Sensor-free Soil Moisture Sensing Using LoRa Signals

Author:

Chang Zhaoxin1,Zhang Fusang2,Xiong Jie3,Ma Junqi4,Jin Beihong5,Zhang Daqing6

Affiliation:

1. Telecom SudParis, Institut Polytechnique de Paris, Evry, France; Institute of Software, Chinese Academy of Sciences, Beijing, China

2. State Key Laboratory of Computer Sciences, Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China; State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China

3. College of Information and Computer Sciences, University of Massachusetts Amherst, United States

4. Beijing University of Posts and Telecommunications; Institute of Software, Chinese Academy of Sciences, Beijing, China

5. State Key Laboratory of Computer Sciences, Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China

6. Telecom SudParis, Institut Polytechnique de Paris, Evry, France; School of Computer Science, Peking University, Beijing, China

Abstract

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.

Funder

Youth Innovation Promotion Association, Chinese Academy of Sciences

National Key Research and Development Plan

National Natural Science Foundation of China A3 Foresight Program

EU CHIST-ERA RadioSense Project

EU Horizon 2020 research and innovation programme IDEA-FAST

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

Reference76 articles.

1. 1993. Water Resource Issues and Agriculture. https://www.fao.org/3/t0800e/t0800e0a.htm 1993. Water Resource Issues and Agriculture. https://www.fao.org/3/t0800e/t0800e0a.htm

2. 2013. Practical Use of Soil Moisture Sensors and Their Data for Irrigation Scheduling. http://irrigation.wsu.edu/Content/Fact-Sheets/FS083E.pdf 2013. Practical Use of Soil Moisture Sensors and Their Data for Irrigation Scheduling. http://irrigation.wsu.edu/Content/Fact-Sheets/FS083E.pdf

3. 2017. Review of latest developments in the Internet of Things. https://www.ofcom.org.uk/__data/assets/pdf_file/0007/102004/Review-of-latest-developments-in-the-Internet-of-Things.pdf 2017. Review of latest developments in the Internet of Things. https://www.ofcom.org.uk/__data/assets/pdf_file/0007/102004/Review-of-latest-developments-in-the-Internet-of-Things.pdf

4. 2018. MQTTSN-over-LoRA. https://github.com/bngesp/MQTTSN-over-LoRA/tree/adcf780d5e85f0cb6e030cc0d1f97795b8bb7a10/SX1276 2018. MQTTSN-over-LoRA. https://github.com/bngesp/MQTTSN-over-LoRA/tree/adcf780d5e85f0cb6e030cc0d1f97795b8bb7a10/SX1276

5. 2018. Semtech Senet and Sensoterra's Proven IoT Solution for Farmers. https://www.semtech.com/company/press/semtech-senet-and-sensoterras-proven-iot-solution-offers-farmers- scale-and-operational-visibility 2018. Semtech Senet and Sensoterra's Proven IoT Solution for Farmers. https://www.semtech.com/company/press/semtech-senet-and-sensoterras-proven-iot-solution-offers-farmers- scale-and-operational-visibility

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