The Human Digital Twin (HDT)


Digital Life and Human Wellbeing

The Human Digital Twin (HDT) is an AI-based mobile application which helps its user to manage, optimize and automate their digital interactions according to their preferences and interests, thus enabling them to manage their lives in a balanced and healthy manner. 

The AI scenarios we envision show how the HDT can help their users to manage and automate various digital interactions simultaneously and thus enable them achieving their goals in an effective and balanced manner.

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Automating Digital Interactions and Choices

The HDT takes care of many of its users' digital decisions, giving them more time and focus to spend on creative and social activities.

The HDT provides the same features of the more general agent, the Information Digital Twin (IDT), which we use to enable various types of digital twins for industrial and commercial use cases. 

Ensuring Users Long-Term Interests

In its most advanced form, the Human Digital Twin (HDT) provides its users with best-action recommendations (for example, regarding health-related choices) to ensure they preserve their long-term interests in the face of a rapidly changing and complex world.

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HDT Short Survey

As with many new technologies, the potential and impact of the Human Digital Twin (HDT) are yet to be seen. We believe, however, that digital twins of humans-in the form of our HDT or other similar technologies-will sooner or later become a common, everyday technology, just like aero planes, or mobile phones.

The HDT survey, and its results should provide an indication of how people interested in the HDT technology also see the potential, impact, and also the time line for maturing the HDT technology. 

Current Human Digital Twin (HDT) Use Cases 

We are developing the HDT in two use cases: Patients-HDT, which assists neonatology ICU patients, and Children-HDT (the TwinUp app), which assures children's safety and minimizes their risk of abuse. Both use cases focus on children because we believe modeling and forecasting risks for children are more achievable due to their less complex nature and behavior. 

Different aspects of the architecture and use of the HDT are discussed in multiple research papers.