| Issue |
E3S Web of Conf.
Volume 537, 2024
International Scientific and Practical Conference “Sustainable Development of the Environment and Agriculture: Green and Environmental Technologies” (SDEA 2024)
|
|
|---|---|---|
| Article Number | 08010 | |
| Number of page(s) | 7 | |
| Section | Digital and Engineering Technologies as a Factor in the Intensive Development of Agriculture | |
| DOI | https://doi.org/10.1051/e3sconf/202453708010 | |
| Published online | 13 June 2024 | |
Analysis of directions for application of artificial intelligence systems in analysis of the state of water resources
1 Ural State Economic University, Ekaterinburg, Russia
2 Ural State Forest Engineering University, Ekaterinburg, Russia
* Corresponding author: 9089267986@mail.ru
Optimizing the use of water resources in conditions of increasing intensity of agricultural production is an important scientific and national economic problem. The complexity and uncertainty of forecasting agricultural demand for water resources necessitates the use of artificial intelligence systems. The authors reviewed research on the use of artificial intelligence systems in the field of analyzing the state of water resources in agricultural production. The purpose of the study is to analyze research on the use of artificial intelligence systems in the field of analyzing the state of water resources for agricultural needs. The scope of application of artificial intelligence systems is to increase the awareness of managers and specialists of agricultural organizations and industry management bodies about the state of water resources. This, in turn, allows you to make optimal decisions on various agricultural activities. The use of artificial intelligence models for water resource management in agriculture will provide significant economic benefits. The areas of application of these models are related to optimizing the use of water resources, saving water, increasing crop yields, saving money on water quality analysis.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.