The master’s thesis is devoted to solving a relevant applied scientific and engineering problem of developing an automated device for measuring the void volume of a tank, intended for monitoring the liquid level and volume in reservoirs of various purposes. The work substantiates the feasibility of using automated information and measurement systems to improve the accuracy, reliability, and efficiency of determining volumetric parameters of liquids under industrial, technological, and operational conditions. The main focus of the thesis is placed on the analysis of existing methods for liquid level and volume measurement, justification of the selection of the float-based measurement method, and the development of a structural and functional architecture of the automated measuring device. A hardware–software implementation of the measuring system is proposed, which includes a level sensor, a microcontroller-based data processing unit, and means for indication and transmission of measurement results. The influence of external factors, such as temperature variations and physical properties of the liquid, on measurement accuracy is also taken into account.

Spatial object positioning is a crucial task in modern security, navigation, and automation technologies. The use of acoustic emission to determine the position of objects opens new perspectives in cases where traditional methods are limited or ineffective. Acoustic methods allow for determining the position of objects in complex conditions, such as poor visibility, the presence of physical obstacles, or a lack of direct line of sight.
At the same time, real-time detection of aerial vehicles faces a number of challenges: Complexity of signal processing in high-noise environments. Presence of reflected sound waves (reverberation) that can distort data. Dependence of acoustic signal characteristics on weather conditions.

Relevance of the study: contact centers are one of the primary channels of communication between customers and businesses, while maintaining service quality standards and overall communication quality is a key factor in achieving customer loyalty and corporate reputation, directly affecting customer satisfaction and service efficiency. Manual quality control of conversations is unable to provide full coverage, typically reviewing only 10–15% of dialogues. Moreover, such evaluations are often subjective and depend on the individual skills of quality controllers and the frequency of team calibration. The use of large language models enables not only the automation of dialogue analysis but also increases objectivity and scalability without the need for additional personnel. These factors determine the relevance and practical significance of the study.

This work is dedicated to the development of an automated system for analyzing plant condition based on spectral data and fundamental vegetation indices such as NDVI, GNDVI, SAVI, EVI, and VARI. The goal of the study is to create a tool that enables vegetation image processing, calculation of spectral indicators, and interpretation of the obtained results to assess the state of agricultural crops.
The implemented system provides automated index calculation, visualization, and generation of summarized analytical results.
The developed software increases the speed and accuracy of vegetation condition assessment, supports the optimization of resource use, enables timely detection of stress factors, and assists in making informed agronomic decisions.

The master’s thesis is devoted to the development and substantiation of an automated quality control system for pulp-and-paper products, focused on continuous online measurements of key paper web parameters and ensuring prompt stabilization of operating regimes. The study was conducted using PJSC “Kyiv Cardboard and Paper Mill” as a case study, as one of the leading enterprises in the pulp-and-paper industry.
The aim of the thesis is to increase the stability of the technological process and reduce the share of defective products by automating quality control, in particular the basis weight (g/m²) and moisture content, with subsequent integration of measurement results into production control loops. The object of the research is an automated quality control system. The subject of the research is its properties and characteristics that determine accuracy, reliability, and suitability for integration into the paper machine’s process control system.
The thesis includes an analysis of the technological process and existing approaches to laboratory and online control, and identifies critical parameters and control points. A system concept is developed based on a cross-direction profiling scanning platform with measurement channels for basis weight (g/m²) and moisture; structural and functional diagrams are prepared, and the selection of sensors and hardware/software tools is justified. A separate outcome is a startup project for commercializing the proposed solution as the “CelluScan” product— a modular online system for basis weight and moisture control with analytics for process engineers and quality control departments.
The total volume of the thesis is 126 pages and includes 11 figures, 32 tables, 11 equations, and 4 appendices; the list of references contains 42 sources.

Research advisor: Yu. Kyrychuk

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All Masters Thesis

АСНК КПІ ім. Ігоря Сікорського, 2021