FitBeast – A Cross-Platform Fitness Monitoring Application Using Flutter & Machine Learning

FitBeast - A Cross-Platform Fitness Monitoring Application Using Flutter & Machine Learning

1 Pratik Kor, 2Keshav Masvale, 3 Rushikesh Karle, 4 Vikrant Khade,

Department of Computer Engineering & Zeal College of Engineering and Research, Pune, India

Objective: FitBeast is an intelligent, cross-platform fitness application designed to help users achieve personalized health goals through data-driven guidance and adaptive machine learning. It establishes a comprehensive user profile, incorporating metrics such as age, weight, and fitness objectives, then leverages K-Means clustering and K-Nearest Neighbors classification to create individualized diet and workout plans. Users actively log daily activities, including meals, workouts, water intake, and sleep patterns, with this data continuously analyzed to monitor progress, adapt recommendations, and dynamically refine future plans. To enhance motivation and engagement, the app features an interactive Challenges module where users participate in administrator-set health goals, with progress automatically tracked from their activity logs. Furthermore, FitBeast integrates robust social functionalities like connections, group chats, and community sharing, fostering a supportive environment for users on their fitness journey. Developed using Flutter for a seamless user interface and Firebase for a scalable, secure backend, FitBeast's core strength lies in its ability to combine real-time fitness tracking with adaptive machine learning to provide highly personalized and actionable health insights.