Real-time Power Curve Visualization

TODO

• fix IOT connection
• connect to api gateway+dynamodb
• python requirments missing
• upgrade websockets

Iot connection support -startworkout,> Assign id

• finish workout ~~- drive dwelling recovery ~~

Aggregated stats, total distance covered, number of workouts

Interface, Stream data

Match times

• Computer vision -Drive, shins vertical start of drive, acute leg angle arms straight
• end of drive, leg angle 180, elbow almost 90
• recovery :
• end shins vertical

1:2 recovery ratio as stroke rate goes up, pace goes down, increasing time

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Frontend

on raspberry pi

Project Structure

• backend/ - Python WebSocket server
• frontend/ - React application with D3.js visualization

Setup Instructions

Backend

1. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies:

pip install -r requirements.txt

3. Start the WebSocket server:

python backend/server.py

Frontend

1. Install dependencies:

cd frontend
npm install

2. Start the React development server:

npm start

The application will be available at http://localhost:3000

Features

• Real-time power curve data visualization
• WebSocket-based data streaming
• Responsive D3.js chart
• Smooth animations for data updates

Architecture

• Backend: Python WebSocket server streaming simulated power curve data
• Frontend: React application with D3.js for visualization
• Real-time updates using WebSocket connection
• Scalable structure for handling real device data