Digital twins and smart cities solutions

Abstract: The transition from Beyond 5G (B5G) to 6G is a sea change in wireless communication technology, which is expected to upend industries such as transportation, healthcare, and manufacturing. By expanding upon the 5G network's current capabilities, B5G boosts mobile broadband, reduces power consumption, and maximizes spectrum usage. Advanced Internet of Things (IoT) devices and real-time applications are made possible by essential features like massive machine-type communications (mMTC) and ultra-low latency. The advent of 6G in the 2030s heralds revolutionary improvements such as intelligent surfaces, AI-driven network automation, and terahertz transmission frequencies. Thanks to this development, previously unimaginable speeds and bandwidth will be available, allowing for a proliferation of networked devices with latency reduced to microseconds. While resolving issues with present networks, these advancements will provide state-of-the-art solutions for smart cities and digital twins and enhance existing networks' capacities.

Cities worldwide are rapidly integrating urban management information technology (IT) systems to address increasing urban challenges effectively. This paper examines the evolution of these systems, from the Ubiquitous City (U-City) to contemporary Smart Cities, and explores emerging technologies like the Metaverse and Digital Twin. Despite their growing relevance, there is ambiguity in their conceptual definitions and how they are applied interchangeably in urban management contexts. This study aims to clarify these technologies by analyzing U-City, Smart City, Metaverse, and Digital Twin within an Analysis Framework of Urban Management IT Systems. Our analysis reveals distinct roles and interconnections among these technologies. U-City initiated the development of essential IT infrastructure, laying the groundwork for subsequent systems. Smart City technology, leveraging the infrastructure provided by U-City, addresses real urban issues but lacks predictive capabilities for future challenges. In contrast, the Metaverse facilitates the simulation of urban changes and planning in a virtual environment, influencing real-world city development. Digital Twin technology enhances the operational efficiency of U-City and Smart City by simulating real-world data and optimizing urban management processes. The study highlights that while U-City and Smart City function in the tangible realm, Metaverse and Digital Twin operate in the virtual domain, yet they are closely integrated. Metaverse assists in urban planning through simulations that inform real-world Smart City designs, while Digital Twin optimizes real-time city operations and informs Metaverse simulations for future planning. The findings underscore the importance of understanding these technologies’ unique contributions and their interplay. Although current urban management IT systems have limitations, especially in technology classification and data accessibility, this research paves the way for future investigations. Further research should focus on refining the definitions and applications of Metaverse and Digital Twin, clarifying their relationships with Smart City and U-City, and addressing security and privacy concerns associated with these technologies.

Smart City solutions are these days applied not only in big, but also in small and medium sized cities in a wide variety of countries worldwide. Also municiplaties in the Slovak Republic are using to a different extent smart city solutions to improve the life of their people. The goal of this paper, based on the premises, that also small and medium sized cities can become Smart City, is to present and analyse good examples of Smart City solutions in the Slovak Republic. The focus will be on the city Kezmarok, which can be considered as a medium sized city and which by implementing existing Smart City solutions from third parties, but mainly by developing innovative solutions directly in the city, can be seen as good example and good practise in the respective field.

This chapter presents the advantages of using APIs in the context of Smart City solutions and describes relevant successful practices. As there is still some uncertainty and the fear of compromising the security of data in these types of scenarios, most cities have just started using web APIs indicating that there are still opportunities for further enhancements. Different views on Smart City solutions result in different priorities and assumptions, so depending on the role, it is possible to differentiate between the programmer's (technical) and customer/citizen's perspective. The research was conducted with two groups of respondents: with end-users and programmers. The purpose of the survey was to find out the preferences and characteristics that potential users are looking for from Smart City solutions, while the aim of conducted interviews with programmers was to explore their attitudes about using web APIs in Smart City solutions.

