Introduction. The increase in the number of heterogeneous groups of UAVs that jointly perform aerial photography missions generates a large amount of poorly structured information: videos, photos, telemetry records, navigation data. To build intelligent databases from unstructured information sources from UAV groups, granular computational approaches are proposed. These approaches are the basis for the application of Big Data technologies and artificial intelligence to increase situational awareness or commercial value of knowledge gained from the data flow from UAV groups.
The purpose of the article. Develop new models for assessing the quality of video data from UAVs, approaches to equipping heterogeneous groups of UAVs and indicators for assessing its tactical and technical characteristics as a team.
Results. The success of UAV group mission planning is based on the forecast of quantitative and qualitative indicators of the received video data. For this purpose, a model for forecasting the quality of the obtained aerial photographs based on the data on the speed, height of the UAV and the angle of the video camera is proposed. The model is based on the development of the theory of fuzzy sets of the first and second types. An example of the implementation of the model in the system of computer mathematics MatLab 2020b is given.
Based on the analysis of a number of works on UAV classification and the proposed model of image quality, the method of equipment for the UAV group and the choice of UAV types are built, as well as the content of the combinatorial optimization problem based on the classic backpack problem. An example of calculations of tactical and technical characteristics for the Ukrainian UAV "Spectator" of Meridian ltd. is given.
Conclusions. A new model for assessing the quality of aerial photography images based on fuzzy logic has been developed. The method of staffing UAV groups is proposed. Keywords: Fuzzy logic, granular calculations, UAV equipment, heterogeneous groups, computer simulation.