Using Digital Twins to Combat Climate Change in BRICS Countries

Threat modeling is a critical proactive security technique for identifying threats and determining mitigations. However, traditional approaches often fall short for Industrial Control Systems (ICS), which automate operations in domains like manufacturing and energy and are a subset of Cyber-Physical Systems (CPS). CPS integrates computation, networking, and physical processes, with ICS requiring specialized cybersecurity approaches due to its operational and safety-critical nature. This study explores the use of digital twin technology as a promising cybersecurity tool for ICS, enabling testing and analysis without disrupting operations. By examining the capabilities of digital twins in analysis, simulation, and replication, the research evaluates their potential to enhance threat modeling across the CPS life-cycle. Insights from the European Cyber Security Organisation (ECSO) Technical Paper on Cybersecurity Scenarios and Digital Twins guide the exploration of their role in threat modeling. The study addresses four research questions: 1. What purposes do digital twins serve in cybersecurity? 2. What benefits do digital twins offer in cybersecurity? 3. How can digital twin technology be leveraged for threat modeling? 4. What advantages can the use of digital twins bring to threat modeling? Our findings reveal that digital twins enhance ICS threat modeling by enabling continuous, dynamic, and autonomous assessment, offering valuable insights for advancing cybersecurity strategies in ICS, CPS, and related domains.

The modern world is undergoing rapid changes, driven by both technological progress and dynamic political and economic processes. In this constantly changing environment, adaptability and flexibility have become critical criteria for business survival, especially in secondary sectors such as transport and logistics. These industries are increasingly faced with the urgent need to optimize financial flows in conditions of high uncertainty and market volatility. In parallel, the pressure for transparency, cost-effectiveness and rapid response in the decision-making process is growing.One of the most promising solutions to these problems is the integration of digital twins into the planning and execution of logistics processes. Digital twins are dynamic virtual models that reflect real objects, systems and processes in real time, allowing companies to simulate operations, track changes and predict results with a high degree of accuracy. While the use of digital twins has been widely studied in engineering, manufacturing, and supply chain optimization, their application to financial management in logistics companies remains relatively underdeveloped and understudied.This paper addresses this critical gap by proposing a conceptual model for integrating digital twin technology into financial decision-making processes in logistics. It explores how digital twins can be used to dynamically monitor costs, simulate cash flows, and increase transparency and traceability of financial transactions. With these capabilities, logistics firms can achieve better cost control, reduce inefficiencies, and improve overall financial performance. The novelty and significance of this study is due to the lack of standardized approaches to implementing digital twin technologies into financial workflows. To address this issue, the paper also provides a review of practical examples and current implementations of digital twins by logistics companies around the world, focusing on the measurable impact of such integrations on financial performance and strategic agility.Key words:logistics process, financial flows, digital twin, cost planning, business process.

This research investigates the use of digital twin (DT) technology to improve building energy management and analyse occupant behaviour. DTs perform the function of acting as virtual replicas of physical assets, which facilitates real-time monitoring, predictive maintenance, and data-driven decision-making. Consequently, energy performance and occupant comfort can be enhanced. This study evaluates the efficiency of DTs in optimising energy usage by a mix of a systematic literature review and scientometric analysis of 466 articles from the Scopus database. Among the main obstacles noted are interoperability issues, privacy and data quality difficulties, and the requirement for a more thorough integration of digital and physical interactions. The results highlight the necessity of standardised frameworks to direct DT implementations and suggest areas for further study, especially in the areas of improving cybersecurity and incorporating occupant behaviour into DT models. This research makes practical recommendations for using DT technology to increase energy efficiency and sustainability in the built environment.

Given the high mortality rate from cardiovascular diseases and the need to transfer medicine to a more high-tech level of development, the authors propose the use of digital twin technology for the diagnosis and treatment of heart diseases. As a digital twin of the human heart, it is proposed to use the combination of an equivalent electric heart generator and the of D. Noble computer heart model within the subsystem for supporting medical decision-making. The use of such digital twin will make it possible to reliably conduct non-invasive cardiodiagnosis to select drugs within the treatment regimen.

