Fedyshyn T. Metrological support of the cyber-physical system of soil monitoring

In the course of the study, theoretical and practical aspects of metrological and information support for cyber-physical systems (CPS) for soil monitoring were developed, which provided a new approach to assessing soil parameters. The use of neural networks and cloud technologies has significantly improved the accuracy and reliability of forecasting agricultural indicators, which is of great importance for the agricultural sector. The main results of the study include the development of a predictive model of soil condition change, which provides for the forecasting of the main stages of agricultural production and possible grain yields. It is established that such a model, built on the basis of neural networks and cloud technologies, provides high accuracy of forecasts, which is important for optimising agro-technological processes and increasing the efficiency of agricultural production. The paper also highlights the features of cyber-physical systems that distinguish them from conventional multi-channel measurement systems. In particular, the concept of "metrological reliability of measurement information" is considered, which is broader than the traditional concept of "metrological reliability of a measuring instrument". This allowed a more comprehensive assessment of the reliability of CFCs. Considerable attention is paid to the environmental component of the grain growing process. Using the special SimaPro software, we conducted a study of the life cycle of agricultural production, based on which we calculated the environmental index and identified the most influential environmental factors. This allows optimising the decision-making process of a cyber-physical soil monitoring system and minimising the negative impact on ecosystems. In general, the results of this thesis contribute to the development of the theory and practice of metrological support for cyber-physical soil monitoring systems. The data obtained can be used to improve agricultural production methods, increase its efficiency and environmental safety, which is of great importance for the sustainable development of the agricultural sector.