F1 AI Commentary System

The F1 AI Commentary System is an integrated pipeline that provides real-time and post-race analysis for the F1 22 racing game, leveraging telemetry data captured via UDP, interactive dashboards, and advanced event detection methods to facilitate AI-generated commentary and insights.

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Modules

1. UDP Telemetry Logger

• Purpose:

  • Captures real-time telemetry data emitted by the F1 22 game via UDP.
  • Organizes and stores telemetry data into structured CSV files.

• Key Features:

  • Real-time UDP data collection for multiple telemetry message types (carDamage, carStatus, carTelemetry, lapData, motionData, eventData, sessionData, etc.).
  • Data organized per driver and session.
  • Efficient logging to minimize resource usage during gameplay.

• Usage:

  • Refer to UDP Telemetry Logger README for setup and execution details.

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2. F1 AI Dashboard

• Purpose:

  • Provides an interactive visualization dashboard built using Dash, Plotly, and Flask.
  • Visualizes telemetry data from live UDP streams or pre-recorded CSV data.

• Key Features:

  • Two visualization modes:
    • Real-Time Mode: Direct visualization of live telemetry streams.
    • Log Mode: Visualization of historical data recorded via UDP Logger.
  • Dynamic driver selection for viewing individual telemetry data.
  • Real-time graphical analysis (speed, tire temperatures, throttle/brake usage, G-forces, etc.) with rolling data windows.

• Usage:

  • Detailed instructions available in F1 AI Dashboard README.

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3. Event Detection Telemetry Pipeline

• Purpose:

  • Parses and processes telemetry data to identify key racing events and generates structured JSON output.
  • Designed for efficient real-time performance using multi-threading.
  • Data prepared by this pipeline is optimized for consumption by Large Language Models (LLMs) for commentary generation.

• Key Features:

  • Real-time telemetry parsing and filtering by message type and individual drivers.
  • Structured JSON output optimized for AI model consumption.
  • Multi-threaded implementation ensures high-performance and low latency.

• Usage:

  • For detailed usage instructions, refer to Event Detection Telemetry Pipeline README.

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Coming Soon

LLM Commentary Module

• An advanced commentary generation module utilizing Large Language Models (LLMs).
• Will provide dynamic, real-time race commentary and performance analysis based on parsed telemetry and event detection data.

Stay tuned for updates!

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Setup & Installation

Prerequisites

• Python 3.8 or later
• Dependencies listed in each module's requirements.txt

Installation

git clone https://github.com/yourusername/F1_AI_Commentary_System.git
cd F1_AI_Commentary_System

# Install dependencies for all modules in one go
pip install -r requirements.txt

# Install dependencies for each module
pip install -r UDP_Telemetry_Logger/requirements.txt
pip install -r F1_AI_Dashboard_OOP/requirements.txt
pip install -r event_detection_telemetry/requirements.txt

Running the Project

• Detailed execution instructions are provided within each module's individual README files.

Contribution

• Contributions and improvements are welcome! Please fork the repository and create pull requests with detailed explanations of your changes.

License

• This project is licensed under the MIT License - see the LICENSE file for details.