On optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plots
One of the main stream of digitalization in agriculture is the introduction of Internet of Things technologies, which is expressed in the creation and use of specialized sensors that are placed in the fields. The placement of such sensors within agricultural plot should make it possible to character...
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| Format: | Article |
| Language: | Russian |
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V.V. Dokuchaev Soil Science Institute
2022-07-01
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| Series: | Бюллетень Почвенного института им. В.В. Докучаева |
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| Online Access: | https://bulletin.esoil.ru/jour/article/view/694 |
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| author | I. Yu. Savin Yu. I. Blokhin |
| author_facet | I. Yu. Savin Yu. I. Blokhin |
| author_sort | I. Yu. Savin |
| collection | DOAJ |
| description | One of the main stream of digitalization in agriculture is the introduction of Internet of Things technologies, which is expressed in the creation and use of specialized sensors that are placed in the fields. The placement of such sensors within agricultural plot should make it possible to characterize all the microvariability of soil fertility parameters in the field. That is, their number and spatial location should be optimal, on the one hand, in terms of costs of their acquisition and operation, and, on the other hand, in terms of accuracy of interpolation of data obtained with their help to the entire plot. It has been shown that the use of crop condition maps obtained on the basis of satellite data and the separation based on them of management zones can lead to significant errors in the interpolation of monitoring results, obtained in separate points, on the whole plot. An approach for optimization of sensor placement is proposed based on the use of soil fertility mapping, which is the result of refinement, updating and clarification of traditionally drawn soil maps on the basis of high spatial resolution remote sensing data. The possibilities of using the approach are demonstrated by the example of a test plot in Leningrad region of Russia. |
| format | Article |
| id | doaj-art-1d4df4c0c0cd4e978e22d2af41b9e7cf |
| institution | Matheson Library |
| issn | 0136-1694 2312-4202 |
| language | Russian |
| publishDate | 2022-07-01 |
| publisher | V.V. Dokuchaev Soil Science Institute |
| record_format | Article |
| series | Бюллетень Почвенного института им. В.В. Докучаева |
| spelling | doaj-art-1d4df4c0c0cd4e978e22d2af41b9e7cf2025-08-03T13:37:42ZrusV.V. Dokuchaev Soil Science InstituteБюллетень Почвенного института им. В.В. Докучаева0136-16942312-42022022-07-010110225010.19047/0136-1694-2022-110-22-50566On optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plotsI. Yu. Savin0Yu. I. Blokhin1Federal Research Centre “V.V. Dokuchaev Soil Science Institute”Agrophysical Research InstituteOne of the main stream of digitalization in agriculture is the introduction of Internet of Things technologies, which is expressed in the creation and use of specialized sensors that are placed in the fields. The placement of such sensors within agricultural plot should make it possible to characterize all the microvariability of soil fertility parameters in the field. That is, their number and spatial location should be optimal, on the one hand, in terms of costs of their acquisition and operation, and, on the other hand, in terms of accuracy of interpolation of data obtained with their help to the entire plot. It has been shown that the use of crop condition maps obtained on the basis of satellite data and the separation based on them of management zones can lead to significant errors in the interpolation of monitoring results, obtained in separate points, on the whole plot. An approach for optimization of sensor placement is proposed based on the use of soil fertility mapping, which is the result of refinement, updating and clarification of traditionally drawn soil maps on the basis of high spatial resolution remote sensing data. The possibilities of using the approach are demonstrated by the example of a test plot in Leningrad region of Russia.https://bulletin.esoil.ru/jour/article/view/694precise agriculturesoil sensorssoil spatial variabilityinternet of things in agriculturesentinel-2 |
| spellingShingle | I. Yu. Savin Yu. I. Blokhin On optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plots Бюллетень Почвенного института им. В.В. Докучаева precise agriculture soil sensors soil spatial variability internet of things in agriculture sentinel-2 |
| title | On optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plots |
| title_full | On optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plots |
| title_fullStr | On optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plots |
| title_full_unstemmed | On optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plots |
| title_short | On optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plots |
| title_sort | on optimizing the deployment of an internet of things sensor network for soil and crop monitoring on arable plots |
| topic | precise agriculture soil sensors soil spatial variability internet of things in agriculture sentinel-2 |
| url | https://bulletin.esoil.ru/jour/article/view/694 |
| work_keys_str_mv | AT iyusavin onoptimizingthedeploymentofaninternetofthingssensornetworkforsoilandcropmonitoringonarableplots AT yuiblokhin onoptimizingthedeploymentofaninternetofthingssensornetworkforsoilandcropmonitoringonarableplots |