Video Anomaly Detection From Edge to Cloud With Qdrant - Qdrant

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This post details the implementation of a video anomaly detection system using Qdrant Edge. It describes how Qdrant Edge's two-shard architecture (immutable HNSW for baseline, mutable for live writes) enables on-device, offline vector search for anomaly detection. The system reframes anomaly detection as a nearest-neighbor search problem, indexing embeddings of normal activity and identifying anomalies based on distance from the normal baseline. It highlights the integration with Twelve Labs for video embeddings and NVIDIA Metropolis VSS on Vultr GPUs for cloud-tier processing, and explains the edge-to-cloud escalation strategy for cost and performance optimization.