Real-Time Video Anomaly Detection System
Design a high-scale, real-time video surveillance system capable of detecting anomalous activities across 10,000+ camera streams. The system must process high-resolution temporal data with sub-2-second end-to-end latency. Detail your approach to handling massive data throughput, the choice of ML paradigm (supervised vs. unsupervised) given the rarity of anomaly labels, the trade-offs between edge and cloud compute, and how you ensure system reliability and model freshness in changing physical environments (e.g., lighting, weather).
3D-Convolutional AutoencoderVision TransformerTensorRTKafkaFlinkOpenVINOPyTorchS3GMMONNX
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