This project is designed to collect, process, and visualize telemetry data from Formula 1 races using various technologies. The incoming UDP packets from the race are categorized into two distinct data streams: Persistent Data and Real-Time Data.
All F1 Simulation racing series can export race telemetry data in form of UDP Packets. General specification where followed from F1 Official UDP Packets
The project integrates multiple services to collect, process, and visualize telemetry data from Formula 1 races. This data is categorized into two main types:
Real-Time Data : Telemetry data such as car speed, lap times, fuel levels, and battery status is processed and visualized in real-time.
A central Python application captures telemetry packets from the game, listening on localhost:20777. Key data fragments are immediately forwarded to a WebSocket service, where they are displayed in Grafana, providing instant insights during the race.
Persistent Data (Stored in PostgreSQL): Telemetry data is directed to Apache NiFi, which routes the packets to specific Kafka topics. Spark processes this data and relays it to PostgreSQL for long-term storage.
Additionally, some telemetry packets, specifically those tied to the current driver's session, are stored directly in PostgreSQL to capture session-specific details.