Адаптивні системи автоматичного управління : міжвідомчий науково-технічний збірник. – 2025. – № 1 (46)

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https://ela.kpi.ua/handle/123456789/73842

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Перегляд Адаптивні системи автоматичного управління : міжвідомчий науково-технічний збірник. – 2025. – № 1 (46) за Автор "Polshakova, O."

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    Automated vehicle number plate recognition in real-time using computer vision technologies
    (КПІ ім. Ігоря Сікорського, 2025) Bodnar, A.; Polshakova, O.
    This article explores the development and application of computer vision across various fields, particularly in transportation and public safety. License plate recognition using advanced technologies ensures accuracy and reliability in managing next generation transport operations. The integration of these technologies with other modern systems makes them critically important for ensuring safety and efficiency. It is projected that the use of computer vision technologies will rapidly increase as they provide essential functions in security, transportation, and other sectors. License plate recognition is a key element of many AI programs and systems, underscoring their significance for contemporary society. This work examines the limitations of current license plate recognition systems and proposes the use of YOLOv8 and EasyOCR libraries for implementing license plate recognition algorithms. YOLOv8 is used for detecting license plates in images, including preprocessing and image quality enhancement. EasyOCR is used for text recognition on license plates, thanks to its highly efficient API.
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    Subsystem for recognition of emergency situations on the road
    (КПІ ім. Ігоря Сікорського, 2025) Vorona, O.; Polshakova, O.
    The article considers an approach to solving the problem of increasing the speed of response to emergency events on the road. The process of incident recognition and automatic notification of the relevant operator to improve the interaction of intelligent smart city systems with emergency services of the city is the object of research in this work.As a result of the study of this subject area,road incidents were classified and systematized. Also, the database includes information about the services that can be involved in responding to the event, and communication channels with them have been configured.The proposed solution involves the use of visual surveillance tools capable of recognizing an emergency situation on the road and sending a notification about it to emergency services, as well as recording information about the incident in a single data store as a component of Smart city.
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    Usingcomputer vision for automated object tracking system
    (КПІ ім. Ігоря Сікорського, 2025) Bulbotka, N.; Polshakova, O.
    The article examines the use of computer vision technologies to automate the process of tracking objects in a video stream. The developed system is described, which implements the recognition, tracking and determination of the characteristics of moving objects using the YOLOv8 model. The system includes modules for video display, recognition, tracking, and determination of object characteristics. The process of retraining the YOLOv8 model on specific data sets is described, as well as the application of algorithms for determining the speed of moving objects.The proposed solution allows analysis of the video stream in real time. The results confirm thecompliance of the developed system with the set requirements and its practical suitability in the areas of video surveillance, analysis of the behavior of objects, unmanned aerial vehicles and transport systems