Smart Tennis Racket

• student: Stefan-Darius Iordache
• email: stefan.iordache1805@stud.acs.upb.ro
• master: SRIC-1

This project is an application for analyzing tennis shots using a smart racket. It collects motion data using sensors, processes it using a Python server, and displays the analysis on a web interface.

• ESP32 - Microcontroller used for data collection and wireless communication.
• MPU6500 - 6-axis motion tracking sensor (accelerometer + gyroscope).
• Power Supply - 9V battery strapped to the tennis racket.

The MPU6500 is mounted to the tennis racket and connected to the ESP32, which streams sensor data wirelessly.

1. MPU6500 collects accelerometer and gyroscope data.
2. ESP32 transmits data to an InfluxDB time-series database.
3. A CSV file is exported from InfluxDB
4. The CSV file is consumed by a Python server that:
   • Parses the data
   • Detects individual shots
   • Analyzes each shot for:
     1. Spin
     2. Power
5. A web interface queries the Python server and visualizes the analysis using Chart.js.

• Sensor Layer:
  1. MPU6500 (Accelerometer + Gyroscope)
  2. ESP32 (Wi-Fi transmission)

• Data Layer:
  1. InfluxDB (time-series data storage)

• Processing Layer:
  1. Python server
     1. CSV parsing
     2. Shot detection

• Presentation Layer:
  1. Web interface
  2. Chart.js for dynamic visualizations

• Loads sensor data from CSV
• Detects tennis shots using
• Computes:
  1. Spin
  2. Shot power (based on acceleration magnitude)
• Provides API endpoints for the web client to fetch shot data

• Developed in HTML/JavaScript
• Uses Chart.js to display:
  1. Shot timeline
  2. Spin distribution
  3. Power graph
• Connects to Python server via RESTful API to fetch analysis results

• Add Bluetooth or BLE support for local device communication
• Implement live streaming directly to the web client
• Integrate machine learning for more accurate shot detection and classification