crashX is a next-generation safety system designed for extreme high-speed sports like skiing, motorcycling, and downhill cycling. By leveraging a high-performance multi-modal sensor stack and real-time edge AI, crashX moves beyond traditional reactive safety devices to provide predictive crash detection—enabling life-saving interventions in the milliseconds before impact.
Most current safety equipment (such as airbag vests) triggers upon impact detection. In high-speed scenarios, this is often too late. crashX analyzes kinetic patterns and environmental proximity to predict an inevitable crash before it occurs.
The crashX core is an edge-computing module driven by a high-frequency MCU (Microcontroller Unit) that synthesizes data from:
- Laser Radar / LiDAR: Continuous 360-degree or forward-facing proximity scanning to detect terrain obstacles and sudden environmental changes.
- High-G IMUs: Industrial-grade 6-axis inertial measurement units for high-precision tracking of acceleration, lean angles, and rotation.
- High-Speed MCU: Orchestrates sub-millisecond data acquisition and local processing to minimize latency.
crashX integrates with external imaging units, such as Insta360 hardware, to provide a visual layer to its prediction model:
- Real-Time Kinematics (RTK): Traces body movement and joint positioning relative to the vehicle or equipment.
- Body Stance Analysis: Deep learning models trained on thousands of "near-miss" and "crash" scenarios identify abnormal body positions (e.g., losing an edge in skiing or high-siding on a motorcycle).
- Anomaly Detection: A specialized Edge ML pipeline that correlates sensor telemetry with visual posture to flag high-probability crash trajectories.
- Alpine Skiing: Detecting high-speed catches and "whiskey-tango" flips before the skier hits the snow.
- Motorcycling: Identifying "high-side" or "low-side" incidents through lean-angle/traction-loss correlation.
- Performance Cycling: Monitoring high-speed stability and obstacle avoidance in peloton or downhill racing.
We believe safety should be collaborative. Our upcoming milestones include:
- v1.0 Schematic Release: Open-source hardware designs for the core MCU and sensor carrier board.
- Training Dataset: Anonymized kinetic and CV datasets for the community to refine crash prediction models.
- API Integration: SDK for triggering 3rd-party safety devices (Airbags, SOS Beacons, and Heads-Up Displays).
crashX: Because milliseconds save lives.