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A high-sensitivity multilayer soil moisture monitoring sensor based on a double high-frequency tuning detection circuit

Author

Listed:
  • Shi Qinglan
  • Shi Yujiao
  • Liu Xiaochen
  • Mei Shuli
  • Feng Lei

Abstract

The multilayer soil moisture Internet of things sensor is designed to monitor the moisture of multiple soil profiles in real time. Its sensitivity and accuracy are of great concern to improve the performance of sensors. This article introduces the system composition of the end-cloud integrated multilayer soil moisture Internet of things sensor and then focuses on the design of key technologies, such as the moisture detection circuit, the time division multiplexing detection technology, and the deredundancy circuit in the analog–digital integrated design. The performance of the soil moisture detection circuit is directly related to the measurement accuracy of the sensor. A detection method is proposed using a high-frequency double-resonance circuit, which can detect small changes in moisture by changing the circuit detuning voltage. The maximum root mean square error of the calibration is less than 1.35% for five typical soils from different places. Compared with that of an independent detection method, the output consistency of the time division multiplexing detection is significantly improved by using the time division multiplexing detection method, which has a root mean square error of only 0.12%. In order to reduce errors caused by inconsistency in each burial, the gravimetric analysis is used in the sensitivity monitoring test, which shows that small changes in soil moisture can be detected by the circuit.

Suggested Citation

  • Shi Qinglan & Shi Yujiao & Liu Xiaochen & Mei Shuli & Feng Lei, 2020. "A high-sensitivity multilayer soil moisture monitoring sensor based on a double high-frequency tuning detection circuit," International Journal of Distributed Sensor Networks, , vol. 16(2), pages 15501477209, February.
    • Handle: RePEc:sae:intdis:v:16:y:2020:i:2:p:1550147720907826
    DOI: 10.1177/1550147720907826
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    1. Virginia Strati & Matteo Albéri & Stefano Anconelli & Marica Baldoncini & Marco Bittelli & Carlo Bottardi & Enrico Chiarelli & Barbara Fabbri & Vincenzo Guidi & Kassandra Giulia Cristina Raptis & Dome, 2018. "Modelling Soil Water Content in a Tomato Field: Proximal Gamma Ray Spectroscopy and Soil–Crop System Models," Agriculture, MDPI, vol. 8(4), pages 1-17, April.
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