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Traditional risk assessments rely on manual audits and system scans, often causing operational disruptions and leaving security gaps. To address these challenges, this work presents Security Digital Twin-as-a-Service (SDT-aaS), a novel…
The concept of Digital Twin (DT) is increasingly applied to systems on different levels of abstraction across domains, to support monitoring, analysis, diagnosis, decision making and automated control. Whilst the interest in applying DT is…
Digital twinning in structural engineering is a rapidly evolving technology that aims to eliminate the gap between physical systems and their digital models through real-time sensing, visualization, and control techniques. Although Digital…
In Industry 4.0, the digital twin is one of the emerging technologies, offering simulation abilities to predict, refine, and interpret conditions and operations, where it is crucial to emphasize a heightened concentration on the associated…
Intelligent intersections play a pivotal role in urban mobility, demanding innovative solutions such as digital twins to enhance safety and efficiency. This literature review investigates the integration and application of digital twins for…
Digital twinning of vehicles is an iconic application of digital twins, as the concept of twinning dates back to the twinning of NASA space vehicles. Although digital twins (DTs) in the automotive industry have been recognized for their…
Although digital twins have recently emerged as a clear alternative for reliable asset representations, most of the solutions and tools available for the development of digital twins are tailored to specific environments. Furthermore,…
The digital twin concept represents an appealing opportunity to advance condition-based and predictive maintenance paradigms for civil engineering systems, thus allowing reduced lifecycle costs, increased system safety, and increased system…
The potential of digital twin technology is yet to be fully realized due to its diversity and untapped potential. Digital twins enable systems' analysis, design, optimization, and evolution to be performed digitally or in conjunction with a…
Industrial processes rely on sensory data for decision-making processes, risk assessment, and performance evaluation. Extracting actionable insights from the collected data calls for an infrastructure that can ensure the dissemination of…
Digital twins are transforming engineering and applied sciences by enabling real-time monitoring, simulation, and predictive analysis of physical systems and processes. However, conventional digital twins rely primarily on passive data…
With the increasing complexity of industrial systems, there is a pressing need for predictive maintenance to avoid costly downtime and disastrous outcomes that could be life-threatening in certain domains. With the growing popularity of the…
The increased use of software in the operation and management of telecommunication networks has moved the industry one step closer to realizing autonomous network operation. One consequence of this shift is the significantly increased need…
Modeling and simulation of autonomous vehicles plays a crucial role in achieving enterprise-scale realization that aligns with technical, business and regulatory requirements. Contemporary trends in digital lifecycle treatment have proven…
Over the recent years, the protection of the so-called `soft-targets', i.e. locations easily accessible by the general public with relatively low, though, security measures, has emerged as a rather challenging and increasingly important…
Digital twins are sophisticated software systems for the representation, monitoring, and control of cyber-physical systems, including automotive, avionics, smart manufacturing, and many more. Existing definitions and reference models of…
Digital Twins (DT) are essentially dynamic data-driven models that serve as real-time symbiotic "virtual replicas" of real-world systems. DT can leverage fundamentals of Dynamic Data-Driven Applications Systems (DDDAS) bidirectional…
Digital Twins (DTs) are virtual representations of physical systems synchronized in real time through Internet of Things (IoT) sensors and computational models. In industrial applications, DTs enable predictive maintenance, fault diagnosis,…
Multi-robot systems face challenges in reducing human interventions as they are often deployed in dangerous environments. It is therefore necessary to include a methodology to assess robot failure rates to reduce the requirement for costly…
Digital twin (DT) technologies have emerged as a solution for real-time data-driven modeling of cyber physical systems (CPS) using the vast amount of data available by Internet of Things (IoT) networks. In this position paper, we elucidate…