Virtual Counterparts Research Articles

Patent Spectrum of Human Digital Twins

Although no "absolute" definition exists, a human digital twin (HDT) may be defined as a virtual physiological copy or counterpart in digital world of a real person existing in the physical world having active connection between the human and his corresponding twin in metaverse. The current study aims to explore the intellectual property rights (IPR) challenges of HDTs. Previously discussions on HDT have mostly focused their potential use in health system for predictions of diseases nearly ignoring the patent associated with them. Current study highlights patent landscape analysis of HDT indicating current trends in HDT patents and future scenario of this technology.

Proxy re-encryption with plaintext checkable encryption for integrating digital twins into IIoT

Digital Twin (DT) technology has emerged as a robust mechanism for overseeing and improving the lifecycle processes of the Industrial Internet of Things (IIoT) by creating their virtual counterparts. The widespread employment of cloud computing is apparent in delivering computational and storage services for the DT within the IIoT environment. Ensuring the confidentiality of DT data is crucial since data owners, cloud service providers, and users operate across separate trust domains. Accordingly, public key encryption is a viable solution for managing access. However, traditional public key encryption encounters challenges in achieving effective search and secure sharing of encrypted DT data in the cloud. This paper introduces a proxy re-encryption scheme with plaintext checkable encryption for data access control (PRE-IBSC-PCE), which addresses the challenges associated with searching for and sharing encrypted digital twin data in the cloud. The PRE-IBSC-PCE achieves efficient data search and sharing while ensuring privacy, integrity, non-repudiation, and authenticity. Meanwhile, we prove that PRE-IBSC-PCE is secure under the decisional bilinear Diffie–Hellman assumption in the random oracle model. Lastly, when compared to similar schemes, the performance analysis of the PRE-IBSC-PCE is more efficient and suitable for DT applications in IIoT.

Mixed Reality Virtual Device (MRVD) for seamless MR-IoT-Digital Twin convergence

Mixed Reality (MR) extends Augmented Reality (AR) by emphasizing real-time interactions and providing a more immersive experience with the seamless integration of contextual elements, such as spaces, situations, objects, and user behaviors. MR creates new opportunities across fields, such as the Internet of Things (IoT) and Digital Twins (DT), and advancements in Artificial Intelligence (AI). However, integrating these technologies poses challenges for data synchronization, particularly for MR devices with limited computing resources. This study proposes a novel architectural concept, called the MR virtual Device (MRVD), to address the problem. MRVD serves as a virtual counterpart to the MR physical device (MRPD), optimizing computation and communication using container technologies to enhance availability, portability, and scalability. By handling resource-intensive tasks, MRVD boosts performance and consistency, thereby improving the effectiveness and efficiency of the MR-IoT-DT convergence. Our experiments demonstrate MRVD’s concrete benefits in overcoming these challenges, offering a promising approach for future convergence applications.

Transferable Virtual-Physical Environmental Alignment With Redirected Walking.

Several advanced redirected walking techniques have been proposed in recent years to improve natural walking in virtual environments. One active and important research challenge of redirected walking focuses on the alignment of virtual and physical environments by redirection gains. If both environments are aligned, physical objects appear at the same positions as their virtual counterparts. When a user arrives at such a virtual object, she can touch the corresponding physical object providing passive haptic feedback. When multiple transferable virtual or physical target positions exist, the alignment can exploit multiple options, but the process requires more complicated solutions. In this paper, we study the problem of virtual-physical environmental alignment at multiple transferable target positions, and introduce a novel reinforcement learning-based redirected walking method. We design a novel comprehensive reward function that dynamically determines virtual-physical target matching and updates virtual target weights for reward computation. We evaluate our method through various simulated experiments as well as real user tests. The results show that our method obtains less physical distance error for environmental alignment and requires fewer resets than state-of-the-art techniques.

