Deployment Targets

• Edge devices (NVIDIA Jetson, Intel NCS, Coral)
• On-premises GPU servers (multi-GPU clusters)
• Cloud deployment (AWS, GCP, Azure, private cloud)
• Hybrid edge-cloud topologies
• Offline mode with local inference capability

Inference Optimization

• ONNX Runtime optimization for cross-platform
• TensorRT acceleration for NVIDIA GPUs
• INT8/FP16 quantization for edge performance
• Multi-stream parallel inference pipelines
• Dynamic batching for throughput optimization

Scene-Aware Configuration

• Per-camera detection zone & ROI configuration
• Confidence threshold tuning per class & scene
• Schedule-based model switching (day/night)
• Cascading model pipelines (detect → classify → act)
• Scene-specific post-processing rules

Event Output Pipeline

• REST API event dispatch with retry logic
• MQTT publishing for IoT integration
• Webhook triggers for third-party systems
• gRPC streaming for real-time consumers
• Event buffering & deduplication controls