Computer Systems and Information Technologies=Комп'ютерні системи та інформаційні технології

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Analysis of artificial intelligence based systems for automated generation of digital content
(Хмельницький національний університет, 2024) Pavlova, O.; Kuzmin, A.
This paper is aimed at the examination of contemporary challenges related to the integration of generative models API of artificial intelligence (AI) into a unified information system to facilitate the automated generation of digital content. In the context of rapid advancements in AI technologies and the increasing demand for diverse and personalized digital content, the integration of API-based generative models emerges as a crucial driver for progress in this field. The research findings underscore the significance of incorporating API-based generative AI models into a unified system, marking a significant step towards automating the process of digital content creation to meet modern market demands. By streamlining content generation workflows, such integration holds promise for enhancing efficiency and scalability while fostering creativity and innovation. Furthermore, the integration of generative AI models into a unified system presents opportunities for the development of personalized and innovative solutions tailored to the needs and preferences of end-users. This not only enhances user experiences but also enables the creation of content that resonates more effectively with target audiences across various domains. The findings gleaned from our research underscore the importance of integration of API-based generative AI models into a unified framework, representing a monumental stride toward the automation of digital content creation that caters to the exigencies of today's market dynamics. By streamlining content generation workflows and alleviating manual intervention, such integration holds immense promise in enhancing operational efficiency, scalability, and adaptability, while simultaneously nurturing a fertile ground for creativity and innovation to flourish. The further efforts of our research team are committed to the practical implementation of this concept and the exploration of its applicability across diverse domains. By continuing to refine and expand upon this integration, we aim to unlock new possibilities for automated content generation and drive further innovation in the digital content creation landscape.
Approaches of building a real-world object detector data source
(Хмельницький національний університет, 2023) Pavlova, O.; Bashta, A.; Kuzmin, A.
In our constantly developing world virtual, augmented, and mixed reality technologies are becoming integral parts of our daily lives. In the current stage of Information Technology field development, technologies of virtual, augmented and mixed reality can be seen in almost all areas of human life. Nowadays AR is used in Marketing and Advertising, Education, Medicine, Automotive, Game Development, Navigation and other areas of our everyday life. Therefore, object detection is a crucial task in computer vision and AI applications, enabling machines to identify and locate objects within images or video frames. The accuracy and performance of an object detector heavily rely on the quality and diversity of the training data. This paper is aimed at finding the approaches of building a real-world object detector data source to be able to create a model for detecting a sport games surfaces using the Action & Vision App. During this research several structured approaches of building an object detector data source have been built, drawing inspiration from Apple's Create ML documentation on the topic. Additionally, real-world applications available on both the App Store and Google Play that leverage object detection technology were showcased and analyzed. In the course of study a dataset of objects has been collected and then utilized to build a robust detection model, tailored to function seamlessly with Vision and Core ML frameworks on iOS devices. The trained object detection model, informed by the diverse dataset and robust training process, is employed to identify and outline tables and rectangles in each frame of the video stream. The model and the proposed approaches will be further applied to develop the method of object detection in the real world and create a mobile application for sport games simulation, that would help players to practice their skills out of the training field.
Augmented reality based information technology for objects 3D models visualization
(Хмельницький національний університет, 2023) Pavlova, O.; Bashta, A.; Kovtoniuk, M.; Павлова, О.; Башта, А.; Ковтонюк, М.
At the current stage of IT industry development, augmented reality is of interest both from the side of science and from the business side, since it is an advanced and newest tool for introducing a new immersive user experience. Today there are plenty ready-to-use applications that use AR for business, educational, medical and other purposes. Augmented Reality is currently one of the most popular upcoming technologies most commonly known for its use within games and advertising. By combining threedimensional modelling with augmented reality, it could be possible to obtain new user friendly applications for the representing 3D models of objects in real time and in real size. The topic of research in the field of augmented reality is currently relevant both for science and for the business industry. The paper proposes a multifunctional information system for three-dimensional models visualization in augmented reality, which is implemented in the form of a cross-platform mobile application. The proposed information system uses a device camera as a mean of object visualization and provides quick reproduction of the selected from the application`s database model in augmented reality in real size and in real time. The developed application works quite well, has a user friendly and intuitive interface and allows user to add own models, that makes this tool multipurpose.Test 3D models have been created for conducting experiments for verification the proposed information system operation. The further efforts of the authors will be directed to improving the existing algorithms for extending the current functionality of the proposed tool for 3D objects models visualization in augmented reality and application of the developed tool for real-life needs, such as digitization and visualization of museum exhibits and archaeological artifacts of Khmelnytskyi region
Augmented reality based information technology for objects 3D models visualization
(Хмельницький національний університет, 2023) Pavlova, O. ,; Bashta, A.; Kovtoniuk, M.; Павлова, О.; Башта, А.; Ковтонюк, М.
