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This invention discloses a soil volumetric water content (VWC) measurement system based on LoRa-RSSI and a drone. The system comprises several underground LoRa nodes for collecting environmental monitoring data; a host computer embedded in the soil; and an aerial node carried by a small drone. Combining IoUT technology, this invention designs an innovative system for soil VWC measurement based on LoRa received signal strength and a drone. The system utilizes the changes in LoRa-RSSI between the soil's internal transmitter and the drone's aerial receiver during the drone's angular rotation. Combined with a Long Short-Term Memory (LSTM) network, it collects differential LoRa-RSSI values ​​and uses a deep learning (DL) algorithm to calculate soil VWC, achieving relatively accurate soil VWC data. This invention eliminates the need for depth measurement of VWC data, utilizes soft sensors to measure soil VWC, and offers low cost, high efficiency, and small measurement error, providing a novel approach for soil VWC measurement design.