Substitute Buttons: Exploring Tactile Perception of Physical Buttons for Use as Haptic Proxies

Buttons are everywhere and are one of the most common interaction elements in both physical and digital interfaces. While virtual buttons offer versatility, enhancing them with realistic haptic feedback is challenging. Achieving this requires a comprehensive understanding of the tactile perception of physical buttons and their transferability to virtual counterparts. This research investigates tactile perception concerning button attributes such as shape, size, and roundness and their potential generalization across diverse button types. In our study, participants interacted with each of the 36 buttons in our search space and provided a response to which one they thought they were touching. The findings were used to establish six substitute buttons capable of effectively emulating tactile experiences across various buttons. In a second study, these substitute buttons were validated against virtual buttons in VR. Highlighting the potential use of the substitute buttons as haptic proxies for applications such as encountered-type haptics.

Digital twin applications in an archaeological site: A virtual reconstruction of the Pishan site, Zhejiang, China

A digital twin is a virtual counterpart of a physical object or system based on precise data collection. Although digital twin applications are gaining traction in the virtual reconstruction of built heritage, their relevance in archaeological sites remains limited, especially for those with only foundations. The Pishan (毘山) site in Huzhou, featuring the remains of a high-platform building and a large stilt-style architecture, represents the largest settlement site from the late Shang (商, ca. 1600 – 1046 BCE) and early Western Zhou (西周, 1046 – 771 BCE) dynasties in Zhejiang Province, China. At present, confronting contradictions among preservation, restoration, and reuse as a heritage park, the site leverages digital twin technologies to address two concerns: (i) reconstructing a 3D scene for further restoration and related studies and (ii) integrating multimedia to enhance visitors’ experiences and dissemination. Photogrammetry, unmanned aerial vehicle, and a mirrorless camera are employed to collect sky and ground dual graphic data and reconstruct the 3D model of the loess terrace. A panoramic roaming environment is created through panoramic photography. Geographic information system is integrated to enable visual analysis and information management while building information modeling facilitates the integration of parametric modeling and point cloud, aiding virtual restoration research. In conclusion, a workflow entitled “Virtual Reconstruction – Management and Analysis – Restoration – Exhibition” is proposed, promising in-depth exploration in further studies.

A Digital Twin Platform Integrating Process Parameter Simulation Solution for Intelligent Manufacturing

The present work aims to develop a digital twin system typical of intelligent manufacturing applications, which has integrated visualization technologies, as well as the process parameter simulation solution. The application under consideration is a typical machining process, with a gantry machine tool controlled by Siemens Programmable Logic Controller(PLC) S7-1200. With the establishment of dual-directional data communication between the physical machine tool and its virtual counterpart based on TCP/IP protocol, real-time visualization, monitoring, and control of the entire working process can be achieved. Furthermore, we integrated with the digital twin system as a solution for real-time process parameter simulation based on finite element modeling (FEM), which enables the real-time monitoring of necessary process parameters, e.g., surface deformation, during the machining process. A preliminary experiment was conducted to validate our proposed digital twin system, and the results demonstrated that our proposed method has satisfactory performance in terms of both control and monitoring of the traditional machining process, and synchronization between the physical and virtual models is also proven to be positive with minimal latency.

In Case of Doubt, One Follows One's Self: The Implicit Guidance of the Embodied Self-Avatar.

The sense of embodiment in virtual reality (VR) is commonly understood as the subjective experience that one's physical body is substituted by a virtual counterpart, and is typically achieved when the avatar's body, seen from a first-person view, moves like one's physical body. Embodiment can also be experienced in other circumstances (e.g., in third-person view) or with imprecise or distorted visuo-motor coupling. It was moreover observed, in various cases of small or progressive temporal and spatial manipulations of avatars' movements, that participants may spontaneously follow the movement shown by the avatar. The present work investigates whether, in some specific contexts, participants would follow what their avatar does even when large movement discrepancies occur, thereby extending the scope of understanding of the self-avatar follower effect beyond subtle changes of motion or speed manipulations. We conducted an experimental study in which we introduced uncertainty about which movement to perform at specific times and analyzed participants' movements and subjective feedback after their avatar showed them an incorrect movement. Results show that, when in doubt, participants were influenced by their avatar's movements, leading them to perform that particular error twice more often than normal. Importantly, results of the embodiment score indicate that participants experienced a dissociation with their avatar at those times. Overall, these observations not only demonstrate the possibility of provoking situations in which participants follow the guidance of their avatar for large motor distortions, despite their awareness about the avatar movement disruption and on the possible influence it had on their choice, and, importantly, exemplify how the cognitive mechanism of embodiment is deeply rooted in the necessity of having a body.

