FitAddict App : έξυπνη εφαρμογή Android για φυσική δραστηριότητα με έτοιμες ασκήσεις και εξατομικευμένα προγράμματα μέσω τεχνητής νοημοσύνης
FitAddict App: a smart Android app for physical activity with built-in exercises and AI-personalized workout programs
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Keywords
Fitness app ; Firebase authentication ; Activity tracking (Distance/Time/Steps) ; Workout build & progress ; Firestore media ; Android UI navigationAbstract
This thesis analyzes the development and functionality of the FitAddictApp. The first chapter presents the theoretical framework related to fitness and wellness applications, as well as existing solutions that inspired the concept and design of FitAddictApp.
The second chapter describes in detail the technologies used for the development of the application, including Android Studio, Kotlin, Git, and Firebase, along with the architectural methodologies MVVM and Clean Architecture. Advanced tools such as Hilt, Room Database, Firebase Cloud Functions, Generative AI, Vertex AI SDK, Prompt Engineering, and Data Validation are also analyzed, demonstrating their contribution to a robust and intelligent software solution.
The third chapter focuses on the code structure of the application, explaining the key components and their interaction for ensuring a seamless user experience. Special attention is given to Jetpack Compose, Navigation Components, and Firebase tools such as Analytics, Crashlytics, and Push Notifications.
Finally, the fourth chapter presents the complete application, explaining its interface and functionality step by step, while highlighting the use of artificial intelligence in the field of health and physical fitness.