Authors: E. A. Skvortsov, V. I. Nabokov, K. V. Nekrasov, E. G. Skvortsova, M. I. Krotov
Ural Federal University named after the first President of Russia B. N. Yeltsin, Ekaterinburg, Russia
Ural State Agrarian University, Ekaterinburg, Russia
Ural State University of the Railway Transport, Ekaterinburg, Russia E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract. The technologies of artificial intelligence (AI) are used in various sectors of the national economy, including agriculture. The purpose of the study is to identify the essence and summarize the directions of application of AI technologies in agriculture. These technologies are used in various fields of agriculture: the detection of plant diseases, the classification and identification of weeds, the determination and counting of fruits, the management of water resources and soil, the prediction of weather (climate), and the determination of animal behavior. AI technologies used in agriculture have a number of significant features. First of all, it is a software and hardware tool. AI technologies perform an intellectual function when performing work in agriculture, which consists in the ability to perform abstract reasoning, recognize images, act in conditions of incomplete information, show creativity, and ability to learn. The strengths of the application of AI technologies include increased labor productivity in agricultural sectors, increased efficiency in managerial decision-making processes, as well as increased access to information, increased human capabilities in the workplace, and the emergence of new professions. The main features are connected with various technical breakthroughs, in particular, machine learning, neural networks, big data, etc. This will create additional jobs in high-tech sectors, including programming. AI technologies will optimize food production worldwide and reduce the problem of global hunger. One of the threats is the outlined lag of the Russian Federation in the development of these technologies for agriculture from the advanced countries. The results of the study can be used by the executive authorities in the development of programs for innovative agricultural development and technical modernization of the industry.
Keywords: artificial intelligence, deep learning (DL), intellectual technologies, digital farming.
For citation: Skvortsov E. A., Nabokov V. I., Nekrasov K. V., Skvortsova E. G., Krotov M. I. Primeneniye tekhnologiy iskusstvennogo intellekta v sel’skom khozyaystve [Application of technologies of artificial intelligence in agriculture] // Agrarian Bulletin of the Urals. 2019. No. 8 (187). Pp. 91–98. DOI: 10.32417/article_5d908ed78f7fc7.89378141. (In Russian.)
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