Digital Technology Advancements in Knowledge Management in Domestic Tour Products in the Russian Federation: Theoretical and Methodological Aspects

Digital Technology Advancements in Knowledge Management in Domestic Tour Products in the Russian Federation: Theoretical and Methodological Aspects

Vardan Mkrttchian, Viacheslav Voronin
Copyright: © 2021 |Pages: 14
DOI: 10.4018/978-1-7998-6792-0.ch007
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Abstract

This chapter discusses the capabilities with problem-oriented digital twin avatars, supply chain, volumetric hybrid, and federated-consistent blockchain use to the nature of knowledge. The goal of this chapter is a theoretical study and practical implementation in the form of basic models and software modules and artificial intelligence algorithms in managing the life cycle of an internal Russian tour product. A laboratory for digitization and management, using multi-agent models of intelligent digital twins-avatars, is created. The purpose of these studies is to solve a scientific problem.
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Introduction

The chapter fits into a moment of operational uncertainty and theoretical redevelopment of the nature of tourism in a society marked by geopolitical turmoil and declining international security, as well as rapid changes at the global level, including the pandemic (COVID-19), which is currently posing new challenges for the sector. Today, it is more relevant and appropriate than ever to reflect on them, with the new, digital energy of blockchain technology, using a fundamental approach to digitalizing the decentralized lifecycle management of the domestic Russian tour product with problem-oriented digital twin avatars, supply chain, volumetric hybrid and federated-consistent blockchain. The goal of the chapter is theoretical study and practical implementation, in the form of basic models and software modules, artificial intelligence algorithms in managing the life cycle of an internal Russian tour product. Why at the State Sochi University, using the scientific potential of the head and responsible executors of the project, the Laboratory for digitalization and management of tour products, using multi-agent models of intelligent digital twins-avatars, is being created, the purpose of these studies is to solve a scientific problem in terms of creating an integrated scientific and methodological approach to modeling and design of monitoring systems, diagnostics and management of distributed cyber-physical objects and processes in the network segments of the Industrial Internet of Things based on the convergence of engineering technologies, data mining and in-depth analysis of processes, predictive modeling and machine learning. The objectives of the research are related to the development of new models, methods and a set of tools for digital transformation of monitoring, diagnostics and management of distributed cyber-physical objects during the transition to the digital economy within the framework of the fourth industrial revolution (Industry 4.0). The results of design research are needed to synthesize the architecture of a new generation of intelligent cyber-physical systems, which represents a multi-agent computing ecosystem. It is designed to provide decision support processes based on monitoring events and processes at distributed cyber-physical objects of the Russian tourism industry. In such systems, there are many cyber-physical objects that receive a huge amount of sensory data that cannot be processed by humans in real time. Currently, there are no ready-made integrated solutions for modeling and designing distributed monitoring and control systems for cyber-physical objects. Despite advances in engineering and knowledge management, the use of this approach for the synthesis of cyber-physical monitoring and control systems is still poorly developed. Such systems work with a variety of distributed cyber-physical objects, which are, in most cases, measuring devices with sensors that collect and accumulate sensor data for transmission to a processing center via a telecommunications network. The results of data analysis are used for predictive modeling of the dynamics of the development of processes at cyber-physical objects and for making management decisions. Cyber-physical monitoring and control systems are needed to automate the decision-making process based on data mining. The relevance of the project is associated with the need to develop and develop new universal mechanisms for modeling and designing cyber-physical systems using new control technologies and in-depth analysis of processes at controlled objects of the Russian tour product. For in-depth analysis of processes, it is necessary to develop automated technologies for collecting, storing and intelligent analysis of data obtained from controlled cyber-physical objects of the Russian tour product. The scientific novelty of design research consists in the creation of a new scientific and methodological approach to the modeling and design of cyber-physical systems for monitoring and controlling distributed objects and processes in the network segments of the Industrial Internet of Things, as well as the methodology for distributed monitoring, diagnostics and recovery of these systems during their operation. Scientific and practical significance lies in the creation of new technologies and software and tools for the synthesis of cyber-physical systems for monitoring and controlling distributed objects and processes on the Internet of Things. For in-depth analysis of processes, it is necessary to develop automated technologies for collecting, storing and intelligent analysis of data obtained from controlled cyber-physical objects of the Russian tour product. The scientific novelty of design research consists in the creation of a new scientific and methodological approach to the modeling and design of cyber-physical systems for monitoring and controlling distributed objects and processes in the network segments of the Industrial Internet of Things, as well as the methodology for distributed monitoring, diagnostics and recovery of these systems during their operation. Scientific and practical significance lies in the creation of new technologies and software and tools for the synthesis of cyber-physical systems for monitoring and controlling distributed objects and processes on the Internet of Things. A new generation cyber-physical monitoring and control system is implemented in the form of a hyper-converged component-based architecture of a reconfigurable ecosystem, which performs the functions of multi-agent processing of large amounts of sensor data in a computing grid of sensor node controllers based on a fog (edge) computing model.

Key Terms in this Chapter

Internet of Everything: Is a broad term that refers to devices and consumer products connected to the internet and outfitted with expanded digital features.

Big Data: Is extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

Internet of People and Things: Is a system of interrelated computing devices, mechanical and digital machines, objects, animals, or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

Internet of Signs: Is categories of signs, including written language, natural language, cultural codes, aesthetic codes, codes of tastes and a number of others.

Context: Is the circumstances that form the setting for an event, statement, or idea, and in terms of which it can be fully understood.

Big Context: Is defined as a better understanding of how entities.

Internet of Things: Is the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data.

Semiotics: Is the study of signs and symbols and their use or interpretation.

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