Open-source timing and event management system for FPV drone racing using video signal tracking.
RotorHazard is an open-source timing and event management system for FPV drone racing that uses video signal tracking to trigger lap times. It processes signals via a central server, typically a Raspberry Pi, and provides a web interface for race organizers, pilots, and spectators. The system solves the need for accurate, reliable, and affordable race timing without requiring an internet connection.
FPV drone race organizers, clubs, and event coordinators who need a self-hosted, professional timing solution. It's also suitable for DIY enthusiasts interested in building custom race timing hardware.
Developers choose RotorHazard for its high accuracy, offline operation, and extensibility via plugins. Its open-source nature and community support provide a cost-effective alternative to commercial systems, with features like adaptive calibration and live streaming integration.
FPV race timing and event management
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Operates entirely on local hardware without an internet connection, ensuring timing accuracy in remote or indoor venues where connectivity is unreliable, as emphasized in the self-contained feature.
Independently verified for precision, with adaptive calibration that learns per-pilot settings and advanced filtering for both analog and digital video transmitters, reducing missed laps even in multipathing environments.
Supports hundreds of pilots across multiple heats and classes, with comprehensive race formats and statistics, extensible via community plugins for custom functionality.
Generates overlay displays and results pages compatible with OBS, enhancing spectator experience without additional software, as highlighted in the features for streaming support.
Requires building or sourcing custom timing hardware with RX5808 modules and microcontrollers like Arduino or STM32, which can be daunting for users without electronics experience, as noted in the timing hardware section.
The README warns that live documentation may not apply to stable releases, forcing users to navigate between GitHub pages and release notes for accurate setup instructions, increasing the learning curve.
Caps at 16 simultaneous racers, making it unsuitable for large-scale events without additional hardware or workarounds, a stated constraint in the project description.