At the current stage of IT industry development, augmented reality is of interest both from the side of science and from the business side, since it is an advanced and newest tool for introducing a new immersive user experience. Today there are plenty ready-to-use applications that use AR for business, educational, medical and other purposes. Augmented Reality is currently one of the most popular upcoming technologies most commonly known for its use within games and advertising. By combining threedimensional modelling with augmented reality, it could be possible to obtain new user friendly applications for the representing 3D models of objects in real time and in real size. The topic of research in the field of augmented reality is currently relevant both for science and for the business industry. The paper proposes a multifunctional information system for three-dimensional models visualization in augmented reality, which is implemented in the form of a cross-platform mobile application. The proposed information system uses a device camera as a mean of object visualization and provides quick reproduction of the selected from the application`s database model in augmented reality in real size and in real time. The developed application works quite well, has a user friendly and intuitive interface and allows user to add own models, that makes this tool multipurpose.Test 3D models have been created for conducting experiments for verification the proposed information system operation. The further efforts of the authors will be directed to improving the existing algorithms for extending the current functionality of the proposed tool for 3D objects models visualization in augmented reality and application of the developed tool for real-life needs, such as digitization and visualization of museum exhibits and archaeological artifacts of Khmelnytskyi region
Automated system for determining speed of cars ahead
(Хмельницький національний університет, 2023) Pavlova, O.; Bilinska, A.; Holovatiuk, A.; Binkovskyi, Y.; Melnychuk, D.
Road accidents and speeding violations are pervasive issues that pose substantial threats to road users on a daily basis. In an ongoing effort to improve road safety and reduce the frequency of accidents, researchers and engineers have been dedicated to the development and implementation of new technologies. One such significant innovation is the utilization of speed control systems based on traffic cameras. This paper delves into a thorough exploration of the pivotal role and significance of speed control systems on our roadways. It investigates the operational principles, advantages, and various strategies employed to enhance the efficiency of these systems, with the ultimate goal of achieving optimal results in speed control and ensuring road safety. Speeding remains a widespread concern that significantly contributes to road accidents. Such incidents lead to injuries, fatalities, and extensive property damage, underscoring the urgent need for effective speed control measures. Among the arsenal of solutions available, speed control systems utilizing traffic cameras have emerged as a prominent and promising approach. These systems function by monitoring and recording the speed of vehicles at specific locations, which is later used to enforce speed limits and penalize offenders. The advantages of speed control systems based on traffic cameras are multifaceted. They offer an objective and reliable method for detecting and documenting speeding violations, eliminating the need for law enforcement personnel to be present at all times. This aspect not only frees up law enforcement resources but also ensures consistent and unbiased enforcement of speed limits. Additionally, the data collected by these systems can serve as a valuable resource for traffic management, accident analysis, and road safety research
Method of FPV drone stabilization on an automatically determined target and its further observation
(Хмельницький національний університет, 2025) Halytskyi, Oleksandr; Denysiuk, Dmytro; Kozhemiako, Yaroslava; Kvassay, Miroslav
In recent years, the use of FPV (First Person View) drones has gained significant traction across various fields, including recreational activities, infrastructure inspections, search-and-rescue missions, and military operations. The paper considers the problem of the lack of stabilization in FPV drones, which significantly limits their functionality for applications that require precise tracking of a specific target. Such drones, although characterized by high maneuverability and affordable cost, are inferior to commercial quadcopters such as the DJI Mavic, which are equipped with effective stabilization systems, but are significantly more expensive due to the use of proprietary technologies. The paper proposes a new approach to stabilizing FPV drones, based on the use of computer vision algorithms for automatic target detection and tracking. The main concept includes target detection based on image analysis from the drone camera, further determination of its trajectory and transmission of appropriate control commands to the flight controller using the MAVLink protocol. This approach allows to significantly increase the accuracy and stability of FPV drones when performing tasks that require focusing on an object, such as infrastructure inspection, search and rescue operations, or video shooting. The proposed solution is based on accessible and open technologies, which ensures its adaptability and low implementation cost. The paper describes in detail the developed system architecture, which includes a computer vision module for video stream analysis, algorithms for data processing and filtering, as well as integration mechanisms with existing flight controllers. A series of experiments were conducted to evaluate the effectiveness of the proposed approach. The results demonstrate that the proposed system is able to ensure stable drone tracking on a specified target even in difficult flight conditions.
Neural network based image recognition method for smart parking
(Khmelnytskyi National University, 2021) Pavlova, O.; Kovalenko, V.; Hovorushchenko, T.; Avsiyevych, V.; Павлова, О.; Коваленко, В.; Говорущенко, Т.; Авсієвич, В.
Currently, the issue of creating smart parking lots is extremely important due to the rapid growth of number of cars, especially in big cities. Thus the need for parking spaces and search facilities still remains an urgent problem. Assuming that every day the average motorist spends 20 minutes searching for such a place, this is about 120 hours a year, which could be spent on something more useful. Today, there are many projects of "smart" parking, but practical examples can be counted on the fingers, and information about the cost-effective aspect of their implementation is generally very limited. The paper provides analysis of the most common methods and tools for smart parking and proves the advantages of camera-based method. The research in general is aimed at image recognition for camera-based smart parking using convolutional neural network.
