Edge Computing Core
Documentation for Proprietary Task-Based OS environments. Optimized for real-time sensor processing and high-velocity data ingestion.
1. OS Scheduling & Architecture
Unlike general-purpose kernels, this system utilizes a Microkernel architecture to isolate tasks and ensure deterministic execution times.
Hard Real-Time
Guaranteed task completion windows for critical radar pulses.
Resource Isolation
Independent memory pools for AV processing and telemetry.
2. Radar Detection & Tracking
The OS handles signal processing through a specialized hardware-abstraction layer to achieve sub-millisecond response times.
- Pulse-Doppler Processing: Real-time FFT analysis for velocity tracking.
- Multi-Sensor Fusion: Synchronized ingestion of Radar, LiDAR, and Camera data.
- Edge Tracking: Localized Kalman filtering to reduce cloud dependency.
3. Big Data & Real-Time AV
Processing high-definition media alongside sensor data requires Zero-Copy Memory management to prevent CPU bottlenecks.
| Parameter | Optimization Strategy | Result |
|---|---|---|
| AV Pipeline | Unified Memory Access (UMA) | Zero-Copy |
| Radar Logic | FPGA-Direct Interrupts | < 10μs |
| Data Logging | Delta Encoding / Compression | -85% Load |
| Sensor Sync | PTP / Time-Sensitive Networking | Nano-sync |