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Article Dans Une Revue Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Année : 2022

Sensor-free soil moisture sensing using lora signals

Résumé

Soil moisture sensing is one of the most important components in smart agriculture. It plays a critical role in increasing crop yields and reducing water waste. However, existing commercial soil moisture sensors are either expensive or inaccurate, limiting their real-world deployment. In this paper, we utilize wide-area LoRa signals to sense soil moisture without a need of dedicated soil moisture sensors. Different from traditional usage of LoRa in smart agriculture which is only for sensor data transmission, we leverage LoRa signal itself as a powerful sensing tool. The key insight is that the dielectric permittivity of soil which is closely related to soil moisture can be obtained from phase readings of LoRa signals. Therefore, antennas of a LoRa node can be placed in the soil to capture signal phase readings for soil moisture measurements. Though promising, it is non-trivial to extract accurate phase information due to unsynchronization of LoRa transmitter and receiver. In this work, we propose to include a low-cost switch to equip the LoRa node with two antennas to address the issue. We develop a delicate chirp ratio approach to cancel out the phase offset caused by transceiver unsynchronization to extract accurate phase information. The proposed system design has multiple unique advantages including high accuracy, robustness against motion interference and large sensing range for large-scale deployment in smart agriculture. Experiments with commodity LoRa nodes show that our system can accurately estimate soil moisture at an average error of 3.1%, achieving a performance comparable to high-end commodity soil moisture sensors. Field studies show that the proposed system can accurately sense soil moisture even when the LoRa gateway is 100 m away from the LoRa node, enabling wide-area soil moisture sensing for the first time. CCS Concepts: • Human-centered computing → Ubiquitous and mobile computing systems and tools.
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Dates et versions

hal-03959864 , version 1 (08-02-2024)

Identifiants

Citer

Zhaoxin Chang, Fusang Zhang, Jie Xiong, Junqi Ma, Beihong Jin, et al.. Sensor-free soil moisture sensing using lora signals. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2022, 6 (2), pp.1 - 27. ⟨10.1145/3534608⟩. ⟨hal-03959864⟩
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