fix(sensing-server): scale per-node smoothing to actual CSI rate

DEBOUNCE_FRAMES, MOTION_EMA_ALPHA, and BASELINE_EMA_ALPHA were tuned
assuming CSI frames arrive at ~10 FPS (per their own doc comments).
smooth_and_classify_node() runs once per raw incoming UDP frame, and
ESP32-C6 boards measured in the field run at ~48-50 FPS - about 5x
faster. That silently compressed a ~0.4s debounce window to ~0.08s
and a ~1s motion EMA to ~0.2s of real smoothing, letting per-frame
CSI noise flip the reported motion_level almost directly instead of
being smoothed - the reported UI "seizure" of rapid label flicker.

Rather than hardcode a different fixed rate (which would just move
the same bug to whatever chip/capture-mode/config next diverges from
it), derive each frame's effective alpha and frame-count thresholds
from the node's own measured csi_fps_ema, which is already tracked
and burst-filtered elsewhere (observe_csi_frame_arrival). Time
constants are back-derived from the original alphas at the assumed
10 FPS point, so behavior is unchanged for a node at exactly 10 FPS
and now scales correctly to whatever rate a node actually runs at.

smooth_and_classify() (simulated/WiFi-scan sources, already tick-
gated at a known fixed cadence) is unaffected - not exhibiting this
bug, left as-is.

Co-Authored-By: claude-flow <ruv@ruv.net>
(cherry picked from commit d29d9fb02078b066be8557af24023c22e99fa3d1)
This commit is contained in:
Joe committed 2026-09-03 17:12:18 -04:00
1 parent db5a898372
commit 5eb8ddde12
1 file changed
+44 -5
@@ -2639,14 +2639,44 @@ fn raw_classify(score: f64) -> String {
}
/// Debounce frames required before state transition (at ~10 FPS = ~0.4s).
/// Used only by [`smooth_and_classify`] (simulated / WiFi-scan sources,
/// which run on a fixed tick cadence close to this design point).
const DEBOUNCE_FRAMES: u32 = 4;
/// EMA alpha for motion smoothing (~1s time constant at 10 FPS).
/// Used only by [`smooth_and_classify`]; see above.
const MOTION_EMA_ALPHA: f64 = 0.15;
/// EMA alpha for slow-adapting baseline (~30s time constant at 10 FPS).
/// Used only by [`smooth_and_classify`]; see above.
const BASELINE_EMA_ALPHA: f64 = 0.003;
/// Number of warm-up frames before baseline subtraction kicks in.
/// Used only by [`smooth_and_classify`]; see above.
const BASELINE_WARMUP: u64 = 50;
/// Debounce duration required before [`smooth_and_classify_node`] accepts a
/// state transition. Equivalent to the original `DEBOUNCE_FRAMES = 4` at the
/// assumed 10 FPS design point.
const NODE_DEBOUNCE_DURATION_SECS: f64 = 0.4;
/// Time constant for [`smooth_and_classify_node`]'s motion-score EMA,
/// derived from `MOTION_EMA_ALPHA` at the assumed 10 FPS design point
/// (τ = -T / ln(1-α)) so behavior is unchanged for a node running at
/// exactly 10 FPS.
///
/// Frame-count/fixed-alpha smoothing silently scales with actual CSI
/// arrival rate. ESP32-C6 boards observed in the field run CSI at
/// ~48-50 FPS, not the assumed 10 FPS — ~5x faster — which made the
/// debounce trigger in ~0.08s instead of ~0.4s and compressed the "1s"
/// motion EMA to ~0.2s of real smoothing, letting raw per-frame noise
/// flip the reported label almost directly (the reported UI "seizure").
/// Deriving a per-frame alpha from the node's actual measured
/// `csi_fps_ema` makes the smoothing strength invariant to arrival rate.
const NODE_MOTION_TIME_CONSTANT_SECS: f64 = 0.6154;
/// Time constant for [`smooth_and_classify_node`]'s baseline EMA, same
/// derivation as `NODE_MOTION_TIME_CONSTANT_SECS` from `BASELINE_EMA_ALPHA`.
const NODE_BASELINE_TIME_CONSTANT_SECS: f64 = 33.28;
/// Baseline warm-up duration before baseline subtraction kicks in for
/// [`smooth_and_classify_node`] (originally 50 frames at 10 FPS = 5s).
const NODE_BASELINE_WARMUP_SECS: f64 = 5.0;
/// Apply EMA smoothing, adaptive baseline subtraction, and hysteresis debounce
/// to the raw classification. Mutates the smoothing state in `AppStateInner`.
fn smooth_and_classify(state: &mut AppStateInner, raw: &mut ClassificationInfo, raw_motion: f64) {
@@ -2700,18 +2730,27 @@ fn smooth_and_classify(state: &mut AppStateInner, raw: &mut ClassificationInfo,
/// Per-node variant of `smooth_and_classify` that operates on a `NodeState`
/// instead of `AppStateInner` (issue #249).
fn smooth_and_classify_node(ns: &mut NodeState, raw: &mut ClassificationInfo, raw_motion: f64) {
// Derive this frame's effective time step from the node's actual
// measured CSI rate (already EMA-tracked, burst-filtered elsewhere —
// see `observe_csi_frame_arrival`) rather than assuming 10 FPS.
let fps = ns.csi_fps_ema.max(1.0);
let dt = 1.0 / fps;
let motion_alpha = 1.0 - (-dt / NODE_MOTION_TIME_CONSTANT_SECS).exp();
let baseline_alpha = 1.0 - (-dt / NODE_BASELINE_TIME_CONSTANT_SECS).exp();
let debounce_frames_needed = ((NODE_DEBOUNCE_DURATION_SECS * fps).round() as u32).max(1);
let warmup_frames_needed = ((NODE_BASELINE_WARMUP_SECS * fps).round() as u64).max(1);
ns.baseline_frames += 1;
if ns.baseline_frames < BASELINE_WARMUP {
if ns.baseline_frames < warmup_frames_needed {
ns.baseline_motion = ns.baseline_motion * 0.9 + raw_motion * 0.1;
} else if raw_motion < ns.smoothed_motion + 0.05 {
ns.baseline_motion =
ns.baseline_motion * (1.0 - BASELINE_EMA_ALPHA) + raw_motion * BASELINE_EMA_ALPHA;
ns.baseline_motion * (1.0 - baseline_alpha) + raw_motion * baseline_alpha;
}
let adjusted = (raw_motion - ns.baseline_motion * 0.7).max(0.0);
ns.smoothed_motion =
ns.smoothed_motion * (1.0 - MOTION_EMA_ALPHA) + adjusted * MOTION_EMA_ALPHA;
ns.smoothed_motion = ns.smoothed_motion * (1.0 - motion_alpha) + adjusted * motion_alpha;
let sm = ns.smoothed_motion;
let candidate = raw_classify(sm);
@@ -2721,7 +2760,7 @@ fn smooth_and_classify_node(ns: &mut NodeState, raw: &mut ClassificationInfo, ra
ns.debounce_candidate = candidate;
} else if candidate == ns.debounce_candidate {
ns.debounce_counter += 1;
if ns.debounce_counter >= DEBOUNCE_FRAMES {
if ns.debounce_counter >= debounce_frames_needed {
ns.current_motion_level = candidate;
ns.debounce_counter = 0;
}