Automated Low-Cost Soil Moisture Sensors: Trade-Off between Cost and Accuracy
(2023) In Sensors 23(5).- Abstract
- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/e4c2df95-e664-42d5-a674-d3c80667364d
- author
- Schwamback, Dimaghi LU ; Persson, Magnus LU ; Berndtsson, Ronny LU ; Bertotto, Luis Eduardo ; Kobayashi, Alex Naoki Asato and Wendland, Edson Cezar
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Sensors
- volume
- 23
- issue
- 5
- article number
- 2451
- pages
- 18 pages
- publisher
- MDPI AG
- external identifiers
-
- scopus:85149797984
- pmid:36904655
- ISSN
- 1424-8220
- DOI
- 10.3390/s23052451
- language
- English
- LU publication?
- yes
- id
- e4c2df95-e664-42d5-a674-d3c80667364d
- date added to LUP
- 2023-03-06 10:24:46
- date last changed
- 2023-10-10 10:23:58
@article{e4c2df95-e664-42d5-a674-d3c80667364d, abstract = {{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<br/>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.}}, author = {{Schwamback, Dimaghi and Persson, Magnus and Berndtsson, Ronny and Bertotto, Luis Eduardo and Kobayashi, Alex Naoki Asato and Wendland, Edson Cezar}}, issn = {{1424-8220}}, language = {{eng}}, number = {{5}}, publisher = {{MDPI AG}}, series = {{Sensors}}, title = {{Automated Low-Cost Soil Moisture Sensors: Trade-Off between Cost and Accuracy}}, url = {{http://dx.doi.org/10.3390/s23052451}}, doi = {{10.3390/s23052451}}, volume = {{23}}, year = {{2023}}, }