caa3b48d0d
Add RF graph theory and minimum cut foundations research
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GOAP Agent 1 output: Graph-theoretic foundations covering max-flow/min-cut
for RF (Ford-Fulkerson, Stoer-Wagner, Karger), RF as dynamic graph with
CSI coherence weights, topological change detection via Fiedler vector and
Cheeger inequality, dynamic graph algorithms, comparison to classical RF
sensing, formal mathematical framework, and 9 open research questions.
Part of RF Topological Sensing research swarm (12 agents).
https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv
2026-03-08 20:57:23 +00:00
80351de3fa
Add resolution and spatial granularity analysis research
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GOAP Agent 9 output: 1,383-line document covering Fresnel zone analysis,
node density vs resolution (16-node/5m room → 30-60cm), Cramer-Rao lower
bounds with Fisher Information Matrix, graph cut resolution theory,
multi-frequency enhancement (6cm coherent dual-band limit), RF tomography
comparison, experimental validation protocols, and resolution scaling laws
(8.8cm theoretical limit).
Part of RF Topological Sensing research swarm (12 agents).
https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv
2026-03-08 20:27:58 +00:00
6482f9ed75
Add contrastive learning for RF coherence research
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GOAP Agent 7 output: 1,226-line document covering SimCLR/MoCo/BYOL for CSI,
AETHER-Topo dual-head extension, coherence boundary detection with multi-scale
analysis, delta-driven updates (2-12x efficiency), self-supervised pre-training
protocol, triplet networks for 5-state edge classification, and MERIDIAN
cross-environment transfer with EWC continual learning.
Part of RF Topological Sensing research swarm (12 agents).
https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv
2026-03-08 20:18:46 +00:00
a3b4590fff
Add CSI edge weight computation research
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GOAP Agent 2 output: ~700-line document covering CSI feature extraction,
coherence metrics (cross-correlation, mutual information, phasor coherence),
multipath stability scoring (MUSIC, ESPRIT, ISTA), temporal windowing
(EMA, Welford, Kalman), noise robustness (phase noise, AGC, clock drift),
edge weight normalization, and implementation architecture showing 32KB
memory for 120 edges within ESP32-S3 capability.
Part of RF Topological Sensing research swarm (10 agents).
https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv
2026-03-08 20:09:07 +00:00
85a93eee39
Add sublinear mincut algorithms research
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GOAP Agent 5 output: 698-line document covering classical mincut complexity,
sublinear approximation (sampling, sparsifiers), dynamic mincut with lazy
recomputation hybrid, streaming sketch algorithms, Benczur-Karger
sparsification, local partitioning (PageRank-guided cuts), randomized
methods reliability analysis, and Rust implementation with const-generic
RfGraph, zero-alloc Stoer-Wagner, SIMD batch updates.
Part of RF Topological Sensing research swarm (10 agents).
https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv
2026-03-08 20:08:25 +00:00
1a3c6b4d11
Add attention mechanisms for RF sensing research
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GOAP Agent 3 output: 1,110-line document covering GAT for RF graphs,
self-attention for CSI sequences, cross-attention multi-link fusion,
attention-weighted differentiable mincut, spatial node attention,
antenna-level subcarrier attention, and efficient attention variants
(linear, sparse, LSH, S4/Mamba). 8 ASCII architecture diagrams.
Part of RF Topological Sensing research swarm (10 agents).
https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv
2026-03-08 20:05:55 +00:00
5e83d70d06
Add transformer architectures for graph sensing research
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GOAP Agent 4 output: 896-line SOTA document covering Graph Transformers
(Graphormer, SAN, GPS, TokenGT), Temporal Graph Transformers (TGN, TGAT,
DyRep), ViT for RF spectrograms, transformer-based mincut prediction,
positional encoding for RF graphs, foundation models for RF sensing, and
efficient edge deployment with INT8 quantization.
Part of RF Topological Sensing research swarm (10 agents).
https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv
2026-03-08 20:05:02 +00:00
e4f82329a9
Add temporal graph evolution & RuVector integration research
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GOAP Agent 8 output: 1,528-line SOTA research document covering temporal
graph models (TGN, JODIE, DyRep), RuVector graph memory design, mincut
trajectory tracking with Kalman filtering, event detection pipelines,
compressed temporal storage, cross-room transition graphs, and a 5-phase
integration roadmap.
Part of RF Topological Sensing research swarm (10 agents).
https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv
2026-03-08 19:11:16 +00:00
d4dc5cb0bc
Merge remote-tracking branch 'origin/claude/use-cases-implementation-plan-tT4s9' into ruvsense-full-implementation
2026-03-01 21:21:24 -05:00
374b0fdcef
docs: add RuView (ADR-028) sensing-first RF mode for multistatic fidelity
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Introduce Project RuView — RuVector Viewpoint-Integrated Enhancement — a
sensing-first RF mode that improves WiFi DensePose fidelity through
cross-viewpoint embedding fusion on commodity ESP32 hardware.
