Ambient Intelligence System (AmIS) can be constructed using data collected from Internet of Things (IoT). In this paper, the IoT data collection problem is studied for AmIS with dynamic structure and dynamic behavior of participants (devices), where constraints on resources consumption and performance are essential. A novel technology is proposed, which includes the following steps: (1) definition of the data collection (DC) problem (considering the model of the observed system, DC conditions, etc.); (2) DC policy assignment; (3) construction of DC models; (4) evaluation and presentation of the data processing results. The proposed DC technology supports the development of data collecting subsystems in AmIS. Such subsystems provide data that reflect the changes in structure, state, situation, and behavior of participants in their IoT environment in time. Therefore, we show how this “cognitive” function of the DC process increases the intelligence level of IoT environment.

The modern stage of technology development is characterized by the emergence of new paradigms for the construction of anthropogenic systems, such as cyber-physical systems, socio-cybernetic systems, etc. The task of data acquisition about the state of a multi-level system and managing the structure and behavior of a system consisting of many thousands of elements of different physical nature is a complex task. This article describes one of possible approaches to solving the problem of data acquisition and management of the structure of a large-scale heterogeneous system. The proposed approach is based on the idea of using dynamic digital twins, which are dynamic models of the observed system. This approach was used for the development of systems in various subject domains, in particular, in production management systems built on the Industry 4.0 principle, in the development of a technical support system for cable television networks and in the development of support systems for the construction of educational trajectories.

A model-based approach to large-scale distributed system architecting is suggested, which is based on the use of dynamic digital twins. This approach can be considered as an integration of known paradigms, such as digital twins, evolutionary architecture and agile architecture. It can also be considered as one of the possible realizations of the digital thread paradigm. As part of this approach, a three-level digital thread reference architecture is suggested, which includes the following levels: (i) digital thread support level; (ii) agile architecture support level; (iii) digital shadow support level. This approach has been used in the development of a number of real systems, and has shown its effectiveness in supporting system agility at the exploitation and modernization stages. The proposed approach is focused on building digital twin-based systems. This article may be interesting for specialists engaged in research and development in the domain of IoT- and IIoT-based information systems, primarily architects.