Prospects for developing digital telecommunication complexes for storing and analyzing media data

Vladimir Kuklin, Islam Alexandrov, Dmitry Polezhaev, Aslan Tatarkanov


In today's digital world, saturated with data flows, universal multifunctional systems are developing, capable of solving various problems related to optimizing the use of available computing resources. A distinctive feature of such systems is the heterogeneity of incoming flows of user requests due to the multifunctionality of modern information systems, expressed in supporting various multimedia services on a single platform. Data heterogeneity and large volumes of data create many problems related to the speed of digital systems and data storage security. The solutions can be found in artificial intelligence (AI) technologies, particularly machine learning. Therefore, development and implementation of digital telecommunication complexes for storing, processing, and forming a dynamic flow of multiformat data using AI technologies are becoming more relevant. This paper aims to identify trends and prospects for developing these complexes, and develop proposals on their perspective characteristics. The authors focused on review the experience of Russian organizations developing multi-object analytics systems and analyze the technical and functional characteristics of existing systems. The result of the review and analysis is a table with a comparison of the technical characteristics of existing complexes and proposals for characteristics that are promising for further implementation.


Artificial intelligence technology; Digital telecommunication complex; Machine learning; Multiformat data processing and storage

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Bulletin of EEI Stats

Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191, e-ISSN: 2302-9285
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).