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Pages 95-98

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From page 95...
... With growing utilization of augmented reality and virtual reality, the collection of human interactions in the digital space will continue to increase and serve as a source of data for human–digital twin interactions. The data gathered within these interactions can also inform what and how future data capture is integrated into the digital twin (e.g., timing of assessments or measurements, introduction of new biosensors for humans interacting with digital twins)
From page 96...
... Conclusion 6-3: While the capture of enough contextual detail in the meta data is critical for ensuring appropriate inference and interoperability, the inclusion of increasing details may pose emerging privacy and security risks. This aggregation of potentially sensitive and personalized data and models is particularly challenging for digital twins.
From page 97...
... TABLE 6-1  Key Gaps, Needs, and Opportunities for Enabling the Feedback Flow from the Virtual Representation to the Physical Counterpart of a Digital Twin Maturity Priority Early and Preliminary Stages  Scalable methods are needed for goal-oriented sensor steering and optimal 1  experimental design that encompass the full sense–assimilate–predict–control–steer cycle while accounting for uncertainty.  Trusted machine learning and surrogate models that meet the computational and 1 temporal requirements for digital twin real-time decision-making are needed.  Scalable methods to achieve dynamic adaptation in digital twin decision-making 2 are needed.  Theory and methods to achieve trusted decisions and quantified uncertainty for 1 data-centric digital twins employing empirical and hybrid models are needed.  Methods and tools to make sensitivity information more readily available for 1 model-centric digital twins, including automatic differentiation capabilities that will be successful for multiphysics, multiscale, multi-code digital twin virtual representations, are needed.  Research on and development of implementation science around digital twins, 1 user-centered design of digital twins, and adaptations of human behavior that enable effective human–digital twin teaming are needed. Certain domains and sectors have had more success, such as in the Department of Defense.  Uncertainty visualization is key to ensuring that uncertainties are appropriately 2 considered in the human–digital twin interaction and resulting decisions, but development of effective approaches for presenting uncertainty remains a gap.
From page 98...
... 2023. "Risk-Adaptive Decision-making and Learning." Presentation to the Committee on Foundational Research Gaps and Future Directions for Digital Twins.

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