mirror of
https://github.com/ruvnet/RuView
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rUv
4e6ef76294
Extends R6.2.3 chest-centric placement to union of chest envelopes
across multiple occupants. Practical question: does coverage degrade
gracefully as occupant count grows?
Result: 2D chest-centric + N=5 + multi-subject union = 100% coverage
for households of 1-4 occupants. N=4 knee returns.
| Scenario | # zones | Cov @ N=5 |
|------------|--------:|----------:|
| 1 occupant | 1 | 100% |
| 2 occupants| 2 | 100% |
| 3 occupants| 3 | 100% |
| 4 occupants| 4 | 100% |
4-occupant saturation: N=4 = 99.0% (+26.1 pp marginal), N=5 = 100%,
N=6+ saturated. Knee at N=4 even for 4 occupants.
Cross-eval: single-subject placement gets 70.6% on 4 zones; multi-
subject-optimised gets 100%. +29.4 pp gain from multi-subject
optimisation. CLI MUST accept multiple --target args and compute union.
Why N=4 knee returns: each chest zone is 40x40 cm, fits inside one
Fresnel ellipsoid (~40 cm wide at midpoint of 5 m link). N=4 anchors
give 6 pairwise links, enough to cover 4 disjoint chest zones without
much waste. Chest-centric multi-subject is the SWEET SPOT for Fresnel
envelope geometry.
R6 family complete (9 ticks: R6, R6.1, R6.2, R6.2.1, R6.2.2, R6.2.2.1,
R6.2.3, R6.2.4, R6.2.5). Family's ship recipe:
- 2D chest-centric + multi-subject + N=5 = 100% coverage
Productisation CLI spec (50 LOC over original R6.2):
wifi-densepose plan-antennas
--room W H [Z] # 2D or 3D
--target NAME X Y W H [DX DY DZ] # repeatable
--target-mode {body, chest} # R6.2.3
--freq-ghz F
--n-anchors N # auto-saturation if omitted
--restarts K
Honest scope: 2D only (3D multi-subject = mechanical extension), static
positions, single 5x5 m geometry, greedy with 4 restarts, 4 occupants
max tested.
Composes:
- R6.2 / R6.2.3 direct extension (single -> multi)
- R6.2.2 / R6.2.4 same saturation behaviour
- R14 V1/V2/V3 in households of 2-4 use this recipe
- R3 / ADR-024 per-subject identity + multi-subject placement
- ADR-105/106/107 federation orthogonal
- R12 PABS multi-subject coverage = multi-subject intrusion detection
Coordination: ticks/tick-27.md, no PROGRESS.md edit.
152 lines
2.3 KiB
JSON
152 lines
2.3 KiB
JSON
{
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"room": {
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"width_m": 5.0,
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"height_m": 5.0
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},
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"freq_ghz": 2.4,
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"scenarios_n5": [
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{
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"scenario": "1 occupant (chair)",
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"n_zones": 1,
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"total_zone_area_m2": 0.16000000000000003,
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"coverage_n5": 1.0,
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"best_anchors": [
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[
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5.0,
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3.25
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],
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[
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0.0,
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1.25
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],
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[
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2.0,
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5.0
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],
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[
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0.0,
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0.0
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],
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[
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0.0,
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5.0
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]
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]
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},
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{
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"scenario": "2 occupants (chair + bed)",
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"n_zones": 2,
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"total_zone_area_m2": 0.4,
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"coverage_n5": 1.0,
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"best_anchors": [
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[
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5.0,
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3.25
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],
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[
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0.0,
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1.25
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],
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[
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5.0,
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0.5
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],
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[
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2.0,
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5.0
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],
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[
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0.0,
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0.0
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]
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]
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},
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{
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"scenario": "3 occupants (chair + bed + desk)",
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"n_zones": 3,
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"total_zone_area_m2": 0.48000000000000004,
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"coverage_n5": 1.0,
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"best_anchors": [
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[
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5.0,
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3.25
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],
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[
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0.0,
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1.25
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],
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[
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2.0,
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5.0
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],
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[
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5.0,
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0.5
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],
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[
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0.0,
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0.0
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]
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]
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},
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{
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"scenario": "4 occupants (+ 2nd chair)",
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"n_zones": 4,
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"total_zone_area_m2": 0.6400000000000001,
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"coverage_n5": 1.0,
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"best_anchors": [
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[
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3.0,
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0.0
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],
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[
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2.5,
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5.0
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],
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[
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0.0,
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3.75
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],
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[
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4.25,
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5.0
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],
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[
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0.75,
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5.0
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]
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]
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}
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],
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"saturation_4subj": [
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{
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"n_anchors": 2,
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"coverage": 0.14516129032258066
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},
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{
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"n_anchors": 3,
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"coverage": 0.7290322580645161
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},
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{
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"n_anchors": 4,
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"coverage": 0.9903225806451613
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},
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{
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"n_anchors": 5,
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"coverage": 1.0
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},
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{
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"n_anchors": 6,
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"coverage": 1.0
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},
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{
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"n_anchors": 7,
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"coverage": 1.0
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}
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],
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"cross_eval": {
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"single_opt_on_multi": 0.7064516129032258,
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"multi_opt_on_multi": 1.0,
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"gain_pp": 29.354838709677423
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}
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} |