5‐2: Unveiling Privacy Challenges: Big Data‐Driven Digital Twins in Smart City Applications

Industrial Internet of Water Things architecture for data standarization based on blockchain and digital twin technology☆

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.

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.

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.

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.

Navigating the Digital Twin Network landscape: A survey on architecture, applications, privacy and security

The inherent nature of public health emergencies often renders them unpredictable and inadequately managed in a timely manner, resulting in significant impacts on lives, property, and social stability. In recent years, the frequency and severity of such emergencies have escalated. As an integration of artificial intelligence, machine learning, deep learning, big data, and the Internet of Things, digital twin technology has been increasingly adopted across diverse fields, including industrial production, urban planning, and healthcare. This study aimed to investigate recent advancements in digital twin technology, particularly in the fields of medicine and urban construction, with a focus on its potential to mitigate the impacts of public health crises. By employing the PPRR framework, this study further explored the prospects for constructing and applying digital twin technology within the public health management system. Taking perceived fidelity (SF), model plasticity (MP), decision coupling (DC), and governance credibility (GC) as the core constructs, we discussed the operability of unified modeling and quantitative evaluation of each stage of digital twin implementation. This approach comprehensively explained all four phases of emergency management: prevention, preparedness, response, and recovery. Through enabling the digitalization, intelligence, and visualization of the entire health emergency management process, digital twin technology offers holistic solutions throughout the life cycle of public health emergencies. These include preventive measures, real-time detection, early warning systems, and intelligent emergency response management. Such innovations have the potential to significantly enhance management efficiency and effectiveness, bolster coordinated responses to public health crises, and improve the overall resilience of public health systems.

In the VUCA era, supply chain disruptions are increasingly frequent and severe, posing significant challenges to global manufacturing industries. This study investigates the application and challenges of emerging technologies, particularly digital twin (DT) technology, in supply chain risk management through a qualitative case study approach. Focusing on six manufacturing enterprises, three of which have deployed DT and three still rely on traditional models, this research aims to reveal the practical effectiveness and implementation obstacles of DT technology in risk identification, assessment, and response stages. Traditional risk management methods, often based on periodic assessments and static contingency plans, have proven inadequate in addressing sudden global crises, as exemplified by the 2023 Red Sea crisis's impact on the European automotive industry. This study employs document analysis of enterprise risk reports, audit records, and emergency response plans to demonstrate how DT technology can transform risk management into a proactive, predictive strategy. The findings show that DT technology enhances supply chain resilience by enabling real-time risk perception, dynamic simulation, and automated response. However, the adoption of DT technology also faces challenges such as organizational division, financial barriers, and human resistance to change. This research provides actionable guidelines for enterprises to navigate the complex path of digital transformation and offers a low-tech threshold risk management upgrade path, especially for small and medium-sized manufacturers.

This chapter discusses the applications of Digital Twin (DT) technology for dental care, to develop precision and patient-specific solutions for advancing dental care. Simulating and fine-tuning procedures for better outcomes are achievable through virtual replicas of patients' oral anatomy by incorporating data from IoT. Methodology This requires developing patient models using 3D imaging, IoT sensors, and big data analytics to simulate treatments such as orthodontic adjustments or implant placements. Key results indicate a 25% increase in the overall efficiency of diagnostics and a corresponding 15% saving in procedural time, with risks cut down by 10%. Specific case studies demonstrate its effectiveness in customized treatment, prosthetic design, and post-treatment follow-up. With minor setbacks in integrating data, cost, and implementation, it is revealed that digital twin technology is transforming dental care by giving better and more effective interventions in practice. This chapter is a resource guide for dental professionals and healthcare providers.

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

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 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.

