The article deals with technologies that work with the Internet of things, and their implementation in various industries. The Internet of Things is considered as a higher level automation, therefore, it becomes possible to make automated complex logical decisions related to the choice of the structure of the process and operations, the assignment of technological bases and other similar tasks. A model based on a universal primitive called Actor for concurrent and distributed computing is considered. Covered issues of implementing an agent-based approach for applications of the Internet of things. The necessary condition for the implementation of the IoT model has been established; this is the possibility of scalability and the availability of fault tolerance configuration. To meet the real need for scalability, as well as fault tolerance, Akka provides comprehensive functions in routing, clustering, edging, and retaining agents. The use of the Akka framework for agent implementation has been analyzed.

Keywords: automation, management, technology, analysis, Internet of things, agent, primitive, implementation, toolkit, scalability, Akka, IoT

Since users can have very different preferences, the personalization of surrounding devices is of paramount importance. Several approaches have been proposed for establishing such personalization in the form of machine learning or more specialized approaches to learning based on scientific knowledge and innovations. Despite great advances in optimization, evolutionary algorithms in this context have been little studied, mainly because they are known as elements that are slow to learn. Anyway, at present there are quite fast optimizers based on evolutionary algorithms. In this article, an analysis is made of the suitability of evolutionary algorithms for "ambient intelligence".

Keywords: ambient intelligence, evolutionary algorithms, personalization, optimizer, CMA-ES, user, controller, machine Learning, sensor