Human digital twin: structure, classes of tasks, and approaches to solving them

This article examines the concept of a human digital twin, a virtual model simulating the physical, biological, and cognitive characteristics of a real person. It focuses on analyzing the sources and types of data required to create the twin, as well as discussing its architecture and defining task classes for it. А human digital twin occupies a central place in the overall system of digital technologies, integrating the capabilities of Big Data, IoT, artificial intelligence, blockchain, augmented and virtual reality, cloud and edge computing. This allows the twin to become a key link and control center in the digital ecosystem. The article also examines the ethical issues associated with creating a human digital twin, including privacy and data security. It is noted that the twin can be used to predict human behavior and manage their state, which opens up new opportunities but also carries certain risks. The differences between a human digital twin and a machine digital twin are highlighted, stating that the human twin is a more complex system, requiring an interdisciplinary approach and consideration of multiple factors, such as genetics, biography, and psychophysiological characteristics. А multi-level architecture for a human digital twin is proposed, enabling the efficient design of data collection and integration processes, data processing, and the interaction of services and applications to support decision-making. The classes of problems that can be solved using a human digital twin and approaches to addressing them are also discussed.