The Master's thesis consists of an introduction, seven chapters, conclusions, and a list of references. It also contains 182 pages, including 65 figures, 32 tables, and 125 sources.
The aim of the Master's thesis is to improve the productivity, reliability, and rhythm of the technological process for sorting fruits of vegetable crops by developing an intelligent automated sorting system. To achieve this goal, methods of machine learning, computer vision, and deep learning algorithms were employed. The results of the work demonstrated a high classification accuracy of the fruits, which allows for the effective use of the system in real production environments.

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The thesis explores and implements an automated real-time object recognition system based on the NVIDIA Jetson Nano platform.
     The purpose of this study is to develop a high-performance and energy-efficient object recognition system that meets real-time requirements while operating under limited hardware resources.
     The research analyzes modern methods and algorithms of computer vision, including YOLOv8, Faster R-CNN, and SSD. A review and comparison of hardware platforms such as Raspberry Pi, Jetson Nano, and Google Coral have been conducted. Data augmentation was applied for model training, and the neural network was optimized using ONNX and TensorRT. A software suite was developed for object recognition, achieving high accuracy (mAP 95%) and a processing speed of 15 frames per second.

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Relevance of the topic
The topic of this master's thesis concerns the development of an automated lighting system for a cottage, which is relevant given the need for energy efficiency, comfort and safety of modern housing. Optimizing lighting is important for improving the quality of life, rationalizing energy use, and creating an attractive environment in residential areas. Traditional lighting control methods are limited due to low efficiency, the need for manual control, or the lack of adaptation to changing environmental conditions. In this regard, the introduction of intelligent lighting systems using modern sensors and microcontrollers is becoming an important task.
The development of digital technologies opens up new opportunities for creating more affordable, efficient and innovative lighting solutions. As part of this work, we developed two automated lighting systems for the cottage: one for the bathroom and one for the living room. These systems are based on the use of Arduino, presence sensors, light levels, and other components to automate lighting processes, providing comfort and convenience to users.

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The paper presents modern systems for controlling the moisture content of fabrics, which are aimed at improving the efficiency of production processes in the textile industry. The main goal of the study is to create a device that provides accurate, fast and uniform measurement of the moisture content of textile materials without destroying their structure.
The system is based on the use of infrared sensors that analyze the intensity of reflected radiation, which varies depending on the moisture content of the material. Integration with a microprocessor platform allows for automatic data processing, storage of results and their transfer to a centralized production management system.

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The master's thesis contains an introduction, three chapters, conclusions and a list of references. The master's thesis includes 113 pages, including 17 figures, a list of references and 30 table.
The purpose of the master's thesis is to improve the measuring system and coordinate measuring machine (CMM), in particular, the development of a motorized servo head for CMM, which will ensure the accuracy of measurements under variable loads and angular positions.
To achieve the goal, the following tasks were performed: development of a model of a motorized servo head for CMM, which includes servo motors, a worm gear reducer. Calculation of the gear ratio of the reducer to ensure the required accuracy of measurements.

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  1. Zemliakov O. Automation of the cartographic image segmentation process
  2. Pitukh I. Web application for visualization of ultrasonic flow detector data
  3. Piven N. Security alarm system for office premises
  4. Novozhylova A. Human Condition Monitoring System with Remote Data Collection and Analysis

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АСНК КПІ ім. Ігоря Сікорського, 2021