This paper presents the development of technologies to support the decision-making of local government executives and smart city concept managers in selecting and evaluating the competencies of new members for advisory groups for solving problems that are implemented in safe times in individual areas or in crises, such as pandemics. The reason for developing effective urban transformation strategies and for the transparent selection of independent experts (non-politicians) for policymaking, decision-making, and implementation teams is not only the heterogeneity of smart city dimensions together with the necessary complexity and systems approach, but also the nature of the capacities and tools needed for smart city concepts. The innovative hybrid competency assessment model is based on fuzzy logic and a network for neuro-fuzzy assessment. It is a technological model for evaluating the competencies of specialists, taking into account the influence of human factors on the processes of personnel selection and system management. An innovative web platform named “Smart City Concept Personnel Selection” has been designed, which can be adapted to various users of municipalities or regional institutions for the transparent selection of qualified personnel for effective decision-making and the use of public funds during safe times or emergencies, such as the COVID-19 pandemic.

The agenda of the international community is focused on the global problem of aviation in the lack of pilots while maintaining the quality of their professional education. The trend is to explore the potential of students and help increase resistance to obstacles on the way to results, but especially on the way to the creation of the required competencies, knowledge, and skills. The main goal of this paper is to develop a hybrid expert model evaluating the results and risks of student (pilot) outcomes to improve the quality of individual results in the didactic system of aviation education (study results from theoretical subjects, evaluation from training on flight simulators, and from practical flight training) within one information platform. The model is based on the modern theory of intellectual knowledge analysis, fuzzy set theory, and a systems approach. Information from the repository of 696 individual results of undergraduate students (pilots) from the total number of 2682 undergraduate students of all specializations in aviation education in the period 2005–2022 was used in the creation of the model. The results were tested on the examples of five undergraduate students (pilots) and demonstrated the applicability of the expert methodology for evaluating the quality and risks of individual results in aviation education for individual study counseling within one information platform.

The main goal of the research is to develop an artificial intelligence technology to assess the practical knowledge of air traffic controller (ATCo) students based on their responses in simulated multitasking situations using the proposed neuro-fuzzy model verified in experiments. An informational neuro-fuzzy model was developed and verified on 157,500 real data points. It illustrates an example of inferring the level of practical knowledge in selected ATCo students who were tested using a device measuring the reaction time and relative error rate in multiple-task tasks. The average error in the incorrect response was 7.7% of the experimental data. Data processing was performed using fuzzy set theory and intellectual knowledge analysis. These measurement results are useful for an individual approach to the student’s education to understand and master the correct solutions to achieve the desired educational results. Ensuring a personal approach to the student’s education is key to acquiring the necessary skills, knowledge, and competencies in the profile of the graduate. The developed technology will enable the integration of automated knowledge and skills assessment systems into the real educational process and the identification of problematic topics and tasks in the training of individuals. The result of the conducted research was used for the software design for the practical application in the flight training of ATCo students.

Testing in the field of parachute technology provides space for the application of new and innovative methods of measuring operating and functional parameters. The main aim of the paper is to present the results of research for the verification of the photo-optical method of measuring the vertical speed of the M-282 parachutes, and for its use in testing, collecting, and investigating motion data in parachuting. As part of this measuring technology, twelve jumps were performed. It was verified that the experiment was completed for the M-282 parachute according to the regulation of SAE AS 8015B “Minimum Performance Standard Parachute Assemblies and Components”. An analysis of the influencing factors and quantification of their influence on the uncertainty of the measurement results was also performed. The results of the measurement achieved by using the photo-optical method were compared with the measurement with the electronic variometer FLYTEC 4030. The vertical speed of the M-282 parachute (4.655 m·s⁻¹) defined by the photo-optical method is significantly similar to the vertical speed of the M-282 parachute (4.662 m·s⁻¹) defined by FLYTEC 4030. We can state that the process of identifying the vertical speed of the parachute by the photo-optical method was correct. This is a suitable method of evaluating motion data in the operation of M-282 type parachutes. In the following research for generalization of the methodology, we assume the performance of more than 60 experimental jumps using different types of parachutes, digital sensors (cameras), and a photo-optical method to examine motion data and formulate recommendations for testing, investigative applications, individualized training programs, and aspects of parachuting injury prevention.

This study aimed to develop an intellectual and analytical platform for assessing the psychophysiological load on flight instructors in a flight school (general aviation). As part of this study, an information model for evaluating the working environment’s load based on noise levels was developed, a model to predict individual psychophysiological load was created, an expert model to assess mental health was established, and a hybrid model was devised to determine the overall psychophysiological load on an instructor while performing their duties. Noise load was measured during flights with two aircraft (Zlín Z43 and Diamond DA-40 TDI), resulting in the acquisition of 4,361,300 data points. This dataset was collected during two data acquisition sessions for each aircraft, encompassing three phases of flight: takeoff, in-flight, and landing. During the flight, noise measurements were conducted based on five indicators: sound pressure, fluctuation strength, roughness, sharpness, and tonality. Based on the measured data, the platform was verified and configured, and example evaluations were demonstrated. This study employed modern methods of intelligent data analysis, utilizing both univariate and multivariate membership functions. The developed platform incorporates quantitative dynamic data obtained from devices measuring psychophysiological load, integrating professional mental health assessments and predicting dynamic work environment indicators for modeling load trends. Early detection of critical load levels helps protect the health of flight instructors, thus creating a safe working environment for training new pilots.

Digital transformation is becoming increasingly widespread, and it can be said that it is an inevitable process. Digitization has enabled the streamlining of a wide range of tasks, from simple everyday activities to complex operations, enhancing efficiency, speed, and cost-effectiveness in their execution. The degree of digitization in a country is a key indicator of its level of development and the competitiveness of its economy. However, the phenomenon of digitization necessitates a heightened focus on cybersecurity measures. Investment in solutions that guarantee cybersecurity is essential for the success of digital transformation, as new technologies are integral to such transformations and will be effectively exploited by cybercriminals and cyberterrorists if not protected. IT systems used in strategic sectors responsible for national or international security must be adequately protected (cybersecurity). Such systems must be resistant to cyberthreats.