Design of databases in road industry using set-theory analysis of complex systems
https://doi.org/10.21285/2227-2917-2022-2-214-223
Abstract
In the article, a method for designing databases for the road industry that meets the requirements of the digital economy was developed. The set-theory analysis of complex systems implemented by relational databases (RDBs) was used. This approach meets current trends in the global digital economy, where relational databases provide efficient operation of the banking sector, industrial production management, fast data processing (bank cards, Internet search), etc. The Department of Roads at Irkutsk National Research Technical University designed and is developing the road database for the Irkutsk region. The paper considers the concept of this project and prospects of its further development with a view to the possible use of this database by remote users. The specifics of digital economy in the Russian Federation call for establishing branches and territorial databases, including the road database for the Russian regions. The efficient solutions for such a database were proposed, including, in particular, integrating remote users with the back-end database based on the attribute characteristics to limit the available content and allowable changes to the backend data.
About the Authors
A. A. Stepanenko
Irkutsk National Research Technical University
Russian Federation
Russian Federation
Anna A. Stepanenko, Senior lecturer of the Department of Automotive Highways
83 Lermontov St., Irkutsk, 664074
V. I. Martyanov
Irkutsk National Research Technical University
Russian Federation
Russian Federation
Vladimir I. Martyanov, Dr. Sci. (Phys.–Math.), Professor of the Department of Automotive Highways
83 Lermontov St., Irkutsk, 664074
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Review
For citations:
Stepanenko A.A., Martyanov V.I. Design of databases in road industry using set-theory analysis of complex systems. Izvestiya vuzov. Investitsii. Stroitelstvo. Nedvizhimost. 2022;12(2):214-223. (In Russ.) https://doi.org/10.21285/2227-2917-2022-2-214-223
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