How can offline AI be deployed for real-time video analytics?
Offline video analytics deploys computer vision models on edge devices connected directly to camera feeds. NVIDIA Jetson Orin and Xavier or Intel NUC platforms run optimized detection models like YOLOv8 and RT-DETR for object detection, tracking, and classification at 30 or more FPS. DeepStream SDK handles video decoding, inference, and tracking in an optimized pipeline. Applications include perimeter intrusion detection, people counting, license plate recognition, PPE compliance monitoring, and anomaly detection in retail environments. All processing occurs locally with only metadata and alerts transmitted. This is critical for environments where video data is sensitive or bandwidth is limited. TensorRT optimization and INT8 quantization enable running multiple camera streams simultaneously.