Applications of the internet of things in agriculture

DOI: 10.31673/2412-4338.2022.026167

Abstract

The article examines the methods of implementing Internet of Things technologies in the agricultural sector, suggests the use of artificial intelligence and neural networks in combination with the Internet of Things to improve the results of growing various plants. The advantages of neural networks, which are able to process large arrays of data on the activity of agricultural formations much faster and more efficiently than an experienced specialist, are also considered. However, for this, the primary information for training the network should be prepared in a format that is understandable for it. Obtaining up-to-date and objective information about the condition of plants using the Internet of Things will improve the exchange of information between specialists and expert consultants.

Modern agriculture needs to have a high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. IoT is one of the most popular tools of this kind. It is widely used in solving various classification and prediction tasks. For some time IoT also been used in the broadly defined field of agriculture. It can form part of the precision farming and decision support systems. IoT and artificial neural networks can replace the classical methods of modeling, and are one of the main alternatives to classical mathematical models. The spectrum of the applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible.

Keywords: intelligent technologies, neural networks, artificial intelligence, agriculture, automation.

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