docs: update README, CHANGELOG, and associated ADRs for MERIDIAN
- CHANGELOG: add MERIDIAN (ADR-027) to Unreleased section - README: add "Works Everywhere" to Intelligence features, update How It Works - ADR-002: status → Superseded by ADR-016/017 - ADR-004: status → Partially realized by ADR-024, extended by ADR-027 - ADR-005: status → Partially realized by ADR-023, extended by ADR-027 - ADR-006: status → Partially realized by ADR-023, extended by ADR-027 Co-Authored-By: claude-flow <ruv@ruv.net>
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# ADR-002: RuVector RVF Integration Strategy
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## Status
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Proposed
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Superseded by [ADR-016](ADR-016-ruvector-integration.md) and [ADR-017](ADR-017-ruvector-signal-mat-integration.md)
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> **Note:** The vision in this ADR has been fully realized. ADR-016 integrates all 5 RuVector crates into the training pipeline. ADR-017 adds 7 signal + MAT integration points. The `wifi-densepose-ruvector` crate is [published on crates.io](https://crates.io/crates/wifi-densepose-ruvector). See also [ADR-027](ADR-027-cross-environment-domain-generalization.md) for how RuVector is extended with domain generalization.
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## Date
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2026-02-28
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# ADR-004: HNSW Vector Search for Signal Fingerprinting
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## Status
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Proposed
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Partially realized by [ADR-024](ADR-024-contrastive-csi-embedding-model.md); extended by [ADR-027](ADR-027-cross-environment-domain-generalization.md)
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> **Note:** ADR-024 (AETHER) implements HNSW-compatible fingerprint indices with 4 index types. ADR-027 (MERIDIAN) extends this with domain-disentangled embeddings so fingerprints match across environments, not just within a single room.
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## Date
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2026-02-28
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# ADR-005: SONA Self-Learning for Pose Estimation
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## Status
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Proposed
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Partially realized in [ADR-023](ADR-023-trained-densepose-model-ruvector-pipeline.md); extended by [ADR-027](ADR-027-cross-environment-domain-generalization.md)
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> **Note:** ADR-023 implements SONA with MicroLoRA rank-4 adapters and EWC++ memory preservation. ADR-027 (MERIDIAN) extends SONA with unsupervised rapid adaptation: 10 seconds of unlabeled WiFi data in a new room automatically generates environment-specific LoRA weights via contrastive test-time training.
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## Date
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2026-02-28
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# ADR-006: GNN-Enhanced CSI Pattern Recognition
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## Status
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Proposed
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Partially realized in [ADR-023](ADR-023-trained-densepose-model-ruvector-pipeline.md); extended by [ADR-027](ADR-027-cross-environment-domain-generalization.md)
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> **Note:** ADR-023 implements a 2-layer GCN on the COCO skeleton graph for spatial reasoning. ADR-027 (MERIDIAN) adds domain-adversarial regularization via a gradient reversal layer that forces the GCN to learn environment-invariant graph features, shedding room-specific multipath patterns.
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## Date
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2026-02-28
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