Integrations & AI Metadata Pipeline Overview
RUSEON Core is engineered as an open, extensible video data platform. It seamlessly connects camera video infrastructure with external AI inference engines, IoT message brokers, edge analytics services, and enterprise notification systems without introducing CPU bottlenecks.
Integration Capabilities Matrix
| Subsystem | Communication Protocol | Typical Latency | Key Use Case | Documentation |
|---|---|---|---|---|
| AI Metadata Pipeline | gRPC / Protocol Buffers | < 10 ms | Synchronizing real-time bounding boxes and AI classifications with video feeds | AI Metadata Guide |
| MQTT Publishing | MQTT 3.1.1 / 5.0 | < 25 ms | IoT and SCADA telemetry, industrial camera state broadcasting | MQTT Guide |
| Webhooks Engine | HTTP/1.1 & HTTP/2 POST | < 100 ms | Dispathing system alerts, motion alarms, and retention events to web endpoints | Webhooks Guide |
| Internal Event Bus | In-Memory Go Channels | < 1 ms | Thread-safe, non-blocking intra-process event routing | Event Bus Guide |
Key Architectural Highlights
- Zero-Copy Frame Extraction: The gRPC Frame Service allows external Python, C++, or Go AI workers to ingest raw video frames directly without duplicate disk reads or CPU transcoding.
- Synchronized Overlay Delivery: Injected AI metadata (such as detected bounding boxes, license plates, or human poses) is synchronized with video frames and delivered via:
- WebRTC DataChannel: Sub-100ms real-time bounding box rendering over HTML5 Canvas.
- HLS WebVTT: Standardized subtitle/metadata tracks for standard web players.
- Resilience & Fault Isolation: The Webhooks engine features an automated Circuit Breaker to prevent failing third-party endpoints from exhausting server memory or thread pools.