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>