Physiology-Informed Deep Learning Modeling of Type 1 Diabetes Dynamics: Mapping Data to Virtual Subjects

We consider the problem of creating Digital Twins (DTs) of glucose metabolism in people with Type 1 Diabetes (T1D), coupling a large-scale mean population metabolic model of glucose dynamics developed from first principles, with deep learning (DL) architectures, to map actual patient data to their virtual counterparts. For the neural network component of our proposed strategy, two models were investigated: a Long Short-Term Memory (LSTM) network and a Generative Adversarial Network (GAN). Our best model outperformed significantly the mean population model with respect to evaluation metrics (LSTM vs. metabolic simulator), expressed as median (interquartile range): MAE 35.0 (28.8, 43.8) vs. 79.7 (62.4, 115.5) [mg/dL], RMSE 44.8 (37.2, 56.2) vs. 94.9 (76.3, 128.0) [mg/dL], eNRMSE 0.85 (0.83, 0.88) vs. 0.54 (0.48, 0.72), eFIT 0.25 (0.13, 0.40) vs. 0.00 (0.00, 0.00). We showed that the proposed physiology-informed deep learning approach successfully mapped real patient data to virtual subjects, with the potential to enable in-silico testing of novel therapeutic strategies on a virtual population.

Virtual voices for real change: The efficacy of virtual humans in pro-environmental social marketing for mitigating misinformation about climate change

Academics have focused their research on the rise of non-human entities, particularly virtual humans. To assess the effectiveness of virtual humans in influencing individual behavior through campaigns, we conducted two separate online experiments involving different participant groups: university students (N = 167) and U.S. adults (N = 320). We compared individuals’ responses to video-type pro-environmental campaigns featuring a virtual or actual human scientist as the central figure who provides testimonials about their individual efforts to prevent misinformation about climate change. The results indicate that an actual human protagonist evoked a stronger sense of identification compared to a virtual human counterpart. Nevertheless, we also observed that virtual humans can evoke empathy for the characters, leading individuals to perceive them as living entities who can have emotions. The insights gleaned from this study have the potential to shape the creation of virtual human content in various domains, including pro-social campaigns and marketing communications.

IoT-digital twin-inspired smart irrigation approach for optimal water utilization

Agriculture industry faces the challenge of increasing productivity by 50% from 2012 to 2050 while reducing water usage, given that it currently consumes 69% of the world’s freshwater. To achieve this goal, smart technologies such as Artificial Intelligence (AI), Digital Twins (DT), and Internet of Things (IoT) are being increasingly utilized. However, the use of DT in agriculture is still in its early stages. This study proposes a smart irrigation framework inspired by digital twins in an application domain. The irrigation framework’s sensors and actuators are linked to their virtual counterparts to create a digital twin. The IoT platform collects, aggregates, and processes data to determine daily irrigation requirements, and the behavior of the irrigation system is simulated. The proposed framework has two main advantages: evaluating the behavior of the digital twin and IoT platform in the context of agriculture before integrating them into the field and comparing various irrigation methods with current farming methods. By providing farmers with information about soil, weather, and crops, the system has the potential to improve farm operations and reduce water consumption.

Agile digital machine development

In mechatronic machine design and development, it is no longer enough to think about machine functionality and integration as machines are increasingly digitalized. Virtual upgrades are being made to manufacturing systems to keep up with the need for faster product cycles, higher quality, and the introduction of Industry 4.0 technologies. The design and development of new mechatronic discrete manufacturing machines (MDMM) should thus include these characteristics in their design. However, most machine builders do not have the capabilities and resources to do virtual engineering (VE) at the required level, which means these machines are made with limitations or sometimes without their virtual counterparts. Reusable VE MDMM modularization allows machine builders to obtain these competencies quickly and with fewer resources. This research proposes developing adaptable digital twins (DT) by modularizing all virtual and physical mechatronic machine aspects. DTs are well-explored in literature, but re-engineering them requires massive resources and is often unviable. We introduce a new DT-based approach that allows machine builders to quickly re-engineer, adapt, and test machines, given its modular confined approach. Although VE on different abstraction levels still must be developed, confined modularization allows hiding the complexity into modules rather than addressing the entire machine simultaneously. Building machines through modularization is thus an investment, as machine builders and other stakeholders will be able to use and reuse them later for other machines, reducing the overall resources that go into the development. The paper shows how to develop adaptable DT machines using Siemens tools related to virtual engineering.

