Digital Twin – Page 2

Securing the Future: Cybersecurity Challenges and Approaches in Extended Reality and Interactive Experiences

Extended Reality (XR) and interactive experiences are revolutionizing training by bridging the gap between theoretical knowledge and practical application. Unlike traditional methods, such as text-based manuals or passive video demonstrations, XR enables scenario-based simulations that allow users to engage with real-world challenges in a risk-free environment. This approach can enhance engagement, improve knowledge retention, and ensure that content can be adapted to evolving industry demands and emerging knowledge.

However, the widespread adoption of XR also raises critical cybersecurity concerns, particularly regarding data collection, management, and protection. The absence of established policies and procedures exacerbates these risks, increasing vulnerability to data breaches and cyberattacks. Without more stringent regulatory frameworks, XR platforms may inadvertently compromise security rather than strengthen it.

This paper examines the intersection between XR and cybersecurity, highlighting both the transformative potential of immersive learning experiences and the urgent need for robust data protection measures. Addressing these challenges is essential to ensuring that XR technologies can be safely and effectively integrated into training environments without undermining security principles.

Revealing and Interpreting Complex Urban Patterns from Location Based Social Network Data. An Investigation into Chinese Stadiums in the Global South

This paper focuses on the adoption of big data visual representation and semantic interpretation to study complex urban patterns in places largely impervious to traditional mapping technologies and documentary analytical tools. In particular, it examines stadiums built by China in the Global South as part of a broader strategy of building diplomacy. Between 1959 and 2022, China facilitated approximately 2,000 construction projects in developing countries, among which more than 150 are large-scale sports facilities. While these buildings have mainly been analyzed from architectural and typological perspectives, their relationships with the surrounding urban environments and their effects on local communities and ecosystems have remained largely unexplored and difficult to interpret. This paper demonstrates how big data — particularly Location-Based Social Network (LBSN) data — together with visualization and AI-supported interpretation systems, can provide new opportunities to understand the capacity of these large-scale architectural infrastructures to attract people, influence movement patterns throughout urban space, and generate economic and social impacts on the existing city.

Representation Across Boundaries: New Paradigms in the Age of AI and XR

The introduction and rapid expansion of new algorithms based on Machine Learning (ML) and Deep Learning (DL) processes to support knowledge and design activities has revolutionized multiple domains in recent years. Among these, research in the fields of Cultural Heritage, Design, and Architecture is fostering the development of new methodologies for study and content creation — partly supporting existing tools and partly replacing them entirely — while offering a new paradigmatic perspective on the impact of AI within these domains.

More specifically, the introduction of Generative AI (GenAI) and the creation of new forms of content within these fields open new possibilities for the understanding, analysis, design, and communication of architecture and design. At the same time, these developments highlight the limitations and risks associated with their uncritical use and raise important ethical questions. Human guidance and supervision in generative processes still remain — fortunately — a foundational component of these workflows, ensuring control over results while encouraging their implementation across different areas.

Through a concise review of current research in the field, the article provides an updated overview of recent international studies, while anticipating possible future developments concerning XR and AI in Cultural Heritage, Design, and Architecture.

A Method for Conscious Retrofitting Based on Handheld Laser Scanner and Environmental Data

The research behind this paper focuses on the connection between monitoring the environmental quality of a sample building and the corresponding digital model. The data obtained from the sample will be extended to a related typology of buildings, thus generating a method for conscious retrofitting of a large portion of the built environment. To conduct this study, a digital ecosystem comprising the model and a series of environmental sensors has been prepared. Within this digital environment, it is possible to visualize the data acquired from real-life sensors directly into the model. The digital twin method, in which there is a direct cause/effect correspondence between the real artifact and its digital alter ego, is foundational to this experimentation. Environmental data gathered from the building interacts with the digital model and returns to the physical reality as indicators. Once these indicators have been verified on the sample, they can be implemented in other related buildings. Sensors measuring temperature, pressure, humidity, and light radiation were concurrently applied to the building. The data flow is bidirectional, from the sensors to the model and vice versa. In the initial direction, the sensors transmit data to the digital model through a series of steps. The sensors communicate with a digital ecosystem. Once the procedure has been verified to work, it can be replicated easily, since open-source Arduino components were used for the sensor system. These components, besides being easy to find and economically viable, can be adapted and reproduced with extreme simplicity because, according to the Arduino philosophy, both the operating codes and the electronic production diagrams of the individual components are freely available.

Digital Twin and Artificial Intelligence: Matrix Automation for Design, Monitoring, and Management of Spaces

In recent years, the increasingly urgent challenge of designing community spaces characterized by the broadest inclusiveness has led to great excitement in the search for innovative methods that establish a strong interconnection between physical and digital reality. Building information models, the internet of things and artificial intelligence are explored as technological solutions to establish a design, monitoring, and management framework for the built environment. The different data domains converge and interact with each other through the digital twin paradigm. This research is focused on the methodological implementation of a system able to detect and collect real-time data from IoT devices on the fields (physical layer), process and organize them (data processing and storage layers), and expose and visualize them through web services and BIM models (application layer). The applications refer to (i) the improvement of thermal-hygrometric and visual comfort, also reducing energy consumption, (ii) the implementation of a detection system for the activation of security procedures, and (iii) the search for assets of interest within an environment. The experimentation is conducted through a real case study which refers to the refunctionalization of a building of historical interest through the design of a smart library.

