheat grain filling stage have demonstrated that the irrigation amount determined based on the irrigation algorithm can maintain the soil moisture content after irrigation within the suitable range for wheat growth and above 90% of the upper limit of the suitable range, thereby achieving a satisfactory irrigation effect. Notably, the water content in the 40 cm soil layer has the strongest correlation with changes in crop evapotranspiration, and the highest temperature is the most critical factor influencing the water requirements of wheat during the grain-filling period in the test area. |
| format | Article |
| id | doaj-art-e714918d6a174884b1f10c396fadf407 |
| institution | DOAJ |
| issn | 2073-4395 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj-art-e714918d6a174884b1f10c396fadf4072025-08-20T03:11:06ZengMDPI AGAgronomy2073-43952025-01-0115236610.3390/agronomy15020366Research and Development of an IoT Smart Irrigation System for Farmland Based on LoRa and Edge ComputingYing Zhang0Xingchen Wang1Liyong Jin2Jun Ni3Yan Zhu4Weixing Cao5Xiaoping Jiang6College of Agriculture, Nanjing Agricultural University, Nanjing 210095, ChinaCollege of Agriculture, Nanjing Agricultural University, Nanjing 210095, ChinaJiangsu Rainfolks Irrigation System Co., Ltd., Nanjing 210011, ChinaCollege of Agriculture, Nanjing Agricultural University, Nanjing 210095, ChinaCollege of Agriculture, Nanjing Agricultural University, Nanjing 210095, ChinaCollege of Agriculture, Nanjing Agricultural University, Nanjing 210095, ChinaCollege of Agriculture, Nanjing Agricultural University, Nanjing 210095, ChinaIn response to the current key issues in the field of smart irrigation for farmland, such as the lack of data sources and insufficient integration, a low degree of automation in drive execution and control, and over-reliance on cloud platforms for analyzing and calculating decision making processes, we have developed nodes and gateways for smart irrigation. These developments are based on the EC-IOT edge computing IoT architecture and long range radio (LoRa) communication technology, utilizing STM32 MCU, WH-101-L low-power LoRa modules, 4G modules, high-precision GPS, and other devices. An edge computing analysis and decision model for smart irrigation in farmland has been established by collecting the soil moisture and real-time meteorological information in farmland in a distributed manner, as well as integrating crop growth period and soil properties of field plots. Additionally, a mobile mini-program has been developed using WeChat Developer Tools that interacts with the cloud via the message queuing telemetry transport (MQTT) protocol to realize data visualization on the mobile and web sides and remote precise irrigation control of solenoid valves. The results of the system wireless communication tests indicate that the LoRa-based sensor network has stable data transmission with a maximum communication distance of up to 4 km. At lower communication rates, the signal-to-noise ratio (SNR) and received signal strength indication (RSSI) values measured at long distances are relatively higher, indicating better communication signal quality, but they take longer to transmit. It takes 6 s to transmit 100 bytes at the lowest rate of 0.268 kbps to a distance of 4 km, whereas, at 10.937 kbps, it only takes 0.9 s. The results of field irrigation trials during the wheat grain filling stage have demonstrated that the irrigation amount determined based on the irrigation algorithm can maintain the soil moisture content after irrigation within the suitable range for wheat growth and above 90% of the upper limit of the suitable range, thereby achieving a satisfactory irrigation effect. Notably, the water content in the 40 cm soil layer has the strongest correlation with changes in crop evapotranspiration, and the highest temperature is the most critical factor influencing the water requirements of wheat during the grain-filling period in the test area.https://www.mdpi.com/2073-4395/15/2/366EC-IOTsensor networksirrigation modelwater saving |
| spellingShingle | Ying Zhang Xingchen Wang Liyong Jin Jun Ni Yan Zhu Weixing Cao Xiaoping Jiang Research and Development of an IoT Smart Irrigation System for Farmland Based on LoRa and Edge Computing Agronomy EC-IOT sensor networks irrigation model water saving |
| title | Research and Development of an IoT Smart Irrigation System for Farmland Based on LoRa and Edge Computing |
| title_full | Research and Development of an IoT Smart Irrigation System for Farmland Based on LoRa and Edge Computing |
| title_fullStr | Research and Development of an IoT Smart Irrigation System for Farmland Based on LoRa and Edge Computing |
| title_full_unstemmed | Research and Development of an IoT Smart Irrigation System for Farmland Based on LoRa and Edge Computing |
| title_short | Research and Development of an IoT Smart Irrigation System for Farmland Based on LoRa and Edge Computing |
| title_sort | research and development of an iot smart irrigation system for farmland based on lora and edge computing |
| topic | EC-IOT sensor networks irrigation model water saving |
| url | https://www.mdpi.com/2073-4395/15/2/366 |
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