INTRODUCTION: Digital twin technology is at the head of smart city innovations; rapid urbanization and the rising complexity of infrastructure management have driven this technology. Real time virtual replicas of the physical urban systems - digital twins - simulate urban scenarios, monitor conditions, and improve resource allocation more accurately than ever before. Rigorous empirical studies that quantify the impact of these technologies on the efficiency of urban planning are rare, curbing evidence-based policy making and large-scale adoption strategies. OBJECTIVES: This study estimates a panel fixed effects econometric model that quantifies the impact of integrating digital twins on urban planning performance of five European countries (Estonia, Germany, Portugal, the UK, Poland) over the period of 2020–2024. METHODS: Using data from the OECD Smart Cities database, the European Commission Urban Data Platform, the World Bank’s Worldwide Governance Indicators, and national municipal APIs, annual data were assembled on a composite urban efficiency index, a digital twin integration score, real time data usage, per capita infrastructure investment, governance quality metrics, and population density. The model employs city and time fixed effects and addresses heteroskedasticity and serial correlation with clustered robust standard errors. RESULTS: The efficiency index of Germany improved from 53,52 in 2020 to 62,57 in 2024; Poland from 45,51 to 58,73; and Estonia dropped sharply from 70,22 to 39,44. Coefficients on digital twin integration (β₁ = 12,00) and governance quality (β₄ = 8,00) are positive and statistically significant. Real-time data use (β₂ = 0,08) and infrastructure investment (β₃ = 0,004) increase efficiency, while population density has a slight negative effect (β₅ = –0,005). CONCLUSION: This underscores the importance of the network and governance relationships of digital twins in realizing their potential. Future research should include non-European cities, apply spatial econometric techniques to account for intercity spillovers, and use dynamic panel models to assess feedback loops from past efficiency gains and their influence on future technology investment.

The digital twin, adapted to the needs of urban planning and monitoring systems, is the subject of research and development in the academic, commercial and public sectors. The article provides international context in conceptual and practical implementation through their maturity level, scope, purpose, structure, input, processing features and output. The City of Zagreb is presented as an example of the implementation of GIS and 3D city models in urban planning, with activities towards a digital twin city. Based on research and local specifics, the concept of a digital city twin was proposed for the needs of urban planning, and future challenges were identified.

Abstract. Technology has advanced and progressed tremendously, and the term city is being elevated to a new level where the smart city has been introduced globally. Recent developments in the concept of smart city have led to a renewed interest in Digital Twin. Using precise Building Information Modelling (BIM) consolidated with big data and sensors, several attempts have been made to establish digital twin smart cities. In recent years, several researchers have sought to determine the capability of smart city and digital twin for various taxonomies such as development and urban planning purposes, built environment, manufacturing, environmental, disaster management, and healthcare. Despite being beneficial in many disciplines, especially in manufacturing, built environment, and urban planning, these existing studies have shown a lack of aspect in terms of emergency or disaster-related as opposed to the elements mentioned above. This is because the researcher has not treated emergencies or disasters in much detail. Therefore, an extensive review on smart city, digital twin, BIM and disaster management and technology that revolves around these terms were summarised. In general, 39 articles from prominent multidisciplinary databases were retrieved over the last two decades based on the suggested PRISMA workflow. These final articles were analysed and categorised into four themes based on the research content, gist, and keywords. Based on the review of 39 articles related to smart city, digital twin and BIM, a workflow for the smart city digital twin and the conceptual framework for indoor disaster management was proposed accordingly. The establishment of smart city digital twins solely for an indoor emergency can be beneficial to urbanites, and it could provide numerous benefits for enhanced situation assessment, decision making, coordination, and resource allocation.

Smart cities solutions are often monolithically implemented, from sensors data handling through to the provided services. The same challenges are regularly faced by different developers, for every new solution in a new city. Expertise and know-how can be re-used and the effort shared. In this article we present the methodologies to minimize the efforts of implementing new smart city solutions and maximizing the sharing of components. The final target is to have a live technical community of smart city application developers. The results of this activity comes from the implementation of 35 city services in 27 cities between Europe and South Korea. To share efforts, we encourage developers to devise applications using a modular approach. Single-function components that are re-usable by other city services are packaged and published as standalone components, named Atomic Services. We identify 15 atomic services addressing smart city challenges in data analytics, data evaluation, data integration, data validation, and visualization. 38 instances of the atomic services are already operational in several smart city services. We detail in this article, as atomic service examples, some data predictor components. Furthermore, we describe real-world atomic services usage in the scenarios of Santander and three Danish cities. The resulting atomic services also generate a side market for smart city solutions, allowing expertise and know-how to be re-used by different stakeholders.