Meta-model-based shop-floor digital twin architecture, modeling and application

Digital twin is regarded as the virtual counterpart of physical entities, which can mirror the physical behavior and performance. Digital twin technology provides strong support for the achievement of cyber-physical system and intelligent manufacturing. Many investigations have been carried out for the digital twin of specific products. However, there are less researches on digital twin in the shop-floor domain, and there is a lack of model-driven digital twin comprehensive architecture. The modeling approach to the full lifecycle of digital twin is not considered enough. This paper proposes a meta-model-based shop-floor digital twin construction approach and a comprehensive architecture. A meta-model based on RAMI 4.0 is constructed, which provide a novel idea for the description of manufacturing resources and their status. The proposed shop-floor digital twin architecture consists of three key implementation elements: the meta-model construction, data modeling (including data interaction between cyber-physical spaces) and constructing different integration level models of shop-floor digital twin based on iteration feedback between the demands and models. The proposed approach is validated through a case study of the fischer learning factory 4.0.

Rethinking The Proteus Effect – Can our digital personas influence our offline selves?

This paper seeks to clarify the notable phenomena known as the Proteus effect. This phenomena clarifies the ability of avatar characteristics within digital gaming environments to have a noticeable impact on people’s actions in the real world. The research question that informs the conceptual framework put forward in this academic discourse is the following: if the Proteus effect is clearly perceptible among members of online gaming communities, might it not possibly also apply to users of social networking platforms? The study will use an example from the science fiction anthology series “Black Mirror” to explain and support this theoretical claim. It is hypothesised that once people create a social media presence, they start creating a digital identity or “avatar”, the development of which has the potential to have a substantial impact on their behaviour in real life. The Proteus effect’s plausible expansion outside of the online gaming industry, where it was first documented, is the main hypothesis that this paper seeks to clarify through the use of a hypothetical scenario taken from modern cinematic narratives. This article’s hypothesis imagines a future in which people eventually become like their digital avatars, leading to a time when real people resemble their virtual counterparts.

Digital Twins in Healthcare: Methodological Challenges and Opportunities.

One of the most promising advancements in healthcare is the application of digital twin technology, offering valuable applications in monitoring, diagnosis, and development of treatment strategies tailored to individual patients. Furthermore, digital twins could also be helpful in finding novel treatment targets and predicting the effects of drugs and other chemical substances in development. In this review article, we consider digital twins as virtual counterparts of real human patients. The primary aim of this narrative review is to give an in-depth look into the various data sources and methodologies that contribute to the construction of digital twins across several healthcare domains. Each data source, including blood glucose levels, heart MRI and CT scans, cardiac electrophysiology, written reports, and multi-omics data, comes with different challenges regarding standardization, integration, and interpretation. We showcase how various datasets and methods are used to overcome these obstacles and generate a digital twin. While digital twin technology has seen significant progress, there are still hurdles in the way to achieving a fully comprehensive patient digital twin. Developments in non-invasive and high-throughput data collection, as well as advancements in modeling and computational power will be crucial to improve digital twin systems. We discuss a few critical developments in light of the current state of digital twin technology. Despite challenges, digital twin research holds great promise for personalized patient care and has the potential to shape the future of healthcare innovation.

Digital Twin for Acoustics and Stage Craft Facility Management in a Multipurpose Hall

Digital twins aim to virtually replicate the static and dynamic building characteristics through real-time connectivity between virtual and physical counterparts. Despite its potential, research into digital twins for facility management (FM) in multipurpose spaces is at an early stage, especially to control and optimize the various uses and configuration layouts. One of the major barriers to the adoption of digital twin technology in multipurpose buildings is the lack of interoperability, primarily between building information modeling (BIM) and Internet of things (IoT) data sources. This paper presents a possible digital-twin architecture to enable digital-twin applications aiming to impact building performance, acting on the facility management of stagecraft and variable acoustic architectural elements to control the reverberation time in real time. The case study of Roberto De Silva Multipurpose Hall is presented, in which the indoor acoustic quality is controlled by the digital twin that returns the reverberation time output as a function of stage equipment layouts, variable acoustic elements and hall occupancy.

