Data-driven Soil Moisture Sensing with mmWave Radar

Yujie Zhuang; Yang Zhao; Jie Liu

doi:10.1145/3671127.3698787

Data-driven Soil Moisture Sensing with mmWave Radar

Yujie Zhuang
, Yang Zhao
, Jie Liu

Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Existing soil moisture sensing methods require either plugging probes into soil or burying sensor nodes or aluminum plate in soil. These methods either have mobility and maintenance limitations or have risks of battery leakage. To address these issues, we propose to build a soil moisture sensing dataset using millimeter-wave radar for non-invasive and non-contact moisture sensing of shallow soil. Our millimeter-wave radar soil moisture dataset includes 20 different moisture levels, filling the gap in mmWave radar-based soil moisture sensing datasets. Furthermore, we propose a mm-SoilNet model, which uses the data-driven approach to extract soil moisture features from radar data to estimate the volumetric water content of soil. Our initial experimental results show that the system achieves a mean absolute error of 5.506%.

Original language	English
Title of host publication	BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
Publisher	Association for Computing Machinery, Inc
Pages	287-290
Number of pages	4
ISBN (Electronic)	9798400707063
DOIs	https://doi.org/10.1145/3671127.3698787
State	Published - 29 Oct 2024
Externally published	Yes
Event	11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2024 - Hangzhou, China Duration: 7 Nov 2024 → 8 Nov 2024

Publication series

Name	BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

Conference

Conference	11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2024
Country/Territory	China
City	Hangzhou
Period	7/11/24 → 8/11/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

mmWave radar
soil moisture sensing

Access to Document

10.1145/3671127.3698787

Cite this

Zhuang, Y., Zhao, Y., & Liu, J. (2024). Data-driven Soil Moisture Sensing with mmWave Radar. In BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 287-290). (BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation). Association for Computing Machinery, Inc. https://doi.org/10.1145/3671127.3698787

Zhuang, Yujie ; Zhao, Yang ; Liu, Jie. / Data-driven Soil Moisture Sensing with mmWave Radar. BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. Association for Computing Machinery, Inc, 2024. pp. 287-290 (BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation).

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title = "Data-driven Soil Moisture Sensing with mmWave Radar",

abstract = "Existing soil moisture sensing methods require either plugging probes into soil or burying sensor nodes or aluminum plate in soil. These methods either have mobility and maintenance limitations or have risks of battery leakage. To address these issues, we propose to build a soil moisture sensing dataset using millimeter-wave radar for non-invasive and non-contact moisture sensing of shallow soil. Our millimeter-wave radar soil moisture dataset includes 20 different moisture levels, filling the gap in mmWave radar-based soil moisture sensing datasets. Furthermore, we propose a mm-SoilNet model, which uses the data-driven approach to extract soil moisture features from radar data to estimate the volumetric water content of soil. Our initial experimental results show that the system achieves a mean absolute error of 5.506\%.",

keywords = "mmWave radar, soil moisture sensing",

author = "Yujie Zhuang and Yang Zhao and Jie Liu",

note = "Publisher Copyright: {\textcopyright} 2024 Copyright held by the owner/author(s).; 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2024 ; Conference date: 07-11-2024 Through 08-11-2024",

year = "2024",

month = oct,

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doi = "10.1145/3671127.3698787",

language = "英语",

series = "BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation",

publisher = "Association for Computing Machinery, Inc",

pages = "287--290",

booktitle = "BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation",

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Zhuang, Y, Zhao, Y & Liu, J 2024, Data-driven Soil Moisture Sensing with mmWave Radar. in BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, Association for Computing Machinery, Inc, pp. 287-290, 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2024, Hangzhou, China, 7/11/24. https://doi.org/10.1145/3671127.3698787

Data-driven Soil Moisture Sensing with mmWave Radar. / Zhuang, Yujie; Zhao, Yang ; Liu, Jie.
BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. Association for Computing Machinery, Inc, 2024. p. 287-290 (BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Data-driven Soil Moisture Sensing with mmWave Radar

AU - Zhuang, Yujie

AU - Zhao, Yang

AU - Liu, Jie

PY - 2024/10/29

Y1 - 2024/10/29

N2 - Existing soil moisture sensing methods require either plugging probes into soil or burying sensor nodes or aluminum plate in soil. These methods either have mobility and maintenance limitations or have risks of battery leakage. To address these issues, we propose to build a soil moisture sensing dataset using millimeter-wave radar for non-invasive and non-contact moisture sensing of shallow soil. Our millimeter-wave radar soil moisture dataset includes 20 different moisture levels, filling the gap in mmWave radar-based soil moisture sensing datasets. Furthermore, we propose a mm-SoilNet model, which uses the data-driven approach to extract soil moisture features from radar data to estimate the volumetric water content of soil. Our initial experimental results show that the system achieves a mean absolute error of 5.506%.

AB - Existing soil moisture sensing methods require either plugging probes into soil or burying sensor nodes or aluminum plate in soil. These methods either have mobility and maintenance limitations or have risks of battery leakage. To address these issues, we propose to build a soil moisture sensing dataset using millimeter-wave radar for non-invasive and non-contact moisture sensing of shallow soil. Our millimeter-wave radar soil moisture dataset includes 20 different moisture levels, filling the gap in mmWave radar-based soil moisture sensing datasets. Furthermore, we propose a mm-SoilNet model, which uses the data-driven approach to extract soil moisture features from radar data to estimate the volumetric water content of soil. Our initial experimental results show that the system achieves a mean absolute error of 5.506%.

KW - mmWave radar

KW - soil moisture sensing

UR - https://www.scopus.com/pages/publications/85211380831

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DO - 10.1145/3671127.3698787

M3 - 会议稿件

AN - SCOPUS:85211380831

T3 - BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

SP - 287

EP - 290

BT - BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

PB - Association for Computing Machinery, Inc

T2 - 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2024

Y2 - 7 November 2024 through 8 November 2024

ER -

Zhuang Y, Zhao Y , Liu J. Data-driven Soil Moisture Sensing with mmWave Radar. In BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. Association for Computing Machinery, Inc. 2024. p. 287-290. (BuildSys 2024 - Proceedings of the 2024 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation). doi: 10.1145/3671127.3698787

Data-driven Soil Moisture Sensing with mmWave Radar

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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