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Integrating @schwarztim's PR #491 into main on their behalf — their fork has fallen too far behind for a clean rebase (the PR's commit graph dropped silently during `git rebase origin/main`), so applying as a merge from the fork head to preserve the diff cleanly. What this lands: - `RollingP95` adaptive normaliser for the person-count feature scaling. Streaming P95 over a 600-sample / ~30 s sliding window. Cold-start (<60 samples) falls back to the legacy denominators (variance/300, motion_band_power/250, spectral_power/500) so day-0 behaviour is preserved on every deployment. - `RuntimeConfig` struct + `load_runtime_config` / `save_runtime_config` persisted to `data/config.json`. Exposes `dedup_factor` via REST so multi-node deployments can tune cluster-deduplication without a rebuild, including an auto-tune endpoint that derives optimal dedup from a known person count (calibration mode). - `compute_person_score()` now takes &AppStateInner alongside &FeatureInfo so the adaptive denominators are reachable. All 3 call sites updated. - New `AppStateInner` fields: `p95_variance`, `p95_motion_band_power`, `p95_spectral_power`, `dedup_factor`, `data_dir`. Closes #491. Directly addresses: - #499 (double skeletons, multi-node) — the slot-clustering problem this PR's adaptive normaliser was designed to fix - #519 Bug 1 (ghost person detection on edge-tier 1 & 2 multi-node) - #496 (person count over-reporting on single-room single-person) Verified locally: - cargo check -p wifi-densepose-sensing-server --no-default-features: 1.0s - cargo test -p wifi-densepose-sensing-server --no-default-features --lib: 233/233 passed in 25.0s Co-authored-by: @schwarztim Co-Authored-By: claude-flow <ruv@ruv.net>