The subject matter of the article is the process of developing information technology for the automated detection and identification of stationary objects by unmanned aerial vehicles arises. The goal of the study is to development of the main points for information technology of automated detection and identification of stationary objects by unmanned aerial vehicles. The tasks to be solved are: the structural diagram of the preparatory stage of information technology for automated detection and identification of stationary objects is constructed; the structural diagram of the basic, additional and final stages of information technology automated detection and identification of fixed objects is constructed. General scientific and special methods of scientific knowledge are used. One of the most effective approaches to the recognition and identification of objects is an approach based on the use of deep learning methods. A new model of UAV motion is proposed based on image recognition methods. The methods of pattern recognition with application of neural networks are considered in detail in this work too. The following results are obtained. The developed information technology is implemented in four stages: preparatory, basic, additional and final. Each stage consists of separate procedures aimed at collecting, processing, storing and transmitting information during the flight UAV. Conclusions. Information technology for the automated detection and identification of stationary objects by unmanned aerial vehicles is based on the knowledge-oriented representation of the stages of image processing of objects on digital aerial photographs on board the UAV. This allows to provide intelligent real-time data processing, changing UAV flight routes depending on the objects detected to improve the effectiveness of the search tasks. Further development of this information technology lies in the development of automated methods of planning UAV routes, automatic change of route parameters in flight processes (performance of a flight task), based on knowledge-oriented technologies. Information technology for the automated detection and identification of stationary objects by unmanned aerial vehicles can become an element of intelligent decision support systems for the use of UAVs (teams of UAVs) to search for both stationary and dynamic objects.