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Due to the widespread use of sensors and sensor networks in the tasks of territory coverage, the relevant criteria are maximizing coverage and minimizing energy consumption. At the same time, the compliance of the network with these criteria is an urgent problem in the modern technological world. A modification of the method for constructing energy-efficient sensor networks is proposed by introducing an additional criterion for minimizing the number of sensors and limiting the number of sensors used, which allows reducing the energy consumption of sensor networks by 19 %. In the resulting optimization problem, the optimality criteria are the functions of minimizing the area of uncovered territory, the value of energy consumption, and the number of sensors. The optimum solution is formed by pairs of values of the coverage radius and the level of intersection of the coverage areas, which provide maximum coverage while minimizing energy consumption and the number of sensors used. To solve the problem, the parameter convolution method and the genetic algorithm were used. In the case of dynamic sensors, the problem is to find such a trajectory of the sensor that provides the maximum flyby of the territory with a minimum length. A grid algorithm is proposed to find the necessary trajectory. The presented algorithm consists in dividing the territory into nodes and estimating the value of the covered territory by the sensor in this node. After the formation of estimates, the search for a Hamiltonian path was used. The case of a multiply connected territory with the possibility of turning it into a simply connected one is considered. A scheme for finding the parameters of energy-efficient coverage of the territory using static and dynamic sensors is proposed.

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Thanks to the rapid development of technologies, in particular information, sensors have become widespread and used in all areas of human activity. Sensors and sensor networks have received special use during the collection and processing of data of various types. When monitoring a certain territory, the problem arises of its maximum coverage in order to increase the information content and completeness of the accumulated data. Simultaneously with the predominance of autonomous use of sensors, the problem of the duration of the sensor operation arises. This value depends on the capacity of the battery. In turn, engineers are faced with the task of minimizing the design of the sensors, which results in a decrease in the volume of the battery simultaneously with all other components. It is also obvious that as the sensor coverage radius increases, the energy consumption increases, which in turn shortens the sensor life. In addition to energy costs, the article considers the costs of servicing and purchasing sensors. Thus, in addition to maximizing the percentage of coverage of the study area, the problem of minimizing the total costs arises. Obviously, to ensure data transfer between sensors, a necessary condition is the presence of the intersection of the sensor coverage areas. In this case, the constant value of this parameter is considered. The materials propose an approach to solving the problem of maximizing the coverage of the territory with minimizing costs for a given level of intersection of the coverage areas of the sensors. The proposed approach is based on solving a nonlinear multiobjective optimization problem. Also, one of the options for solving the described problem is proposed to reduce the objective functions in one by using a weighted convolution of criteria. In addition, the article proposes an iterative approach to solving the described problem. A number of computer experiments have been carried out. The results of the performed computational experiments confirm the possibility of using the proposed information technology both in the form of an optimization problem and in the form of an iterative process.

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