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Profile photo of Ronny Berndtsson

Ronny Berndtsson

Professor, Dep Director, MECW Dep Scientific Coordinator

Profile photo of Ronny Berndtsson

Automated Low-Cost Soil Moisture Sensors: Trade-Off between Cost and Accuracy

Author

  • Dimaghi Schwamback
  • Magnus Persson
  • Ronny Berndtsson
  • Luis Eduardo Bertotto
  • Alex Naoki Asato Kobayashi
  • Edson Cezar Wendland

Summary, in English

Automated soil moisture systems are commonly used in precision agriculture. Using low-cost sensors, the spatial extension can be maximized, but the accuracy might be reduced. In this paper, we address the trade-off between cost and accuracy comparing low-cost and commercial soil moisture sensors. The analysis is based on the capacitive sensor SKU:SEN0193 tested under lab and field conditions. In addition to individual calibration, two simplified calibration techniques are proposed: universal calibration, based on all 63 sensors, and a single-point calibration using the sensor response in dry soil. During the second stage of testing, the sensors were coupled to a low-cost monitoring station and installed in the field. The sensors were capable of measuring daily and seasonal oscillations in soil moisture resulting from solar radiation and precipitation. The
low-cost sensor performance was compared to commercial sensors based on five variables: (1) cost, (2) accuracy, (3) qualified labor demand, (4) sample volume, and (5) life expectancy. Commercial sensors provide single-point information with high reliability but at a high acquisition cost, while low-cost sensors can be acquired in larger numbers at a lower cost, allowing for more detailed spatial and temporal observations, but with medium accuracy. The use of SKU sensors is then indicated for short-term and limited-budget projects in which high accuracy of the collected data is not required.

Department/s

  • Division of Water Resources Engineering
  • Centre for Advanced Middle Eastern Studies (CMES)
  • MECW: The Middle East in the Contemporary World
  • LTH Profile Area: Water

Publishing year

2023

Language

English

Publication/Series

Sensors

Volume

23

Issue

5

Document type

Journal article

Publisher

MDPI AG

Topic

  • Signal Processing
  • Environmental Sciences related to Agriculture and Land-use

Status

Published

ISBN/ISSN/Other

  • ISSN: 1424-8220