Research document (docs/research/ruview-multistatic-fidelity-sota-2026.md):
- SOTA analysis of three fidelity levers: bandwidth, carrier frequency, viewpoints
- Multistatic array theory with virtual aperture and TDM sensing protocol
- ESP32 multistatic path ($84 BOM) and Cognitum v1 + RF front end path
- IEEE 802.11bf alignment and forward-compatibility mapping
- RuVector pipeline: all 5 crates mapped to cross-viewpoint operations
- Three-metric acceptance suite: joint error (PCK/OKS), multi-person
separation (MOTA), vital sign sensitivity with Bronze/Silver/Gold tiers
ADR-028 (docs/adr/ADR-028-ruview-sensing-first-rf-mode.md):
- DDD bounded context: ViewpointFusion with MultistaticArray aggregate,
ViewpointEmbedding entity, GeometricDiversityIndex value object
- Cross-viewpoint attention fusion via ruvector-attention with geometric bias
- TDM sensing protocol: 6 nodes, 119 Hz aggregate, 20 Hz per viewpoint
- Coherence-gated environment updates for multi-day stability
- File-level implementation plan across 4 phases (8 new source files)
- ADR interaction map: ADR-012, 014, 016/017, 021, 024, 027
https://claude.ai/code/session_01JBad1xig7AbGdbNiYJALZc
2026-03-02 02:07:31 +00:00
c707b636bd
docs: add RuvSense persistent field model, exotic tiers, and appliance categories
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Expands the RuvSense architecture from pose estimation to spatial
intelligence platform with persistent electromagnetic world model.
Research (Part II added):
- 7 exotic capability tiers: field normal modes, RF tomography,
intention lead signals, longitudinal biomechanics drift,
cross-room continuity, invisible interaction layer, adversarial detection
- Signals-not-diagnoses framework with 3 monitoring levels
- 5 appliance product categories: Invisible Guardian, Spatial Digital Twin,
Collective Behavior Engine, RF Interaction Surface, Pre-Incident Drift Monitor
- Regulatory classification (consumer wellness → clinical decision support)
- Extended acceptance tests: 7-day autonomous, 30-day appliance validation
ADR-030 (new):
- Persistent field model architecture with room eigenstructure
- Longitudinal drift detection via Welford statistics + HNSW memory
- All 5 ruvector crates mapped across 7 exotic tiers
- GOAP implementation priority: field modes → drift → tomography → intent
- Invisible Guardian recommended as first hardware SKU vertical
DDD model (extended):
- 3 new bounded contexts: Field Model, Longitudinal Monitoring, Spatial Identity
- Full aggregate roots, value objects, domain events for each context
- Extended context map showing all 6 bounded contexts
- Repository interfaces for field baselines, personal baselines, transitions
- Invariants enforcing signals-not-diagnoses boundary
https://claude.ai/code/session_01QTX772SDsGVSPnaphoNgNY
2026-03-02 01:59:21 +00:00
25b005a0d6
docs: add RuvSense sensing-first RF mode architecture
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Research, ADR, and DDD specification for multistatic WiFi DensePose
with coherence-gated tracking and complete ruvector integration.
- docs/research/ruvsense-multistatic-fidelity-architecture.md:
SOTA research covering bandwidth/frequency/viewpoint fidelity levers,
ESP32 multistatic mesh design, coherence gating, AETHER embedding
integration, and full ruvector crate mapping
- docs/adr/ADR-029-ruvsense-multistatic-sensing-mode.md:
Architecture decision for sensing-first RF mode on existing ESP32
silicon. GOAP integration plan (9 actions, 4 phases, 36 cost units).
TDMA schedule for 20 Hz update rate from 4-node mesh.
IEEE 802.11bf forward-compatible design.
- docs/ddd/ruvsense-domain-model.md:
Domain-Driven Design with 3 bounded contexts (Multistatic Sensing,
Coherence, Pose Tracking), aggregate roots, domain events, context
map, anti-corruption layers, and repository interfaces.
Acceptance test: 2 people, 20 Hz, 10 min stable tracks, zero ID swaps,
<30mm torso keypoint jitter.
https://claude.ai/code/session_01QTX772SDsGVSPnaphoNgNY
2026-03-02 00:17:30 +00:00
91a3bdd88a
docs: Add remote vital sign sensing modalities research (RF, radar, quantum)
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Covers Wi-Fi CSI, mmWave/UWB radar, through-wall RF, rPPG, quantum radar,
and quantum biomedical instrumentation with cross-modality relevance to
WiFi-DensePose ADR-014 algorithms.
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
2026-02-28 14:40:00 +00:00
cc82362c36
docs: Add SOTA research on WiFi sensing + RuVector with 20-year projection
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Comprehensive research document covering:
- WiFi CSI pose estimation SOTA (CVPR 2024, ECCV 2024, IEEE IoT 2025)
- ESP32 sensing benchmarks (88-97% accuracy, 18.5m through-wall)
- HNSW vector search for signal fingerprinting
- ONNX Runtime WASM for edge inference
- NIST post-quantum cryptography (ML-DSA, SLH-DSA) for sensor mesh
- WiFi 7/8 evolution (320MHz channels, 3984 CSI tones, 16x16 MIMO)
- 20-year projection through 2046 with cited sources
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
2026-02-28 09:12:02 +00:00
Claude
ruv