Abstract
The issues that are currently identified in Russia during the implementation of Digital Agriculture project are considered. The main issues that need to be addressed in development of modern digital technologies in the fish farming industry using natural and artificial reservoirs are highlighted. Aqua engineering trends and scientific works of a number of teams that conduct research and use the capabilities of deep machine learning, are analyzed. Particular attention was paid to specific tasks and research results that solve applied problems in the field of aquaculture and fish farming. Conclusions are made about the prospects for implementing these objectives in Russia. The conclusions of scientific teams and new tasks set as a result of scientific experiments are considered. The main directions in the area of commercial fish farming that need active adaptation of computer vision to deal with applied problems, are identified. Questions of efficiency in introduction of neural networks of deep learning are raised, and also conclusions are drawn on introduction of the term “selectivity” to determine the relation of a data set received by a digital method, referred to quantity of the same data which would be received at their collection by means of non-digital technologies.
Highlights
With the growth of computing power, libraries for software development, popularity of digital technologies and at the same time simplification of methods of mastering programming languages, there was a call for deep digitalization of the most specific areas of national economy
The fish feeding procedure was recorded by an unmanned aerial vehicle (UAV), the images were analyzed with the help of computer vision technology of disturbances appeared on the surface ("peak" of pixels that are brighter than pixels in the immediate neighborhood)
It would be interesting to test this technology in the conditions of river fish farming, because the degree of water transparency is obviously different and, as a consequence, it is complicates the ability of computer vision technology to analyze the parameters of fish
Summary
With the growth of computing power, libraries for software development, popularity of digital technologies and at the same time simplification of methods of mastering programming languages, there was a call for deep digitalization of the most specific areas of national economy. The team of authors of this article has been actively developing digital solutions for the problems of fish farming in the Tyumen region [1, 2]. This article is of a review nature, since a detailed analysis of foreign practices at the "junction" of IT and fish farming is interesting, first of all, because it will make it possible to form a spread of areas that are relevant for fish farming abroad. In this regard, the logic of the presentation will follow the principle "information given in the article - summing up - applicability for fish farming in the Tyumen region"
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