Background: With the rapid development of digital twinning technology, the compatibility of digital twinning technology to other technologies is continuously enhanced. It is because of this that the application of image recognition technology in digital twinning technology becomes a reality. However, the key technology of digital twin, the virtual-actual mutual control technology, is not mature enough, and the image recognition technology applied in digital twin technology also has the problem of coordinate system transformation, which becomes an important link of image recognition technology in digital twin. Methods: Based on the above two problems, we take the tangram splicing project as an example to realize a virtual-actual mutual control method, so that the digital twinning technology can be well presented. Furthermore, we implement an image recognition applied to the conversion of digital twinning technology, so that digital twinning technology and image recognition have a seamless connection, allowing the application range of digital twinning technology to be further expanded. Results: In this paper, image recognition technology is successfully applied to digital twin technology by adopting the conversion between different coordinate systems and the real and virtual real time control, which makes the applicability of digital twin technology in high-tech fields such as smart factories and smart manufacturing to a higher level. Conclusions: Finally, through the tangram splicing project, the motion trajectories of the robotic arm and the tangram are consistent with the virtual robotic arm and the tangram in the computer. It is proved that our method can well combine digital twinning technology and image recognition technology.

• Examined various battery types, BMS architectures, and modelling techniques. • Explored deterministic, non-deterministic, and hybrid SOC estimation methods. • Discussed SOH estimation and RUL prediction using various methods. • Exploration of digital twin technologies and battery digital twins (BDTs) for enhancing BMS functionality. • Discussion of future research directions in battery state estimation. Accurate state estimation is fundamental for the safety, reliability, and performance of electric vehicle (EV) batteries. This review highlights the critical need for precise evaluation of key battery states such as state of charge (SOC), state of health (SOH), and remaining useful life (RUL). It surveys the existing modelling and estimation techniques used in lithium-ion battery (LIB) systems. It explores parameter identification methods and the challenges associated with real-time monitoring and predictive diagnostics in dynamic EV environments. The paper further investigates the transformative role of digital twin (DT) technologies in addressing these challenges. By integrating battery digital twins technologies(BDTs): Internet of Things (IoT), cloud computing, artificial intelligence (AI), and extended reality (XR), it offers a virtual replica of the battery system. That enables continuous monitoring, predictive maintenance, and performance optimization. The review delves into the architecture, functions, challenges and future perspectives of battery digital twins (BDTs). And it emphasizes their potential to enhance traditional battery management systems (BMS) through intelligent, adaptive control. Through comparative analysis and identification of research gaps, this review provides a roadmap for future advancements in state estimation and digital twin integration.

Purpose This study aims to explore the combined adoption of Blockchain and Digital Twin (DT) technologies in the construction industry, addressing a notable research gap where these technologies have primarily been studied in isolation. This study aims to identify and analyze the key factors influencing joint adoption, by capturing their intricate relationships under an integrated environment. Design/methodology/approach A systematic research methodology is adopted, which includes a systematic literature review to identify preliminary influencing factors. Subsequently, a fuzzy DEMATEL approach is used to model the interrelationships among 14 identified factors across financial, technological, design, regulatory and communication dimensions. Cause–effect diagrams are developed to understand the underlying structure of influence, followed by the compilation of strategies. Findings The analysis reveals 14 critical factors impacting the integrated use of Blockchain and DT technologies, with several sub-factors exhibiting strong cause-and-effect relationships. This study highlights the importance of technological readiness, regulatory clarity, financial feasibility and inter-organizational collaboration in successful adoption. The framework developed assists stakeholders in overcoming key challenges and enables efficient resource allocation for digital transformation initiatives. Research limitations/implications This study is limited by its reliance on literature-derived factors and expert-based fuzzy DEMATEL evaluations, which may introduce subjectivity. However, the results of this study provide a structured and actionable framework that assists policymakers, industry practitioners and project managers in prioritizing key factors, mitigating adoption barriers and formulating targeted strategies to accelerate digital transformation across the construction sector. Originality/value To the best of the authors’ knowledge, this paper is among the first to systematically examine the interplay between Blockchain and DT technologies in the construction sector using a fuzzy DEMATEL approach. Bridging a significant research gap provides novel insights and a practical framework that supports industry stakeholders in embracing digital solutions more effectively and sustainably.