Enhancing Cognition for Digital Twins

Eirinakis, Pavlos; Kalaboukas, Kostas; Lounis, Stavros; Mourtos, Ioannis; Rožanec, Jože M.; Stojanović, Nenad; Zois, Georgios

doi:10.1109/ice/itmc49519.2020.9198492

Cited by 37 publications

(25 citation statements)

References 24 publications

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“…Virtualization is a dynamic design-time process involving computational approaches to model the physical feature, evolving into the complex, run-time process that allows the digital counterpart's behavioral model to be constantly adjusted to mirror the physical element's actions, resulting in the CDT. The CDT is a DT with cognitive abilities, including detecting anomaly and behavioral learning, and the power to determine physical twin actions to improve measures defining its state or function [46]. Therefore, a CDT uses optimization approaches to aid decision-making and data from the physical twin analyzed using analytics or ML.…”

Section: Cognitive Digital Twins (Cdt)mentioning

confidence: 99%

“…To put it another way, the CDT is envisioned as a robust monitoring and control mechanism and an essential part of the decision-making action that leads to system optimization. Using optimization techniques inside the heart of the cognitive twin and its impact is the primary crucial differentiating point instead of currently available DT solutions [46]. To make the transition from physical assets in the form of digital replicas to cognitive advancement, Abburu et al [6] used a three-layer structure to describe the types of twins needed: digital, hybrid, and cognitive.…”

Section: Cognitive Digital Twins (Cdt)mentioning

confidence: 99%

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An Adapted Model of Cognitive Digital Twins for Building Lifecycle Management

et al. 2021

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In the digital transformation era in the Architecture, Engineering, and Construction (AEC) industry, Cognitive Digital Twins (CDT) are introduced as part of the next level of process automation and control towards Construction 4.0. CDT incorporates cognitive abilities to detect complex and unpredictable actions and reason about dynamic process optimization strategies to support decision-making in building lifecycle management (BLM). Nevertheless, there is a lack of understanding of the real impact of CDT integration, Machine Learning (ML), Cyber-Physical Systems (CPS), Big Data, Artificial Intelligence (AI), and Internet of Things (IoT), all connected to self-learning hybrid models with proactive cognitive capabilities for different phases of the building asset lifecycle. This study investigates the applicability, interoperability, and integrability of an adapted model of CDT for BLM to identify and close this gap. Surveys of industry experts were performed focusing on life cycle-centric applicability, interoperability, and the CDT model’s integration in practice besides decision support capabilities and AEC industry insights. The evaluation of the adapted model of CDT model support approaching the development of CDT for process optimization and decision-making purposes, as well as integrability enablers confirms progression towards Construction 4.0.

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Section: Cognitive Digital Twins (Cdt)mentioning

confidence: 99%

Section: Cognitive Digital Twins (Cdt)mentioning

confidence: 99%

An Adapted Model of Cognitive Digital Twins for Building Lifecycle Management

et al. 2021

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“…In the context of FACTLOG, an EU SPIRE 2019 innovation action project, the concept of CDT is being developed and demonstrated [19]. The CDT model goes further on the road to Cognitive Manufacturing by developing a cognitive DT that not only uses cognition to adapt to changes by reacting to already known problems, but also to detect and respond to conditions and events that cannot be analytically modelled beforehand, having not been detected in past data of the system.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Cognitive Digital Twins in Connected and Agile Supply Networks – an Operational model

Kalaboukas¹,

Rožanec²,

Košmerlj³

et al. 2021

Preprint

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Supply chain agility and resilience are key factors for the success of manufacturing companies in their attempt to respond to dynamic changes. Circular economy, the need for optimized material flows, ad-hoc responses and personalization are some of the trends that require supply chains to become “cognitive”, i.e. able to predict trends and flexible enough in dynamic environments, ensuring optimized operational performance. Digital Twins (DTs) is a promising technology, and a lot of work is done on the factory level. In this paper, the concept of Cognitive Digital Twins (CDTs) and how they can be deployed in connected and agile supply chains is elaborated. The need for CDTs in the supply chain as well as the main CDT enablers and how they can be deployed under an operational model in agile networks is described. Emphasis is given on the modelling, cognition and governance aspects as well as on how a supply chain can be configured as a network of connected CDTs. Finally, a deployment methodology of the developed model into an example of a circular supply chain is proposed.

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“…Digital Twins are computational models of physical systems, including humans. The DT market is rapidly growing at a compound annual rate of 45.4% [7]. Notably, massive DT projects such as the British National Digital Twin [8] are being built.…”

Section: Introductionmentioning

confidence: 99%

Cybonto: Towards Human Cognitive Digital Twins for Cybersecurity

Nguyen¹

2021

Preprint

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Cyber defense is reactive and slow. On average, the time-to-remedy is hundreds of times larger than the time-to-compromise. In response to the expanding ever-more-complex threat landscape, Digital Twins (DTs) and particularly Human Digital Twins (HDTs) offer the capability of running massive simulations across multiple knowledge domains. Simulated results may offer insights into adversaries' behaviors and tactics, resulting in better proactive cyber-defense strategies. For the first time, this paper solidifies the vision of DTs and HDTs for cybersecurity via the Cybonto conceptual framework proposal. The paper also contributes the Cybonto ontology, formally documenting 108 constructs and thousands of cognitive-related paths based on 20 time-tested psychology theories. Finally, the paper applied 20 network centrality algorithms in analyzing the 108 constructs. The identified top 10 constructs call for extensions of current digital cognitive architectures in preparation for the DT future.

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Enhancing Cognition for Digital Twins

Cited by 37 publications

References 24 publications

An Adapted Model of Cognitive Digital Twins for Building Lifecycle Management

An Adapted Model of Cognitive Digital Twins for Building Lifecycle Management

Implementation of Cognitive Digital Twins in Connected and Agile Supply Networks – an Operational model

Cybonto: Towards Human Cognitive Digital Twins for Cybersecurity

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