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Some features of training future technical engineers for the application of artificial intelligence in the field of geoinformatics

https://doi.org/10.32517/0234-0453-2025-40-5-37-48

Abstract

The distinctive feature of Industry 4.0 is digital transformation of all sectors of the economy, accompanied by an exponential growth in the volume of data. Among these data, spatial data (geodata) makes up a significant share. Artificial Intelligence (AI) is becoming a key factor in the implementation of advanced technologies and digital tools in the field of geoinformatics, using machine learning algorithms (ML). This creates a pressing need for training students to use AI in this field, both from the modern labor market and in the context of engineering education.

The article examines the features of training future technical engineers whose professional functions involve managing geodata using AI. It is revealed the technological potential of AI for effective geodata management and examines the significance and prospects of using AI in geoinformatics. The methodical recommendations are offered for integrating AI into basic educational programs of future engineers. It is developed the content of disciplines aimed at mastering AI and ML, taking into account the features of geodata and spatial analysis. This will ensure high-quality training of future engineering and technical personnel for the use of AI to solve problems of analyzing and processing geodata in their professional activities.

About the Author

N. A. Moiseeva
Omsk State Technical University
Russian Federation

Natalya A. Moiseeva, Candidate of Sciences (Education), Docent, Associate Professor at the Department “Applied Mathematics and Fundamental Informatics”, Faculty of Information Technology and Computer Systems

Omsk



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For citations:


Moiseeva N.A. Some features of training future technical engineers for the application of artificial intelligence in the field of geoinformatics. Informatics and education. 2025;40(5):37-48. (In Russ.) https://doi.org/10.32517/0234-0453-2025-40-5-37-48

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ISSN 0234-0453 (Print)
ISSN 2658-7769 (Online)