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Soil Moisture Content Detection Based on Sensor Networks

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Big Data Computing and Communications (BigCom 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9784))

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Abstract

With rapidly development of wireless communications and electronics, precision agriculture turns into a promising application of the sensor networks. In this paper, the measurement of volumetric moisture content for soil is explored with the sensor networks. The method of high-frequency capacitance is applied to the moisture content detection for three kinds of arable soil: red soil, moisture soil and paddy soil. First of all, the measuring principle is analyzed: high-frequency equivalent electronic model of soil test plate is serially connected with constant inductor, so as to obtain the relation between the equivalent capacitance and resonance. Then we measure the correspondence between resonance frequency and soil volumetric moisture content through experimental methods, in addition, the impact of resonance frequency range and environmental temperature is analyzed. To the best of our knowledge, this is the first study on soil moisture content detection based on high-frequency capacitance covering circuit theory, hardware simulation, resonance-frequency selection, temperature compensation and sensor networks. The experimental results validate the effectiveness of our method, thus, our method possesses significant application value.

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Notes

  1. 1.

    Jiangsu Province, research joint innovation funds – BY2014037-07.

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Authors and Affiliations

  1. School of Information Science and Engineering, Changzhou University, Wujin, 213164, Jiangsu, China

    Zhan Huan, Li Chen, LianTao Wang & CaiYan Wan

Authors
  1. Zhan Huan
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  2. Li Chen
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  3. LianTao Wang
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  4. CaiYan Wan
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Corresponding author

Correspondence to Zhan Huan .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of N. Carolina at Charlotte, Charlotte, North Carolina, USA

    Yu Wang

  2. Northeastern University, College of Information Science and Engineering, Shenyang, Liaoning, China

    Ge Yu

  3. Department of Electrical & Computer Engineering, Rutgers University, Piscataway, New Jersey, USA

    Yanyong Zhang

  4. Department of Electrical and Computer Engineering, University of Houston Department of Engineering, Houston, Texas, USA

    Zhu Han

  5. College of Information Science and Engineering, Northeastern University, Shenyang , Liaoning, China

    Guoren Wang

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© 2016 Springer International Publishing Switzerland

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Huan, Z., Chen, L., Wang, L., Wan, C. (2016). Soil Moisture Content Detection Based on Sensor Networks. In: Wang, Y., Yu, G., Zhang, Y., Han, Z., Wang, G. (eds) Big Data Computing and Communications. BigCom 2016. Lecture Notes in Computer Science(), vol 9784. Springer, Cham. https://doi.org/10.1007/978-3-319-42553-5_14

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  • DOI: https://doi.org/10.1007/978-3-319-42553-5_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42552-8

  • Online ISBN: 978-3-319-42553-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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