The idea of a smart city has evolved in recent years from limiting the city’s physical growth to a comprehensive idea that includes physical, social, information, and knowledge infrastructure. As of right now, many studies indicate the potential advantages of smart cities in the fields of education, transportation, and entertainment to achieve more sustainability, efficiency, optimization, collaboration, and creativity. So, it is necessary to survey some technical knowledge and technology to establish the smart city and digitize its services. Traffic and transportation management, together with other subsystems, is one of the key components of creating a smart city. We specify this research by exploring digital twin (DT) technologies and 3D model information in the context of traffic management as well as the need to acquire them in the modern world. Despite the abundance of research in this field, the majority of them concentrate on the technical aspects of its design in diverse sectors. More details are required on the application of DTs in the creation of intelligent transportation systems. Results from the literature indicate that implementing the Internet of Things (IoT) to the scope of traffic addresses the traffic management issues in densely populated cities and somewhat affects the air pollution reduction caused by transportation systems. Leading countries are moving towards integrated systems and platforms using Building Information Modelling (BIM), IoT, and Spatial Data Infrastructure (SDI) to make cities smarter. There has been limited research on the application of digital twin technology in traffic control. One reason for this could be the complexity of the traffic system, which involves multiple variables and interactions between different components. Developing an accurate digital twin model for traffic control would require a significant amount of data collection and analysis, as well as advanced modeling techniques to account for the dynamic nature of traffic flow. We explore the requirements for the implementation of the digital twin in the traffic control industry and a proper architecture based on 6 main layers is investigated for the deployment of this system. In addition, an emphasis on the particular function of DT in simulating high traffic flow, keeping track of accidents, and choosing the optimal path for vehicles has been reviewed. Furthermore, incorporating user-generated content and volunteered geographic information (VGI), considering the idea of the human as a sensor, together with IoT can be a future direction to provide a more accurate and up-to-date representation of the physical environment, especially for traffic control, according to the literature review. The results show there are some limitations in digital twins for traffic control. The current digital twins are only a 3D representation of the real world. The difficulty of synchronizing real and virtual world information is another challenge. Eventually, in order to employ this technology as effectively as feasible in urban management, the researchers must address these drawbacks.

Application of artificial intelligence in digital twin models for stormwater infrastructure systems in smart cities

This study examines the potential of digital twin (DT) technology to strengthen urban security, with a specific focus on flood risk management in smart cities. A DT is understood as a virtual representation of real-world assets and processes, continuously synchronised with data from the physical environment. Building on an analysis of the existing DT literature and maturity assessment, identified operational requirements and the authors’ expertise in crisis management, this study proposes a structured set of DT maturity levels with stage boundary conditions and illustrative measurable indications and designs a maturity-driven data content model for a flood-oriented DT. The framework identifies essential data layers, sensing requirements and integration mechanisms necessary for representing hydrological, infrastructural and environmental conditions at operationally meaningful update frequencies. This study further outlines the conceptual architecture of a flood DT and discusses its potential to support prediction, situational awareness and decision making across crisis management phases. By providing recommendations for DT implementation and highlighting opportunities for future development, this study contributes to ongoing efforts to enhance the resilience and safety of urban areas through advanced digital technologies.

