Jump Rope AI
Challenge
The client envisioned an innovative fitness solution: an AI-powered mobile app that could provide real-time analysis of jump rope techniques using only a smartphone camera. The goal was to empower users—whether beginners or athletes—to improve their form, track progress, and receive instant feedback as if they had a personal coach in their pocket.
The challenge? Develop and train a computer vision model accurate enough to recognize subtle nuances in jumping form, and integrate it seamlessly into a sleek, responsive mobile experience.
The client envisioned an innovative fitness solution: an AI-powered mobile app that could provide real-time analysis of jump rope techniques using only a smartphone camera. The goal was to empower users—whether beginners or athletes—to improve their form, track progress, and receive instant feedback as if they had a personal coach in their pocket.
The challenge? Develop and train a computer vision model accurate enough to recognize subtle nuances in jumping form, and integrate it seamlessly into a sleek, responsive mobile experience.
Solution
Inolab proposed and executed a comprehensive plan to build JumpPro AI, a cutting-edge fitness app combining real-time AI motion tracking with robust analytics and intuitive UI design.
JumpPro AI is poised to become a game-changer in the digital fitness space, offering accessible coaching and performance analytics through the power of artificial intelligence. By combining real-time feedback with sleek usability, the app aims to help users jump smarter, not harder.
Inolab proposed and executed a comprehensive plan to build JumpPro AI, a cutting-edge fitness app combining real-time AI motion tracking with robust analytics and intuitive UI design.
JumpPro AI is poised to become a game-changer in the digital fitness space, offering accessible coaching and performance analytics through the power of artificial intelligence. By combining real-time feedback with sleek usability, the app aims to help users jump smarter, not harder.
Results
Key Features Developed
AI Motion Tracking: Custom-trained AI model to analyze jumping movements and form in real time.
Real-Time Feedback: On-screen insights guide users instantly—highlighting correct and incorrect techniques.
Performance Analytics: Personalized metrics help users monitor progress and improvement trends over time.
User Profiles: Secure accounts allow users to track sessions, achievements, and historical data.
UI/UX Design: A modern, engaging interface built for both novice and advanced users.
Cross-Platform Deployment: One codebase serving both Android and iOS devices efficiently.
Development Approach
1. AI Model Development
Trained with high-quality video data for accuracy in detecting jump rope movement.
Collaborative refinement with the client, including sample movements and iterative feedback.
Early demo delivery to align on precision and feature expectations.
2. Mobile App Engineering
Built using a cross-platform framework for consistent performance on both iOS and Android.
Real-time AI integration leveraging native camera systems.
UI refinements based on best practices in mobile fitness app engagement.
3. Testing & Optimization
Multi-device testing to ensure performance, accuracy, and responsiveness.
Optimized for battery efficiency and various device specifications.
Prepared and assisted with deployment on Google Play and Apple App Store (client developer accounts required).
Key Features Developed
AI Motion Tracking: Custom-trained AI model to analyze jumping movements and form in real time.
Real-Time Feedback: On-screen insights guide users instantly—highlighting correct and incorrect techniques.
Performance Analytics: Personalized metrics help users monitor progress and improvement trends over time.
User Profiles: Secure accounts allow users to track sessions, achievements, and historical data.
UI/UX Design: A modern, engaging interface built for both novice and advanced users.
Cross-Platform Deployment: One codebase serving both Android and iOS devices efficiently.
Development Approach
1. AI Model Development
Trained with high-quality video data for accuracy in detecting jump rope movement.
Collaborative refinement with the client, including sample movements and iterative feedback.
Early demo delivery to align on precision and feature expectations.
2. Mobile App Engineering
Built using a cross-platform framework for consistent performance on both iOS and Android.
Real-time AI integration leveraging native camera systems.
UI refinements based on best practices in mobile fitness app engagement.
3. Testing & Optimization
Multi-device testing to ensure performance, accuracy, and responsiveness.
Optimized for battery efficiency and various device specifications.
Prepared and assisted with deployment on Google Play and Apple App Store (client developer accounts required).