Olena Fedusenko
Faculty of Information Technology, Taras Shevchenko National University of Kyiv, Ukraine
Natalia Shkurpela
Faculty of Information Technology, Taras Shevchenko National University of Kyiv, Ukraine
Iryna Domanetska
Faculty of Information Technology, Taras Shevchenko National University of Kyiv, Ukraine
Anatoliy Fedusenko
Military unit-К1410, Ukraine
Abstract
DOI: https://doi.org/10.17721/AIT.2021.1.02
The are crop planning problems exist in a modern agriculture of Ukraine. With the help of the intelligent support system for agro-technological decisions proposed by the authors, it is possible to simplify the planning process by using the concept of precision farming. Modern fields monitoring methods were analyzed and methods that will be used in the intelligent system are identified. The k-means method is one of them and will be applied to field clustering. The authors analyzed modern research and publications related to the concept of precision farming and the problem of implementing modern innovative information systems in agriculture of Ukraine. The decomposition of the intelligent system was carried out. Six main subsystems were identified, functional requirements were developed for each of them. Modern methods of fields monitoring are analyzed and methods that will be used in the intelligent system are identified, one of which is the k-means method, which will be applied to field clustering. Based on the already developed requirements, the authors have developed the general architecture of the system. The notation TOGAF was applied for the graphical display of the architecture. Based on the proposed architecture, intelligent system software was created. As a result of testing the soft-ware of the intelligent system, it is possible to draw a conclusion about its efficiency and readiness for implementation. The designed and developed system allows to carry out intellectual analysis of historical data of crops, to display results in the form of tables and graphs, to carry out planning of crops, agrotechnological operations and fertilizer application. The introduction of this system will improve the quality of management decisions and productivity of agricultural activities.
Keywords – intelligent system, precision farming, cluster analysis, agro-technological solutions.
Information about the author
Olena Fedusenko. Works as an associate professor of the Department of Intellectual Technologies of Taras Shevchenko National University of Kyiv, Kyiv, Ukraine. She got degree of candidate of technical sciences in the field of information technologies in 2006. He is the author of more than 60 scientific works. Research interests include adaptive learning systems, genetic algorithms and their application, Data Mining methods.
Natalia Shkurpela. She graduated with a bachelor’s degree in Computer Science from Taras Shevchenko National University of Kyiv.
Iryna Domanetska. Works as an associate professor of the Department of Intellectual Technologies of Taras Shevchenko National University of Kyiv, Kyiv, Ukraine. She has a Ph.D. in information technology. He is the author of more than 100 scientific works. His research interests include system-technical research in the field of IT, neural network technologies and their application, adaptive learning systems
Anatoliy Fedusenko. Serviceman. He graduated from Kyiv National University of Construction and Architecture in 2000 with a degree in automation engineering. He received the degree of Candidate of Technical Sciences in the field of information technology in 2016. He is the author of many scientific works. Research interests include genetic algorithms and their application, Data Mining and data visualization methods, adaptive learning systems
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Published
2021-11-04
How to Cite
O. Fedusenko , N. Shkurpela , I.Domanetska , A. Fedusenko . “Intelligent support system for agro-technological decisions for sowing fields”, Advanced Information Technology , vol.1, pp. 15–22, 2021
Issue
Advanced Information Technology № 1 (1), 2021
Section
Applied information systems and technology