Exploring Alternative Urban and Architectural Virtual Realities Through Multidomain Digital Twins

The paper explores the use of multidomain Digital Twins (DTs) integrated with Virtual Reality (VR), GIS data, photogrammetry, configurational analysis, and AI-related approaches to support urban and architectural design exploration in historical contexts. The research develops a low-cost workflow combining spherical photogrammetry, point clouds, GIS integration, Space Syntax analysis, VR visualization in Unity, and immersive interaction to test alternative architectural hypotheses within their urban environment. The study investigates how VR-enabled DTs can function not only as visualization tools but also as cognitive and analytical devices for historical interpretation, urban analysis, configurational assessment, and design decision-making. The paper also discusses the future integration of AI methods such as NeRFs, semantic enrichment, and generative architectural sampling to automate reconstruction and support culturally sustainable urban design workflows.

Digital Twin for BIM-FM Data Comparison: A Decision Support System Based on Graphical Interfaces

The paper investigates the integration of BIM, Digital Twin technologies, Extended Reality (XR), and graphical interfaces for facility management and maintenance support in complex buildings. The research proposes a methodological framework describing the evolution of BIM models from physical twins to as-built, as-is, record, and FM-oriented digital twin models. The study explores the use of desktop graphical interfaces, 360° photo comparison systems, augmented reality, and virtual reality applications to inspect, compare, update, and manage BIM-based information. The proposed workflow aims to improve decision support systems for maintenance operations, data reliability, and operational awareness in the AECO sector through interactive and immersive visualization environments.

Immersive Technologies for the Remote Fruition of an Inaccessible Archaeological Complex: The Site of Cento Camerelle in the Phlegraean Fields Archaeological Park

The paper presents the development of an integrated digital platform for the remote access, documentation, and dissemination of an inaccessible archaeological site. The methodology combines multi-source digital survey techniques—including UAV photogrammetry and terrestrial laser scanning—with 3D modeling and semantic data integration to generate accurate digital replicas of the site. These models are implemented within immersive environments (VR and WebXR), enabling virtual tours, interactive exploration, and data querying through user-friendly interfaces. The platform supports both scientific analysis and public engagement, integrating spatial data, annotations, and multimedia content into a scalable knowledge system. The research highlights the potential of immersive technologies to overcome physical accessibility constraints, while also supporting heritage conservation, monitoring, and valorisation through interoperable digital ecosystems.

BIM and Data Integration: A Workflow for the Implementation of Digital Twins

This paper presents a methodological and operational workflow for the implementation of Digital Twins (DT) in the construction sector through the integration of Building Information Modeling (BIM) and Internet of Things (IoT) systems. The research addresses the growing need for structured data management across the lifecycle of built assets, emphasizing the transition from static BIM models to dynamic, data-driven environments capable of supporting real-time monitoring and decision-making.

The proposed framework combines federated BIM models (in IFC format) with real-time sensor data collected from IoT devices, enabling the creation of a unified information system where geometric, semantic, and environmental data converge (Fig. 1, p. 826). The workflow is structured into six phases—creation, communication, aggregation, analysis, insight, and action—defining a progressive integration between physical assets and digital environments. Data collected from sensors (e.g. temperature and humidity) are processed through edge computing systems and integrated into the Snap4City platform, where they are visualized via dashboards and linked to BIM components (Figs. 6–7, pp. 831–832).

The results demonstrate that the integration of BIM and IoT enables the development of digital twins that support facility management, predictive maintenance, and performance monitoring. While artificial intelligence is identified as a future extension for data analytics and predictive evaluation, the current contribution focuses primarily on data integration, interoperability, and visualization. The study highlights both the potential and the limitations of current DT implementations, particularly regarding semantic interoperability and data standardization.

Documentation Procedures for Rescue Archaeology Through Information Systems and 3D Databases

This paper presents a methodological framework for the documentation, management, and interpretation of rescue archaeology data through integrated information systems and three-dimensional databases. The research addresses the critical challenge of preserving archaeological memory in contexts where excavation processes inherently lead to the destruction of physical evidence.

The proposed approach combines integrated survey techniques—including terrestrial laser scanning, photogrammetry, and UAV acquisition—with the development of a structured digital archive linking stratigraphic data, textual records, and 3D models. As illustrated in the workflow diagrams (Fig. 3–5, pp. 767–769), multi-temporal point clouds and photogrammetric models are aligned and processed to reconstruct excavation phases, enabling the visualization of stratigraphic evolution over time. A key contribution is the implementation of a three-dimensional GIS environment in which each stratigraphic unit is semantically defined and associated with database records through a one-to-one relationship, allowing query-based interaction and thematic visualization (Fig. 10, p. 775).

The system supports in situ data acquisition through digital forms and mobile devices, improving the efficiency and accuracy of documentation under time-constrained conditions. Results demonstrate that integrating 3D models with relational databases enhances data accessibility, interpretability, and long-term preservation, while enabling multi-scalar analysis from stratigraphic detail to urban context. The study concludes that three-dimensional information systems can act as dynamic repositories of archaeological knowledge, bridging survey data, archival records, and interpretative processes.