Recently, Digital Twins solutions have attracted a growing interest as a fundamental paradigm for managing data driven processes on smart cities. They are complex modelling that should include 3D interactive representations of buildings and infrastructures, integrated with a wide range of data for Smart City cyber-physical ecosystem monitoring and controlling. This paper presents a framework for modelling, generating and distributing Digital Twin representations with 3D models from a various set of data, as well as its integration into the open-source Smart City framework, where many kinds of real time and historical data are available. The proposed solution offers a method for creating integrated data rendering of 3D city entities coupled with Smart City data (e.g., IoT Devices with time-series and historical data, heatmaps, geometries and shapes related to traffic flows, bus routes/stops, cycling paths). The solution for generating 3D representation is based on a number of computer vision and machine learning solutions, thus shortening the activities of passing from raw data (i.e., Lidar, shapes, patterns, etc.) to 3D representations. Implementation has been enforced into the quite widespread open-source Snap4City Smart City platform and has been validated by using hundreds of buildings in Florence city central area, Italy, plus hundreds of thousands of data as points of interest, IoT Devices, traffic flows, dynamic heatmaps, etc.

In this paper, we present a smart framework for Internet-of-Things (IoT) enabled environments that promotes consumer interaction with that smart environment while still providing the control and management functionality necessary to manage the environment. Traditional smart frameworks focus solely upon the control and management functionality, allowing for consumer interaction via a centralized controller only (typically through a website or dedicated application). Traditional frameworks work in small, single manager environments, but are impractical in even medium sized, complex, or distributed multi- manager environments such as smart homes, smart buildings, and smart cities. Our framework is built upon the Liberated Object Location System (LOLS) that provides a distributed, decentralized, secure, and consumer oriented system that merges a control management framework for data collection and analysis with the consumers and the smart elements in the environment. Digital twins, or proxy services, are created for each device. LOLS provides a directory service for each device and its digital twin, allowing consumers to interact with the connected devices in the environment either directly or through the digital twin. Digital twins may exist at multiple levels in the information hierarchy, allowing for localized, regional, or even global functional scope. All digital twins are integrated with the environment control and management functionality, allowing for scalable, distributed smart environments that provide a consumer accessible interface for each smart device.

Digital Twins are emerging as a transformative technology within Cyber-Physical Systems (CPS), offering enhanced optimization, predictive maintenance, and real-time monitoring. However, their integration also introduces significant security challenges. These include vulnerabilities such as data breaches, unauthorized access, and cyber-attacks that disrupt real-time data flow between their physical and digital components. The involvement of IoT devices, sensors, and complex networked environments expands the attack surface, making Digital Twins susceptible to threats like Distributed Denial-of-Service (DDoS) attacks, malware infiltration, and insider sabotage. Effective risk management and assessment are crucial in identifying vulnerabilities, evaluating risks, and implementing mitigation strategies. Securing Digital Twins ensures data integrity, system reliability, and the continued functionality of the physical assets they represent. This paper aims to classify the various security threats associated with Digital Twins and propose structured risk management approaches to enhance their security within CPS. By addressing these challenges, organizations can ensure the dependability and trustworthiness of Digital Twin implementations across industries such as manufacturing, healthcare, smart cities, and IoT ecosystems.

The paper aims to compare NX Mechatronic Concept Designer (MCD) and Tecnomatix Process Simulate (TPS) and their suitability for simulating mechatronic machines in digital twinning. A Digital Twin (DT) is a virtual model that serves as a real-time digital counterpart of a physical object or process. Compared to a conventional simulation, it differs in its ability to model the behavior of the actual counterpart from many points of view and with much greater complexity. Digital Twins have a crucial role in the Fourth Industrial Revolution but are also used in different areas like meteorology, traffic simulation in smart cities, and civil engineering. Digital Twins in industrial engineering help maintain the optimal pace of assembly lines, flexibly adapt production, increase manufacturing process efficiency, and generate cost-effective products. Increasing usage of IoT solutions drives the Digital Twin market, which is growing exponentially. The paper discusses the two software packages’ possibilities, advantages, and disadvantages and proposes the methodology and philosophy of making DT. The contribution of this work is to compare the possibilities of making mechatronic devices for educational and research purposes from scratch through to their final implementation.