Digital Twin (DT) technology is revolutionizing industry in the Industry 4.0 era by enabling simulating, analyzing, and monitoring physical assets real-time. To reduce downtime for machines, improve maintenance schedules, and maximize equipment lifespan, this research explores the use of digital twins in implementing predictive maintenance (PdM) concepts. An imitation of an actual machine or process that is continuously supplied with information from embedded Internet of Things sensors is referred to as a "digital twin." Condition-driven maintenance, in contrast to reactive or time-based maintenance, is enabled by the system to predict failures before they occur by the integration of AI/ML algorithms. With reference to four key components—data collection, model building, simulation environment, and feedback mechanisms—the research provides a conceptual framework for the application of digital twins in a typical manufacturing environment. It also illustrates a case study of a CNC machine that employs real-time temperature and vibration data to anticipate spindle bearing issues. Compared to standard methods, DT-based predictive maintenance enhances asset availability, cost savings, and accuracy in maintenance significantly. To deliver insights into future directions and scalability of DT in smart factories, the article concludes by considering challenges such as data security, interoperability, and computing complexity. Keywords: Industry 4.0, IoT, Smart Manufacturing, Machine Learning, CNC, Condition Monitoring, Digital Twin, Predictive Maintenance.

The article focuses on the project to develop a supply chain management information system using a digital twin for the maritime transport chain. Digital twins reflect real objects and processes in a virtual environment, which enables analysis, modelling and optimisation of supply chain operations. The author describes the main stages of the project, including requirements definition, system architecture development, implementation and testing. Particular attention is paid to the benefits of using digital twins in supply chain management, such as increased efficiency, reduced risk and improved forecasting. The results of the study show the potential of digital twins to optimise supply chain management and increase the competitiveness of companies. The article presents an approach to building a new model of interaction and systematic optimisation of business processes based on digital technologies at all stages of supply chain formation, which ensures the creation of a digital twin for the maritime transport chain. In order to improve supply chains, a digital twin has been proposed, which opens up great prospects for the management of logistics processes and the exchange of information between supply chain participants. This paper presents a framework for an integral Digital Supply Chain Twin (DSCT) capable of covering the entire transport chain. The proposed information system based on the use of the DSCT provides a number of improvements throughout the supply chain, as well as the ability to model and evaluate different scenarios for the supply chain. This creates opportunities to reduce the cost of organising and coordinating transport, improve the quality of transport and logistics services and make them more reliable by identifying potential problems at an early stage. The article analyses the main information technologies that facilitate the use of DSCT as a useful and reliable tool.

Purpose This study aims to investigate the relationship between the use of digital twin (DT) and the overall equipment effectiveness (OEE) metric from the perspective of Lean 4.0. Design/methodology/approach A systematic literature review was conducted, and the resulting articles were subjected to a content analysis based on Bardin (2011). Using spreadsheets and graphical software, the data were organised to facilitate the presentation of the results. Findings The results characterise the DT into two groups, which address the level of integration of this system: “Partial interaction” and “Full interaction”. With this distinction made, we gathered the inhibitors related to the development of full DT integration, to detail opportunities and insights from the application of Lean 4.0, enabling the migration from one system to another and allowing operational excellence through the OEE indicator. Research limitations/implications This study is limited by its theoretical approach, relying on a systematic literature review rather than empirical validation. It also highlights insights into how Lean 4.0 can be used by professionals to facilitate the transition from Partial Interaction to Full Interaction models for the integration of OEE measurements. Originality/value The novelty of this study lies in the application of Lean 4.0 to enable DT integration across production systems, filling a gap in the literature regarding the use of DT for tracking OEE as a tool to enable operational excellence.

Digital Twin (DT) technology is a pivotal innovation within the built environment industry, facilitating digital transformation through advanced data integration and analytics. DTs have demonstrated significant benefits in building design, construction, and asset management, including optimising lifecycle energy use, enhancing operational efficiency, enabling predictive maintenance, and improving user adaptability. By integrating real-time data from IoT sensors with advanced analytics, DTs provide dynamic and actionable insights for better decision-making and resource management. Despite these promising benefits, several challenges impede the widespread adoption of DT technology, such as technological integration, data consistency, organisational adaptation, and cybersecurity concerns. Addressing these challenges requires interdisciplinary collaboration, standardisation of data formats, and the development of universal design and development platforms for DTs. This paper provides a comprehensive review of DT definitions, applications, capabilities, and challenges within the Architecture, Engineering, and Construction (AEC) industries. This paper provides important insights for researchers and professionals, helping them gain a more comprehensive and detailed view of DT. The findings also demonstrate the significant impact that DTs can have on this sector, contributing to advancing DT implementations and promoting sustainable and efficient building management practices. Ultimately, DT technology is set to revolutionise the AEC industries by enabling autonomous, data-driven decision-making and optimising building operations for enhanced productivity and performance.