The concept of AI-based information systems for the analysis of learning foreign words
(Хмельницький національний університет, 2024) Pavlova, O.; Kozyra, A.
In the modern world, information systems based on artificial intelligence (AI) are increasingly used to automate learning and improve the educational process. One of the perspective areas of AI application is foreign language learning, particularly vocabulary acquisition. By integrating AI components, specifically those utilizing machine learning algorithms to analyze large volumes of data and provide automated recommendations to enhance the learning process, users gain constant access to selfassessment tools and automatic adjustment of cognitive workload.This paper examines the key role and significance of information systems for analyzing foreign language vocabulary acquisition with the help of AI. It investigates the working principles of such systems, their advantages, and various strategies used to enhance the efficiency of language learning, aiming for optimal results in acquiring new linguistic knowledge and improving learning outcomes. Learning new foreign terms is often a challenging task for many students, leading to a loss of motivation or slow progress, highlighting the urgent need for solutions that enhance material retention. Adapting to individual users, AI-based information systems have developed a range of services and platforms with global potential for language learning worldwide. These systems function by analyzing user behavior and success, based on specific indicators and metrics, whose numerical values are interpreted to identify patterns and correlations between user behavior and its impact on the system. The advantages of AI-based information systems for language learning are significant, offering an objective, reliable method for assessing learning achievements, eliminating the need for human intervention in many cases. Data collected by these systems serve as a valuable resource for analyzing user productivity, detecting common mistakes, creating effective study plans, and more. However, it's important to note that AI has not yet reached the level of understanding semantics or the cultural and historical nuances of certain words, complicating the implementation of more comprehensive functionality for evaluating and adjusting the learning process. This requires developers to prepare additional data through proprietary sources or gain useful input from user interactions with the system.
Use of smart contracts on the ton blockchain for innovative educational solutions development ed on machine learning algorithms
(Хмельницький національний університет, 2025) Askerov, Viacheslav; Tomchyshen, Bohdan; Bouhissi, Houda El
In the modern world, blockchain technologies are gaining popularity due to their ability to ensure security, transparency and decentralization of data. One of the most promising platforms is The Open Network (TON), which provides unique opportunities for the development of smart contracts. This article discusses the main features of the TON blockchain and its advantages in the context of educational process automation. Smart contracts implemented on the TON platform can serve as a tool for optimizing educational systems. They allow to automate processes related to knowledge validation, grade management, and even finance in educational institutions. For example, smart contracts can provide automatic scholarships based on students' grades, as well as control over the implementation of curricula. The paper also analyzes the benefits of using smart contracts in the educational process, such as reducing administrative costs, increasing transparency, and reducing fraud risks. In addition, blockchain technologies provide an opportunity to create decentralized platforms for storing and sharing knowledge, which makes learning more accessible and effective. Particular attention is paid to the mathematical aspects that ensure the functioning of TON, as well as sharing mechanisms that allow the platform to process thousands of transactions per second. These technologies can be used to create educational applications requiring high bandwidth and data processing speed. The paper contains formulas that illustrate the technical characteristics of the TON blockchain and provides a detailed analysis of its architecture. The study shows that smart contracts on the TON platform have the potential to revolutionize educational processes by providing new tools for data management and security.
Video repeater design concept for UAV control
(Хмельницький національний університет, 2024) Pavlova, O.; Halytskyi, O.
This study is aimed at the utilization of a video repeater for unmanned aerial vehicle (UAV) control, involving a comparative analysis of existing scientific literature, methodologies, and available solutions. Through comparative analysis, the method of using an external repeater emerged as the most promising, offering flexibility in selecting repeaters with superior performance and advanced capabilities. Notably, this approach allows for the utilization of a single repeater across multiple UAVs and facilitates convenient modification or upgrade of the repeater without necessitating alterations to the UAV itself. Following component selection, an experimental prototype was designed to facilitate empirical investigations. Additionally, a frequency transmission scheme was devised for quadcopter control employing the repeater. This research represents a significant advancement in the realm of UAV control systems, introducing a novel approach to video repeater integration that is poised to revolutionize operational efficiency and adaptability across diverse operational settings. This approach offers unparalleled flexibility in the selection of repeaters boasting superior performance and advanced capabilities. The insights gleaned from this study are poised to catalyze further advancements in UAV technology, particularly in the realm of optimizing video transmission for enhanced situational awareness and mission effectiveness. By shedding light on the efficacy of video repeater integration, this study lays the groundwork for future innovations aimed at pushing the boundaries of UAV capabilities and enhancing their utility across a myriad of applications. The findings from this study are anticipated to inform further developments in UAV technology, particularly in optimizing video transmission for improved situational awareness and mission effectiveness

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