The research subject of the article is modern intellectualization methods for wireless sensor networks (WSN). Typically, their application field is uncertain and poorly formalized environments, therefore, it is possible to achieve the desired efficiency of such complexes mainly by improving the intellectual component of their control system as a whole and a separate node in particular. However, it should be noted that there is a gap between primitive behavioral models of artificial entities, for example, in swarm robotics, their interaction models and expectations from practice. The situation is aggravated by the requirements of secrecy, miniaturization, and low power consumption. In practice, it is required that a network node to be an autonomous node with the property of intelligent behavior, which also has to be able to learn the situation and make decisions, both independently taking into account the data received from other network devices and as part of a group.

The paper identifies the main requirements for the autonomous operation of an intelligent WSN. The highlighted key factors are low energy consumption and the exchange of reliable information about the environmental state to form right decisions. The purpose of the paper is to form a theoretical and mathematical base from the existing methods of WSN intellectualization that meet the above requirements, as well as to formulate proposals for further research in order to be applied in practice.