Towards the future of smart electric vehicles: Digital twin technology

Introduction. Digitalization of the construction industry, including individual housing construction, is becoming a global trend. Digital Twin (DT) technology allows to create a virtual copy of a physical object and synchronize it with real data online. Aim. To analyze the use of digital twins in private housing construction, identify the challenges of digitalization, and determine promising areas of development based on foreign research and case studies. Materials and methods. The article is based on foreign research analyzing the technological architecture of a digital twin and the necessary software and hardware components for its creation. Results. The analysis shows that creating a digital twin requires a carefully collected database (DataRoom), the integration of sensors, IoT devices, and analytical tools, as well as real-time data synchronization and AI model training based on the owners' behavior. Cloud platforms provide scalability for the system, but there are also barriers to implementation. Practical significance. The article shows that digital twins of private homes are becoming part of the smart home concept, improving the operation and interaction of residents. It offers recommendations for real-time data processing, optimizing operational modes, adapting control to the behavior of owners, and intelligently predicting consequences. Conclusions. The digital twin of a private house occupies an important place in the technological and social context, transforming approaches to construction and resident interaction. It combines the functions of a passport, a manager, and an analyst, making the house smart, adaptive, and secure, capable of responding to internal and external challenges, acting as a "digital shadow".

The Digital Twin (DT) technology is considered as a backbone in the Industrial 4.0 revolution as it is playing a vital role in the digitization of various industries. A DT is a virtual representation of a physical entity, thus having the ability to simulate real data generated at physical space to optimize, estimate, control, monitor and forecast states / configurations. Despite enormous benefits, DT technology has several implementation challenges. Although deploying DT on edge or cloud platforms yields a plethora of services, its implementation in both spaces faces certain limitations. These limitations include latency, data communication overload, transmission energy consumption, privacy concerns, and communication inefficiencies. It is evident that these shortcomings could significantly impact real-time monitoring and control. Therefore, when considering whether to deploy DT on the edge or on the cloud, it is necessary to make a trade-off, or alternatively, adopt a hybrid approach. However, it is important to acknowledge that even with a hybrid approach, the aforementioned issues will persist to some extent. To address these challenges, this article introduces two innovative approaches. Local DT (LDT) and Distributed DT (DDT). These deployment strategies are designed to mitigate latency, minimize data communication overload, reduce energy consumption, improve communication efficiency, and strengthen privacy measures.Thus, resulting in environmental and economic sustainability. Consequently, these advancements facilitate superior real-time monitoring and control capabilities. Through the utilization of LDT and DDT methodologies, organizations can harness the full potential of DT technology, thereby maximizing its benefits.

The emergence of Digital Twin (DT) technology has garnered significant attention in healthcare, providing a revolutionary approach to patient care, diagnostics, and treatment planning. Digital twins are virtual replicas of physical entities (in this case, human beings), created through the integration of real-time data collected from sensors and devices. This paper explores the potential role of Digital Twin technology in healthcare, its applications, challenges, and opportunities. We review recent studies and current implementations, focusing on the integration of digital twins for personalized care, predictive analytics, and decision-making. The research also highlights the barriers such as data privacy concerns, high implementation costs, and technological limitations. The findings point to a future where Digital Twin technology plays a central role in improving patient outcomes, operational efficiency, and the accuracy of treatments in healthcare. The paper concludes with a discussion of future research directions and applications for digital twins in healthcare. The purpose of this research study is to examine how digital twins can transform healthcare by going over the prospects, difficulties, and future course of their integration into healthcare systems. This study looks at the existing situation in an effort to offer insightful information about how digital twins can transform healthcare delivery and enhance patient care, while also identifying the challenges that need to be addressed for their widespread adoption