Digital twins for internal combustion engines: A brief review

The adoption of digital twin technology in the realm of internal combustion (IC) engines has been attracting a lot of interest. This review article offers a comprehensive summary of digital twin applications and effects in the IC engine arena. Digital twins, which are virtual counterparts of real-world engines, allow for real-time monitoring, diagnostics, and predictive modeling, resulting in improved design, development, and operating efficiency. This abstract digs into the creation of a full virtual depiction of IC engines using data-driven models, physics-based simulations, and IoT sensor data. The study looks at how digital twins can potentially be used throughout the engine's lifespan, including design validation, performance optimization, and condition-based maintenance. This paper emphasizes the critical role of digital twins in revolutionizing IC engine operations, resulting in enhanced reliability, decreased downtime, and enhanced emissions control through a methodical analysis of significant case studies and innovations.

Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review.

Digital Twins serve as virtual counterparts, replicating the characteristics and functionalities of tangible objects, processes, or systems within the digital space, leveraging their capability to simulate and forecast real-world behavior. They have found valuable applications in smart farming, facilitating a comprehensive virtual replica of a farm that encompasses vital aspects such as crop cultivation, soil composition, and prevailing weather conditions. By amalgamating data from diverse sources, including soil, plants condition, environmental sensor networks, meteorological predictions, and high-resolution UAV and Satellite imagery, farmers gain access to dynamic and up-to-date visualization of their agricultural domains empowering them to make well-informed and timely choices concerning critical aspects like efficient irrigation plans, optimal fertilization methods, and effective pest management strategies, enhancing overall farm productivity and sustainability. This research paper aims to present a comprehensive overview of the contemporary state of research on digital twins in smart farming, including crop modelling, precision agriculture, and associated technologies, while exploring their potential applications and their impact on agricultural practices, addressing the challenges and limitations such as data privacy concerns, the need for high-quality data for accurate simulations and predictions, and the complexity of integrating multiple data sources. Lastly, the paper explores the prospects of digital twins in agriculture, highlighting potential avenues for future research and advancement in this domain.

Self-Evolving and Transformative Protocol Architecture for 6G

The fusion of digital and real worlds in all dimensions will be the driving force for future sixthgeneration (6G) wireless systems. Ubiquitous in-time and on-time communication services between humans, machines, robots, and their virtual counterparts are essential, and they expand from the ground to air, space, underground, and deep sea. 6G systems are not only data pipelines but also large-scale distributed computing systems with integrated sensing, processing, storage, communication and computing capabilities. It is challenging to build ubiquitous and intelligent 6G systems, handling stringent quality-of-service (QoS) requirements, providing a rich set of communication modes, including unicast, multicast, broadcast, in-cast, and group-cast, and supporting user-centric mobile applications. In this article, we propose a new protocol architecture, Self-Evolving and Transformative (SET) architecture that can provide a wide range of control functions, and be intelligently configured for different types of 6G applications and networking environments. Its design principles, potentials, and open issues are discussed.

NFV-empowered digital twin cyber platform: Architecture, prototype, and a use case

Building, managing, upgrading, and diagnosing networks becomes increasingly difficult due to the increased complexity in protocol design, enlarged network scale, rapidly-growing types of network applications, and the uncertainty of network faults and cyber attacks. It is not satisfactory to rely on network simulators/emulators for conducting these tasks because of different defects including poor fidelity, long implementing time, and weak interconnection with physical networks. To enable the interplay of networks and their virtual counterparts, this paper aims to build a Network Functions Virtualization (NFV)-empowered digital twin cyber platform (DTCP) for enabling network innovation and test with high fidelity, low complexity, and high timeliness. First, after regulating the paradigm of DTCP, a six-dimensional model is defined to profile a DTCP. Second, the architecture of the DTCP is detailed along with the key enabling technologies. Third, a prototype implementation of the DTCP is shortly introduced. Lastly, a use case based on fault diagnosis for video conference system is tested on the prototype. Results show that our DTCP prototype is a good platform for conducting different types of network operations without explicitly providing the mapping model between physical and virtual networks.