## 6 Conclusions  
This work develops an intelligent analytical platform for assessing the psychological workload of flight instructors. To achieve this goal, an informational model for evaluating the workload of flight instructors in the working environment based on the noise level was developed; a model for predicting the individual psychophysiological workload of flight instructors in the working environment was created; an expert model for assessing the mental health of flight instructors was constructed; a hybrid model for determining the overall psychophysiological workload of the flight instructor during duty was developed; the intelligent analytical platform was verified and calibrated using real data from flight instructors in Slovakia; and examples of assessments are described. For the first time, an informational model for assessing the workload of flight instructors in the working environment based on noise level has been developed. Five key noise measurements that have the greatest impact on the instructor's workload are proposed: sound pressure, fluctuation strength, sound roughness, sound sharpness, and sound tonality assessed using the harmonic masking signal method. In addition, the use of a harmonic S-spline for normalizing the input data is justified. It has been experimentally confirmed that the use of a harmonic S-spline improves the smoothness and accuracy of interpolation of acoustic parameter data, which is especially important for capturing transient peaks in noise exposure during flight maneuvers. Therefore, its selection is not arbitrary but based on the empirical advantage it provides for modeling precision and preserving the harmonic nature of acoustic signals. However, it should be emphasized that the effectiveness of these acoustic indicators depends on the specific characteristics of the flight phase and aircraft type. Preliminary analysis showed that sound roughness and fluctuation strength are more sensitive to sudden changes in cabin conditions during takeoff and landing, while sharpness and tonality better reflect background discomfort in cruise mode. Measurement quality was controlled using calibrated equipment. However, future studies are needed to quantify the signal-to-noise ratio and assess measurement uncertainty under varying operational conditions. For the first time, a model for predicting the individual psychophysiological workload of the flight instructor in the working environment has been developed. The model uses regression analysis techniques, and the obtained predicted assessments of the individual psychophysiological workload of the flight instructor establish a comprehensive trend relationship of the working environment indicators. Measurements were performed on the two above-mentioned aircraft types by two instructors during flights with two university student pilots, in standard flight conditions. For the first time, an expert model for assessing the mental health of the flight instructor has been developed. This model proposes an open set of seven criteria that allow examining various aspects of mental health, namely: the difficulty and intensity of the training program; the experience and qualifications of the instructor; the working day; the technical condition of the aircraft; weather conditions; social and family factors; and the atmosphere in the team. During its creation, the model was compared with the technical solution of the utility model \"Device for measuring individual psychophysiological load\", which is also protected within the framework of air traffic by the Industrial Property Office of the Slovak Republic, as described in this article, although it has not yet been compared with another, for example, clinical assessment. The output provides an expert linguistic conclusion DM, regarding the flight instructor's mental health. A hybrid model for determining the overall psychophysiological workload of the flight instructor during duty has also been developed for the first time.