FIREFLY

Data Processing & Visualization Contributions

AI-Powered Personal Training Platform

Project Overview

FireFly is a fitness technology platform offering AI-powered personal training. It uses motion tracking and performance analytics to deliver real-time feedback and personalized workout guidance.

The platform combines personalized workouts, intelligent coaching, and progress analytics to make training more accessible and results-driven.

Key Features

  • Real-time motion tracking
  • AI-powered form analysis
  • Performance analytics
  • Progress visualization

My Data Processing & Visualization Role

Structured Data Processing

Developed scripts to process structured fitness session data including session duration, average rep duration, form scores, and rep counts.

JSON to DataFrame Transformation

Transformed raw JSON data into structured DataFrames for comprehensive analysis and visualization.

Interactive Visualizations

Created interactive and static visualizations using Plotly and Matplotlib to make session performance trends easier to interpret.

Dashboard Integration

Helped shape data into formats that could be integrated into app dashboards and performance summaries.

Data Processing Pipeline

1

Raw JSON Data

Structured fitness session data collection

2

Data Processing

Transform JSON into structured DataFrames

3

Visualization

Create interactive charts with Plotly/Matplotlib

4

Dashboard Integration

Format for app dashboards and summaries

Sample Session Metrics

Session Complete
Data Processed
Duration20 min
Avg Rep Duration7 sec
Form Score85%
Total Reps12
Data Insights
"Performance trends show consistent improvement over last 5 sessions."

Technologies Used

Python (Pandas, NumPy)
Plotly & Matplotlib for visualization
JSON for structured data storage

Key Outcomes

Clear visual representation of workout trends
Improved accessibility of raw training data
Visual insights for user-facing and internal analytics

How It Works

1

User Movement

Real-time motion capture during workouts

2

Motion Tracking

AI-powered form analysis and detection

3

AI Feedback

Intelligent coaching and corrections

4

Progress Insights

Personalized analytics and recommendations

App Interface Concept

Live Session
Form Analysis Active
Reps Completed12/15
Form Score94%
Calories127
AI Feedback
"Great form! Keep your core engaged for the next rep."

Technologies

Industry-standard mobile app frameworks
Machine learning and computer vision tools
Cloud-based infrastructure for scalability

Key Outcomes

Enhanced app responsiveness during workouts
Improved motion tracking integration
More intuitive user feedback loops

Development Process

1
Concept
2
Development
3
Testing
4
Iteration
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