Aim. Development of the author’s concept of increasing the efficiency of financial risk management on the basis of application of the technology of creating and using the digital twin of the enterprise.Objectives. To formalize the problems of existing approaches to solving the problems of financial risk management of enterprises of the real sector of economy; to identify trends in the development of digital twins, to formulate the advantages of their practical application and to give the author’s interpretation of the concept of “digital twin of the enterprise”; to build and substantiate a multilayer system of indicators of the digital twin of the enterprise in the context of improving the efficiency of financial risk management; to develop the principles of building a digital twin of the enterprise, focused on solving the problems of financial risk management.Methods. The research was carried out on the basis of system approach, in the process of realization of which the methods of synthesis, logical comparative, factor and graphical analysis, basic provisions of financial risk management and the results obtained in domestic and foreign scientific literature on the problems of realization of approaches and methods of financial risk management were used.Results. The author’s concept of increasing the efficiency of financial risk management based on the application of new technologies for creating digital twins is proposed. In particular, by means of formalizing the problems of existing approaches to solving the problems of financial management, identifying trends in the development of methodology and technologies for creating digital twins, the idea of increasing the efficiency of financial risk management on the basis of creating a digital twin of the enterprise is outlined. The multilayer system of indicators defining the structure of this digital twin is proposed and substantiated, the tasks are defined and the principles of its construction oriented to solving the tasks of financial risk management are developed. The financial kernel of the digital twin of the enterprise is constructed, containing the contours of formation of financial indicators common for different enterprises, determining the achievement of the objectives of financial risk management and its efficiency. The qualitative substantiation of increasing the efficiency of financial risk management with the application of the methodological basis for the creation and use of digital twins proposed in the article is given.Conclusions. Conceptual provisions of creation and use of digital twins for the purposes of financial risk-management, given in the article, create a theoretical and methodological basis for increasing the efficiency of financial risk-management taking into account the use of new digital technologies and can serve as a basis for practical construction of effective systems of financial risk-management at enterprises of the real sector of economy.

The growing interest in Digital Twin (DT) Technology represents a significant advancement in academic research and industrial applications. Leveraging advancements in Internet of Things (IoT), sensors, and communication devices, DTs are increasingly utilised across different sectors, notably in the energy domain such as Power Systems and Smart Grids. DT concepts facilitate the creation of virtual models mirroring physical assets, streamlining real-time data management and analysis. Driven by the potential of DTs to revolutionise energy systems, this paper offers a comprehensive review of DT applications in the power sector, specifically within next-generation energy systems like Smart Grids. TThe integration of DT technology with Machine Learning (ML) algorithms is highlighted as a key factor in significantly enhancing the performance and capabilities of these advanced energy systems. In contrast to prior reviews, our study meticulously investigates all of the crucial components of energy systems, including forecasting, anomaly detection, and security, which are fundamental for improving the management of operational grids. In addition, the study examines the seamless incorporation of Renewable Energy into current grids and investigates how DT technology could contribute to Electric Vehicles for increased sustainability and reliability within the Smart Grid framework. This review underlines that DTs significantly enhance the management of real-time data and analysis, consequently improving operational grid management. There are ample opportunities into further research and development to design a more advanced and digital system as compared to conventional power systems. The findings are presented in clear and concise tables, highlighting current limitations, proposing effective solutions, and identifying potential future research directions in academia and industry.

The Halal supply chain, which encompasses the sectors of food, medicines, cosmetics, has enormous challenges to comply with Islamic rules, maintain product traceability and combating fraud. Given the increasing global demand for Halal products, the demand for technology innovations to enhance supply chain transparency and ensure Halal compliance is growing. This paper explores the application of Digital Twin (DT) technology in Halal supply chain management, highlighting its ability to address these challenges. The main research question of this paper is as follows: How can Digital Twin technology facilitate transparency, traceability, and compliance in the Halal supply chains? The current study employs a qualitative methodology through a review of the extant literature and reviews of industrial case studies. The study reveals that the Digital Twin technology promises to considerably improve the operational excellence of Halal supply chains through real-time Halal status monitoring ensuring that products comply with religious and ethical requirements along the supply chain. The main applications include tracking Halal certification, preventing cross-contamination, and enhancing transparency for certification bodies, manufacturers, and consumers. The results indicate that Digital Twin technology has the potential to transform Halal supply chains by reducing fraud, improving operational efficiencies, and building consumer trust. As a comprehensive Halal compliance solution, Digital Twin can enable a more transparent and trustworthy Halal certification process on a global scale. The study extends the knowledge body on technology innovations in supply chain management especially with religious and ethical product certifications and sets the stage for future research in the area.