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ruv
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Deep SOTA research into WiFi sensing domain gap problem (2024-2026). Proposes 7-phase implementation: hardware normalization, domain-adversarial training with gradient reversal, geometry-conditioned FiLM inference, virtual environment augmentation, few-shot rapid adaptation, and cross-domain evaluation protocol. Cites 10 papers: PerceptAlign, AdaPose, Person-in-WiFi 3D (CVPR 2024), DGSense, CAPC, X-Fi (ICLR 2025), AM-FM, LatentCSI, Ganin GRL, FiLM. Addresses the single biggest deployment blocker: models trained in one room lose 40-70% accuracy in another room. MERIDIAN adds ~12K params (67K total, still fits ESP32) for cross-layout + cross-hardware generalization with zero-shot and few-shot adaptation paths. Co-Authored-By: claude-flow <ruv@ruv.net>