CBL - Campus del Baix Llobregat

Projecte llegit

Títol: Desenvolupament d'una aplicació destinada al món del fitness amb Machine Learning

Estudiants que han llegit aquest projecte:


Departament: DAC

Títol: Desenvolupament d'una aplicació destinada al món del fitness amb Machine Learning

Data inici oferta: 12-07-2023     Data finalització oferta: 12-03-2024

Estudis d'assignació del projecte:
Tipus: Individual
Lloc de realització: EETAC
Paraules clau:
Fitness, Machine Learning, Development, Backend, Frontend
Descripció del contingut i pla d'activitats:
Overview (resum en anglès):
In recent years, a growing awareness of the importance of a healthy lifestyle has fueled a surge in the demand for personal trainers. The ongoing COVID-19 pandemic has further emphasized the importance of accessible fitness solutions. With lockdowns and restrictions limiting traditional gym access, individuals have sought alternative means to maintain their health and well-being. Fitness applications, offering at-home workouts and virtual coaching, have become essential tools for many during these challenging times. The pandemic has, in essence, served as a propulsor, encouraging a broader demographic to engage in regular workouts and adopt a healthier lifestyle.

Recognizing these challenges, the development of a fitness application becomes pivotal in bridging fitness enthusiasts a professional guidance along workouts. Many individuals aspiring to go to the gym lack the necessary knowledge or financial means to hire a personal trainer. A fitness application, particularly one developed in Swift with embedded machine-learning capabilities, can address these handicaps effectively acting as a virtual personal trainer, thus, offering personal guidance when doing specific exercises.

Moreover, a fitness application can go beyond the role of a traditional personal trainer and serve as a social network, fostering a sense of community among users. This social aspect encourages motivation, friendly competition, and the exchange of tips and experiences. Additionally, the application can function as a comprehensive registry, allowing users to track their fitness journey, monitor achievements, and set new goals. This multifaceted approach enhances the overall user experience and provides a holistic solution to the challenges faced by fitness enthusiasts.

This document aims to explore and highlight how a fitness application developed in Swift with embedded machine-learning capabilities can effectively serve as a personal trainer, a social network, and a registry app. By providing a thorough account of the theoretical foundations, technical implementations, and forward-looking considerations, this document serves as a valuable resource for comprehending the evolution of our fitness application. It not only captures the essence of our current achievement but also offers a strategic roadmap for future development and enhancements, making it an indispensable reference for stakeholders and developers alike. Finally, addressing the limitations of traditional fitness approaches, this innovative solution strives to make fitness more accessible and inclusive, catering to a diverse audience with varying needs and constraints.

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