Today, the demand for digital tools supporting a healthy lifestyle is booming. Our research addresses crucial challenges like sedentary living and declining physical activity, which contribute to chronic diseases. Current fitness apps often fall short on personalization, wearable integration, strong motivation, and data security. This drives the need for advanced, cross-plat-form solutions like React Native.The core problem lies in the limited customization of existing apps, poor wearable connectivity, weak motivational ele-ments, and clunky user interfaces. Some of them also offer only narrow functionalities. Our goal is to develop a cross-platform mobile fitness app using React Native, Expo, and AsyncStorage, focusing on personalized training, optimized UX/UI, and integrated motivation and progress tracking.The app's architecture follows the Separation of Concerns principle, with distinct layers for presentation, business logic, data, and navigation. AsyncStorage ensures autonomous, local data storage for user profiles, workouts, and statistics. We used UML diagrams to visualize system functionality and data structure, encompassing UserProfile, Workout, and Statistics entities linked by user IDs. A key feature is the dynamic workout selection based on user goals.The React Native interface is modular, featuring intuitive tab navigation. It includes a home screen for quick stats, a workout screen, a statistics screen with progress graphs, and a profile management section. An onboarding screen gathers initial data for a tailored experience. Developed with Visual Studio Code, Expo CLI, and tested on Android Emulator, the app offers an intuitive interface, personalized fitness, and reliable local data storage.This project delivers an innovative architectural solution for an autonomous mobile workout management system, dy-namically adapting to user goals and tracking progress without constant internet. This emphasizes personalization and privacy. The functional prototype and detailed architectural models offer practical value, potentially cutting development time for sim-ilar systems by 20-30 %. Future research will explore AI for deeper adaptation, enhanced gamification, wearable integration, and secure cloud backup.
Morokhovych et al. (Mon,) studied this question.
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