EnergieFiets Project (2024-2025)

A real-time cycling performance tracking system that reads data from ANT+ sensors (speed, cadence, and power), stores it in InfluxDB, and displays results on an interactive scoreboard.

📋 Project Overview

The EnergieFiets project allows users to:

• Record cycling performance data using ANT+ sensors
• Track speed, cadence, and power output in real-time
• Store user information and results in a database
• View live performance metrics on a scoreboard
• Visualize historical data with Grafana dashboards

🏗️ Architecture

The system consists of:

• ANT+ Sensor Reader: Python script that captures bike speed, cadence, and power data
• Backend API: Flask REST API for managing users and results
• Frontend: React-based scoreboard with real-time updates
• Time-Series Database: InfluxDB for storing sensor data
• Visualization: Grafana for creating performance dashboards
• Data Storage: SQLite for user data and results

🚀 Getting Started

Prerequisites

• Python 3.x
• Node.js and npm
• Docker and Docker Compose
• ANT+ USB stick
• ANT+ compatible sensors (speed/cadence sensor and power meter)

Installation

1. Clone the repository

   git clone <repository-url>
   cd 2425-EnergieFiets

2. Start InfluxDB and Grafana

   cd code
   docker-compose up -d

   • InfluxDB will be available at http://localhost:8086
   • Grafana will be available at http://localhost:3000

3. Install Python dependencies

   cd code/WebApp
   pip install -r requirements.txt

4. Install Frontend dependencies

   cd code/WebApp/react/scoreboard
   npm install

Running the Application

1. Start the ANT+ sensor reader

   cd code
   python antReadCadence.py

2. Start the Flask backend

   cd code/WebApp
   python app.py

3. Start the React frontend

   cd code/WebApp/react/scoreboard
   npm run dev

4. Access Grafana (optional)

   • Navigate to http://localhost:3000
   • Configure InfluxDB as a data source
   • Create dashboards to visualize performance metrics

📁 Project Structure

code/
├── antReadCadence.py          # Main ANT+ sensor reader
├── antTest.py                 # ANT+ testing script
├── docker-compose.yml         # InfluxDB and Grafana services
└── WebApp/
    ├── app.py                 # Flask REST API
    ├── readData.py            # Data reading utilities
    ├── saveToDB.py            # Database operations
    ├── testAverage.py         # Data processing/testing
    ├── requirements.txt       # Python dependencies
    ├── Dockerfile             # Backend container
    └── react/
        └── scoreboard/
            ├── src/
            │   ├── App.jsx              # Main React component
            │   ├── components/
            │   │   └── Scoreboard.jsx   # Scoreboard component
            │   └── api/
            │       ├── api_client.js       # API client
            │       └── results_service.js  # Results service
            ├── package.json         # Node dependencies
            └── Dockerfile           # Frontend container

🔧 Configuration

ANT+ Sensor Configuration

Edit antReadCadence.py to adjust:

• WHEEL_CIRCUMFERENCE_M: Wheel circumference in meters (default: 2.1m)
• RECORDING_DURATION: Recording duration in seconds (default: 10s)
• MIN_POWER_THRESHOLD: Minimum power threshold in watts

Database Configuration

• InfluxDB database name: trainerdata
• SQLite database: trainer.db (auto-created)

📊 API Endpoints

• POST /api/naam - Save user information (name and email)
• GET /api/results - Retrieve performance results
• Additional endpoints available in app.py

🐳 Docker Deployment

The application can be fully containerized using the provided Dockerfiles and docker-compose configuration:

docker-compose up -d

This will start:

• InfluxDB (port 8086)
• Grafana (port 3000)

📝 Data Model

SQLite Tables

• temp_naam: Temporary user information storage
• resultaten: Performance results with averaged metrics

InfluxDB Measurements

• Speed (km/h)
• Cadence (RPM)
• Power (Watts)