CSIT - 2025 рік

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https://elar.khmnu.edu.ua/handle/123456789/18099

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Перегляд CSIT - 2025 рік за Ключові слова "cyber-physical system"

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  • Ескіз
    Документ
    Cyber-physical system for determining soil parameters
    (Хмельницький національний університет, 2025) Voichur, Yurii; Payonk, Illya
    The relevance of a cyber-physical system for determining soil parameters in Ukraine is determined by several important factors, including climate change, declining soil fertility, and the need to implement efficient technologies to ensure sustainable agriculture. In Ukraine, where a large part of the economy depends on the agricultural sector, accurate soil monitoring is a key aspect to increase the efficiency of agricultural production, optimize the use of water and land resources, and reduce the cost of fertilizers and pesticides. Cyber-physical systems can provide timely data collection on soil moisture, temperature, pH, and other critical soil parameters, allowing farmers to respond quickly to changes in environmental conditions. Such systems can reduce the negative impact of excessive irrigation and optimize the use of water resources, which is especially important in the face of drought, which is increasingly common in Ukraine due to climate change. These systems also allow for accurate forecasts of yields and soil conditions, as well as the development of individualized recommendations for each field or plot. Since Ukraine has a wide variety of climatic conditions and soil types, cyber-physical systems are able to adapt to different agricultural needs, making them extremely useful for the development of precision agriculture. The introduction of such technologies helps not only to preserve natural resources but also to improve the economic efficiency of agriculture. Therefore, the development and implementation of cyber-physical systems for soil monitoring is an extremely important step for the sustainable development of Ukraine's agricultural sector. Therefore, our research is devoted to the development of a method and a cyber-physical system for determining soil parameters. The cyber-physical system for determining soil parameters consists of three levels: the level of sensors, the level of the controller to which the sensors are connected, and the system for collecting, monitoring, and managing data in real time. To build a cyber-physical system for determining soil parameters, we selected sensors, selected a controller, selected a data transmission standard, and developed a method for collecting, monitoring, and controlling data. The proposed method of data acquisition, monitoring and control for the upper level of the cyber-physical soil parameterization system allows for efficient data acquisition, monitoring and control in a cyber-physical system with various parameters stored in real time.
  • Ескіз
    Документ
    Method and cyber-physical system for forecasting and optimizing electricity consumption in residential districts
    (Хмельницький національний університет, 2025) Pysmeniuk, Volodymyr; Levashenko, Vitaly
    The development of cyber-physical systems combined with machine learning algorithms opens new opportunities for forecasting and optimizing electricity consumption in residential districts. This study examined existing technologies and solutions for energy consumption management, identifying their advantages and disadvantages. The analysis showed that modern commercial systems are primarily designed either for industrial use or individual consumption, lacking a comprehensive approach for residential districts. The proposed forecasting and optimization method is based on hybrid machine learning algorithms. For energy consumption forecasting, a combination of recurrent neural networks (RNN) and XGBoost was used, allowing for the consideration of both temporal dependencies and nonlinear factors. For energy consumption optimization, a combination of genetic algorithms (GA) and particle swarm optimization (PSO) was implemented, ensuring efficiency in finding optimal solutions. The developed cyber-physical system includes sensors for data collection, microcontrollers (Raspberry Pi) for data processing, and intelligent systems for controlling electrical appliances. This enables real-time energy consumption analysis and management, improving the energy efficiency of residential districts. Experimental results confirmed the effectiveness of the proposed approach, demonstrating high accuracy in energy consumption forecasting and the potential for reducing electricity costs through optimized usage. The proposed method has significant potential for scaling and implementation in large residential complexes, contributing to sustainable development and reducing the load on energy grids. Thus, the results of this study can be used for further improvement of energy management systems, promoting efficient electricity use, reducing consumer costs, and minimizing the environmental impact of energy systems.
  • Ескіз
    Документ
    Method of operation of the cyber-physical water resources monitoring system
    (Хмельницький національний університет, 2025) Voichur, Yurii; Balan, Andrii
    The relevance of designing and developing a cyber-physical water monitoring system for Ukraine is driven by the need for effective water management in the face of climate change, water pollution, and growing water supply needs. Modern challenges, such as the lack of clean drinking water, irrational use of resources, emergency condition of water supply networks and environmental threats, require the introduction of innovative technologies. The use of sensor networks, artificial intelligence, and cloud computing allows us to quickly obtain information about water quality and quantity, predict changes, and prevent emergencies. The introduction of cyber-physical systems in the field of water resources monitoring will help to increase the efficiency of water management, reduce losses, improve the ecological condition of water bodies and provide the population with quality water. For Ukraine, where water security is a strategic issue, such solutions will be an important step towards sustainable development and environmental balance. The use of Internet of Things (IoT), Big Data, and artificial intelligence technologies can automate the processes of data collection, analysis, and forecasting, which will help optimize water use, prevent pollution, and increase the efficiency of water infrastructures. Thus, the task of designing and developing a cyber-physical water resources monitoring system is currently relevant for Ukraine. The article develops a method for the operation of a cyber-physical water resources monitoring system that provides cyber-physical integration (a combination of physical (sensors, objects) and cybernetic (analytics, control) components), autonomy (the ability to function without constant human intervention), scalability (the ability to expand the geography of monitoring), and monitoring continuity (round-the-clock real-time monitoring).
  • Ескіз
    Документ
    Mobile-oriented cyber-physical system for food allergen detection based on machine learning and image analysis
    (Хмельницький національний університет, 2025) Talapchuk, Valentyn; Zaitseva, Elena
    The prevalence of food allergies necessitates the development of effective methods for the timely detection of allergenic components in food products to prevent dangerous medical reactions. In this work, a mobile-oriented cyber-physical system is proposed, leveraging state-of-the-art machine learning techniques and image analysis for the automated detection of food allergens. The developed system integrates the capabilities of mobile devices equipped with high-quality cameras and efficient computational resources, enabling accurate processing and classification of food product images either locally or via cloud-based inference. This approach ensures flexibility in deployment while maintaining high detection accuracy across diverse environments. This study examines both the theoretical and practical aspects of applying deep neural networks to object recognition tasks. Particular emphasis is placed on the EfficientDet model, which, due to its optimal balance between detection accuracy and computational cost, represents a promising solution for mobile applications. To enhance recognition performance, image preprocessing methods—including normalization, scaling, and data augmentation—are employed to increase the model’s resilience to variations in imaging conditions. The methodology for data collection and image annotation is described in detail, including the pre-processing procedures that ensure improved model robustness under diverse external conditions. Experimental investigations conducted on a large annotated dataset demonstrate the high accuracy and effectiveness of the system in detecting the presence of food allergens, thereby enabling the prompt identification of potentially hazardous components. The results of the work highlight the practical applicability of the proposed system in mobile applications for monitoring food quality and preventing allergic reactions. The conclusions outline prospects for further research, focusing on expanding the platform’s functional capabilities through the integration of additional sensor technologies and the refinement of data processing algorithms.