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Item type:Наукова стаття, Latency Reduction in Real-time GPS tracking in Android and the Web-based GPS Monitoring System(IEEE, 2022-12-09) Tsindeliani, Davyd; Povstiana, Yuliia; Lishchyna, Nataliia; Yashchuk, AndriiThe paper focuses on the research aimed to reduce latency in real-time GPS-tracking and implementation of a real-time web GPS-monitoring system based on Android devices that publicly provides access to users' locations. A real-time GPS monitoring system with low latency consists of three main components: a web front-end client, a server part, and an Android application. During the development process, the performance of WebSocket back-end frameworks was researched. The performance of Google Maps and Leaflet (OpenStreetMap) was compared to select the option which provides the best performance in the developed system. The conducted research and the chosen solutions for the implementation of the project made it possible to develop a system that shows high efficiency and performance. The developed software allows any user with an Android mobile device to share their location with others with minimal latency and show their location and traffic history. © 2022 IEEE.Item type:Наукова стаття, Architectural And Engineering Aspects Of Integrating The Novita Ai Api Into A Web Application For Image Generation(Lutsk: LNTU, 2026-03-28) Povstiana, Yuliia; Lishchyna, Nataliia; Surynovych, Olena; Boiko, LevThis paper investigates architectural and software engineering approaches to integrating the Novita AI image generation service into a web-based application that supports scalable and asynchronous request processing. The proposed solution is based on a clear separation of responsibilities between frontend and backend components, where the backend handles validation, orchestration of long-running tasks, interaction with external APIs, and data persistence. Communication is implemented using REST for synchronous operations and WebSocket-based notifications for asynchronous updates, while resource-intensive tasks are executed through a queue-based mechanism to prevent interface blocking. Integration with the Novita AI service is encapsulated within a dedicated service layer, ensuring modularity, maintainability, and extensibility. An experimental evaluation was conducted to measure execution times of key operations, including image generation, transformation, upscaling, and custom model training. The results confirm the effectiveness of asynchronous processing and demonstrate that custom models improve output consistency at the cost of a minor increase in generation time. The novelty of this study lies in the architectural justification of asynchronous API integration for AI-based image generation with support for custom model training, validated through experimental performance evaluation.