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F1 Telemetry Analysis using AWS

Project Description

The F1 Race Data Streaming and Visualization System is a real-time application designed to simulate, process, and visualize Formula 1 race data. It leverages AWS services such as Kinesis, Lambda, SNS, and S3, along with web technologies like Flask, to provide a dynamic, interactive dashboard for tracking driver positions, lap times, tyre details, and other race statistics.

The system uses FastF1 to simulate a race session and streams real-time race data into an AWS Kinesis Data Stream. The data is processed through multiple Lambda functions and sent to a Flask web server, which updates a live dashboard showing drivers' positions, lap numbers, tyre compounds, tyre ages, and more.

Architecture Diagram

Architecture-Diagram

Key Components

Race Simulation and Data Streaming simulate-race.py

  • This script uses the FastF1 library to simulate the race session.
  • Data points such as driver name, lap number, position, tyre compound, tyre age, and sector times are extracted and sent to an AWS Kinesis Data Stream in near real-time.
  • The simulation runs at 10x speed for faster updates.
  • Data is continuously sent to Kinesis for further processing by AWS Lambda.

Data Processing with AWS Lambda

There are two Lambda functions:

  1. Driver Position Update Lambda:

    This Lambda function listens to the Kinesis Data Stream, decodes the race data, and forwards the driver position details to a Flask web server via an HTTP POST request.

  2. Fastest Lap Detection Lambda:

    This Lambda function processes race data to detect the fastest lap. When a new fastest lap is detected, an SNS (Simple Notification Service) alert is triggered, sending the details of the fastest lap.

Web Server with Flask

  • A Flask-based web server hosts a live dashboard that visualizes driver positions and race updates.
  • It receives data from the Lambda function via HTTP POST requests and updates the current standings.
  • A HTML table displays race data (driver, team, position, lap number, tyre compound, and tyre age), refreshing every 5 seconds to show real-time updates.
  • The Flask web server uses the /positions endpoint to fetch sorted driver positions.
  • A simple HTML page is used for the front-end, which continuously fetches updated driver positions every 5 seconds using JavaScript.
  • Data is displayed in a tabular format, with real-time updates on driver positions, tyre compounds, and tyre ages.