The forest industry complex was left without the ICC

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Market players discussed this during theII Federal Forum on IT and Digitalization in the Forestry Complex (FIC). Ivan Kozlov, the development director of the IT-Dialogue club, reported that in Russia there was an idea to reproduce the Finnish technology so that in the future it would be possible to count every tree, but it was not implemented. "The Finns have long been counting and recording the GPS coordinates of each micro-elevation (an inverted layer of soil where a tree is planted). The result is a database that allows us to track where a forest will grow in the future. The idea was to obtain the GPS coordinates and overlay them on the state information system (GIS). But when we tried to repeat the Finnish technology in Russia, we encountered a problem with the connection," he reported.

Ivan Kozlov noted that it was not bahrain whatsapp resource possible to reproduce the technology and achieve the accuracy necessary for placing data in the GIS, but it was possible to collect statistics on the number of micro-elevations per hectare of land. According to him, the escalator operator can now see the density of tree planting on his smartphone, which allows him to better determine the boundaries of territories.

Andrey Karpilovich, director of special projects at the All-Russian Society for Nature Conservation, believes that even negative results can be viewed positively, and the experience gained can be discussed in competence centers.

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The forest industry complex (FIC) turned out to be the only significant sector of the Russian economy for which an industrial competence center (ICC) has not appeared. Market participants are interested in cooperation to create industry information solutions, but the ICC idea was treated with caution.

As Andrey Dmitriev, Managing Director - Head of Client Transformation Directorate CIB, Sberbank PJSC, noted, research and development work should be divided into two types: the first solutions are ready-made business cases that can bring economic benefits in the near future, and the second are knowledge-intensive projects that require long-term investments, but management and investors do not always see potential in their implementation.

One such controversial project, according to Andrey Dmitriev, is unmanned harvesters (special equipment that fells trees and trims branches). According to him, the drivers of this equipment work in difficult conditions, and large companies are looking for a solution to replace drivers with automated systems. However, Andrey Dmitriev considers investments in such a project to be highly risky due to the complexity of development and its high cost.

Vice President of Information Technology at Ilim Group Irina Pirogova noted that their company has both successful and failed examples of production automation. According to her, when assessing the economic effect of a fully robotized finished goods warehouse, it turned out that working the old way remains more profitable for the company.

"Since 2007, we have been storing information on production management - we collect data after each shift. We do not have an answer as to what needs to be aggregated and what does not, but the capacity allows us to store this data. Of course, we prepare analytical reports, but we understand that this data can be used more intensively," noted Irina Pirogova. According to her, the analytical systems that companies install are primarily aimed at business analysts, not IT specialists, but there is a shortage of such analysts in business, so businesses are not yet able to use huge amounts of data to the maximum.

Sergey Merkulov, Director of Digital Transformation, PJSC Segezha Group, noted two factors that complicate working with data in the forest industry: firstly, problems with lighting and communication in the forest, and secondly, the human factor. "Data throughout the production chain is generated by humans - this is a geometric method for measuring wood. But in this case, they are subject to external influence. If you incorrectly determine, for example, the cause of defects, then when analyzing large volumes of data, you can come to the wrong conclusions," said Sergey Merkulov.

According to him, in order to avoid unreliable data, the company should automate the sources of its receipt, namely, use drones, computer vision, so that similar or identical algorithms that are not subject to emotions are used when collecting data. "In an ideal picture of the world, the role of a person in routine processes should be at the final stage for decision-making. And routine tasks for collecting data and their primary analysis should be translated into mathematical models," concluded Sergey Merkulov.