Abstract With the development of science and technology, the high-tech industry is developing rapidly, and various new-age technologies continue to appear, and Digital Twins (DT) is one of them. As a brand-new interactive technology, DT technology can handle the interaction between the real world and the virtual world well. It has become a hot spot in the academic circles of all countries in the world. DT have developed rapidly in recent years result from centrality, integrity and dynamics. It is integrated with other technologies and has been applied in many fields, such as smart factory in industrial production, digital model of life in medical field, construction of smart city, security guarantee in aerospace field, immersive shopping in commercial field and so on. The introduction of DT is mostly a summary of concepts, and few practical applications of Digital Twins are introduced. The purpose of this paper is to enable people to understand the application status of DT technology. At the same time, the introduction of core technologies related to DT is interspersed in the application introduction. Finally, combined with the current development status of DT, predict the future development trend of DT and make a summary. 

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Application of Digital Twins in multiple fields

A neural blockchain for a tokenizable e-Participation model

Megacities are complex systems facing the challenges of overpopulation, poor urban design and planning, poor mobility and public transport, poor governance, climate change issues, poor sewerage and water infrastructure, waste and health issues, and unemployment. Smart cities have emerged to address these challenges by making the best use of space and resources for the benefit of citizens. A smart city model views the city as a complex adaptive system consisting of services, resources, and citizens that learn through interaction and change in both the spatial and temporal domains. The characteristics of dynamic development and complexity are key issues for city planners that require a new systematic and modeling approach. Multiscale modeling (MM) is an approach that can be used to better understand complex adaptive systems. The MM aims to solve complex problems at different scales, i.e., micro, meso, and macro, to improve system efficiency and mitigate computational complexity and cost. In this paper, we present an overview of MM in smart cities. First, this study discusses megacities, their current challenges, and their emergence to smart cities. Then, we discuss the need of MM in smart cities and its emerging applications. Finally, the study highlights current challenges and future directions related to MM in smart cities, which provide a roadmap for the optimized operation of smart city systems.

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Multiscale Modeling in Smart Cities: A Survey on applications, Current Trends, and Challenges

Traditionally, cities evolved over time into current quite rigid urban conurbations. As complexity of our political, social and economic environment increases, cities begin to experience new pressures - traffic congestion, pollution, immigration, overcrowding, inadequacy of services, to mention just a few, which affect both citizens and visitors. Digital technology now exists that we could use to turn rigid cities into Urban Ecosystems. The paper provides an updated definition of Smart City as an Urban Ecosystem, it analyses problems experienced by cities caused by complexity of the Internet-based global economy and describes an advanced solution - to design cities as urban ecosystems capable of delivering services to citizens and visitors under conditions of complexity. The authors have developed an evolutionary methodology that ensure a minimum of disruptions to city services during its transformation into an urban ecosystem. Design of Smart City ontology is provided as an example.

Smart City as an Urban Ecosystem

In this paper, Smart City is described as a live and constantly developing complex adaptive system operating in an uncertain environment with many participants and actors involved. The vision of the “Smart City 5.0” concept as an ecosystem of smart services based on multi-agent technology is presented. It is characterized by the cooperation of Artificial Intelligence systems and humans, and can harmoniously balance all spheres of life and contradictory interests of different city actors. In this concept, each smart service is presented by an autonomous agent. They can compete or cooperate with each other through a service bus and interact both vertically and horizontally on the basis of specialized protocols. Top-level services can be constructed as autonomous multi-agent systems of a lower level, where an agent can recursively reveal a new service for itself. The paper describes the design principals and the general architecture of the digital platform including the basic agent of smart service, the architecture and basic principles of smart city ontologies and knowledge base. The paper shows how the platform can support the decision-making life cycle for managing any urban object and the adaptive behaviour of Smart City 5.0 is compared with the fixed scenarios Smart City 4.0.

Smart City 5.0 as an Urban Ecosystem of Smart Services

The field of smart cities and the latest problems in this area of expertise accent the need for interaction among different areas, such as transportation, energy management, education, buildings and others. New technologies and new methods allow for a fast development of each of the areas and of the city itself. At the same time, there is a need for further involvement of citizens and different stakeholders in the decision-making process within cities. In order to demonstrate the impact of a new policy (e.g., building a new shopping center) on certain city aspect (e.g., transportation), simulation models have been recognized as probably the best approach. Unfortunately, there is still no tool that would allow the stakeholders to evaluate the impact of such a policy on a city as a whole and from multiple perspectives. Dedicated simulation frameworks should be used in cooperation, one for transportation, one for energy grid management, another for its impact on the environment until all important aspects are covered. This paper describes a complex tool aiming on overcoming such complicated demands and giving the policy makers one tool to assess impact on different interconnected fields. It combines existing dedicated simulation frameworks into a complete software suite that can combine even contradictory results into one or more performance indicators. This can be used as a decision support system and help in involving citizens into the city government and planning. This article focuses on the utilization of mobility modelling in such a software.

Sergei Kozhevnikov

Papers

Smart City 5.0 as an Urban Ecosystem of Smart Services

Smart City as an Urban Ecosystem

City Simulation Software: Perspective of Mobility Modelling

Smart Grid System for Real-Time Adaptive Utility Management in Smart Cities

Smart City as a Complex Adaptive System