Track_Me
An AI-powered fitness platform that uses computer vision for real-time activity recognition, provides instant feedback, gamifies workouts with scoring and challenges, and supports cross-platform accessibility for an engaging, tech-driven healthy lifestyle.
AI-Powered Fitness Engagement Platform
1. Real-Time AI-Powered Physical Activity Recognition
Utilizes computer vision (PoseNet, MediaPipe, OpenCV) for motion tracking.
Adapts to lighting conditions, camera angles, and body variations for accuracy.
Provides instant feedback (visual/audio cues) for posture correction.
2. Dynamic Scoring Mechanism
AI automatically counts reps for exercises like squats, push-ups, crunches.
Includes visual/audio guides for engagement and motivation.
Tracks workout history and progress for personalized fitness goals.
3. Multiplayer Challenges & Community Features
Leaderboard and reward system for motivation.
Users can create/join groups, challenge friends, and share progress.
Hosts live fitness challenges and events for real-time participation.
4. Cross-Platform Compatibility (Web, Android & iOS)
Web-based access with webcam support.
Mobile apps for Android & iOS with a responsive UI.
Cloud-based data syncing for seamless multi-device access.
5. Technology Stack
AI & Computer Vision: TensorFlow.js, MediaPipe, PoseNet, OpenCV.
Frontend: React.js (Web), Flutter/React Native (Mobile).
Backend: Node.js, Firebase/Supabase for real-time data handling.
Database: PostgreSQL/MongoDB for user activity tracking.
Authentication: Google Sign-In, OAuth, Firebase Auth