Development of a Fuzzy Variable Rate Irrigation Control System Based on Remote Sensing Data to Fully Automate Center Pivots Article Swipe
Willians Ribeiro Mendes
,
Salah Er‐Raki
,
Derek M. Heeren
,
Ritaban Dutta
,
Fábio Meneghetti Ugulino de Araújo
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202106.0564.v1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202106.0564.v1
Growing agricultural demands for the global population are unlocking the path to developing innovative solutions for efficient water management. Herein, an intelligent variable rate irrigation system (fuzzy-VRI) is proposed for rapid decision-making to achieve optimized irrigation in various delimited zones. The proposed system automatically creates irrigation maps for a center pivot irrigation system for a variable-rate application of water. Primary inputs are spatial imagery on remotely sensed soil moisture (SSM), soil adjusted vegetation index (SAVI), canopy temperature (CT), and nitrogen content (NI). To eliminate localized issues with soil characteristics, we used the crop nitrogen content map to provide a focused insight on issues related to water shortage. The system relates these inputs to set reference values for the rotation speed controllers and individual openings of each central pivot sprinkler valve. The results showed that the system can detect and characterize the spatial variability of the crop and further, the fuzzy logic solved the uncertainties of an irrigation system and defined a control model for high-precision irrigation. The proposed approach is validated through the comparison between the recommended irrigation and actual irrigation at two field sites, and the results showed that the developed approach gives an accurate estimation of irrigation with a reduction in the volume of irrigated water of up to 27% in some cases. Future research should implement the fuzzy-VRI real-time during field trials in order to quantify its effect on irrigation use, yield, and water use efficiency.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.20944/preprints202106.0564.v1
- https://www.preprints.org/manuscript/202106.0564/v1/download
- OA Status
- green
- Cited By
- 2
- References
- 60
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3173954967
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3173954967Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.20944/preprints202106.0564.v1Digital Object Identifier
- Title
-
Development of a Fuzzy Variable Rate Irrigation Control System Based on Remote Sensing Data to Fully Automate Center PivotsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-06-23Full publication date if available
- Authors
-
Willians Ribeiro Mendes, Salah Er‐Raki, Derek M. Heeren, Ritaban Dutta, Fábio Meneghetti Ugulino de AraújoList of authors in order
- Landing page
-
https://doi.org/10.20944/preprints202106.0564.v1Publisher landing page
- PDF URL
-
https://www.preprints.org/manuscript/202106.0564/v1/downloadDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.preprints.org/manuscript/202106.0564/v1/downloadDirect OA link when available
- Concepts
-
Center pivot irrigation, Irrigation, Agricultural engineering, Environmental science, Precision agriculture, Fuzzy logic, Computer science, Variable (mathematics), Remote sensing, Mathematics, Agriculture, Engineering, Artificial intelligence, Geography, Agronomy, Mathematical analysis, Biology, ArchaeologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2024: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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60Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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