Recent Continuation in Part and International filings:
Phocoustic, Inc. is pleased to announce the filing of CIP-11: “System and Method for Classical Physics-Anchored Drift Benchmarking, Quantum-Conditioned Measurement Clarification, and Assistive Human-Geometry Detection.”
CIP-11 expands the VisualAcoustic.ai platform with a comprehensive physics-anchored framework for drift quantization, stability analysis, and classical admissibility filtering. This continuation strengthens Phocoustic’s intellectual-property foundation by introducing three major advances:
CIP-11 establishes the first formal comparison framework between statistical anomaly models (CNN/PINN) and the physics-anchored drift engine (VASDE/PADR/SOEC). The filing demonstrates that physics-derived drift remains stable under fog, glare, motion, and viewpoint changes—conditions where CNN-based drift maps collapse, hallucinate, or produce inconsistent anomaly scores.
CIP-11 introduces a novel two-tier reference system:
Static Golden Baseline (SGB) for high-precision environments such as PCB inspection, wafer CMP, and connector metrology.
Dynamic Drift-Admissibility Reference (DDAR), a rolling physics-anchored reference that updates only when drift satisfies strict admissibility gates (PADR, SOEC, PEQM, SCVL/Q-SCVL).
This architecture ensures safe, deterministic operation across both controlled and dynamic environments—without relying on adaptive‐pixel backgrounds or learned statistical models.
CIP-11 formalizes the role of Raman drift, nanoscale vibrational signatures, and other quantum-origin physical measurements as purely classical stabilizing channels. These signals strengthen admissibility and lineage validation without invoking quantum computing.
The filing extends physics-anchored drift analysis into human-geometry detection for visibility-degraded environments and assistive navigation. Facial and body-shape geometry is extracted from physical curvature drift, without any biometric identification, pose estimation networks, or CNN-based classification.
CIP-11 harmonizes and captures demonstrations, drift comparisons, XVADA fog/glare examples, PCB/wafer drift benchmarks, and GUI elements published on VisualAcoustic.ai. These public-facing materials are now formally incorporated to preserve priority and secure the expanding footprint of the Visual Acoustic Semantic Drift Engine (VASDE).
CIP-11 reinforces Phocoustic’s
commitment to physics-first sensing.
The system:
Requires no neural training,
Produces deterministic, regulator-friendly outputs,
Avoids AI hallucinations and instability, and
Operates efficiently on CPUs, edge devices, and embedded architectures.
This continuation further differentiates VisualAcoustic.ai from conventional machine-learning approaches, positioning the platform as a physics-anchored foundation for industrial inspection, wafer metrology, assistive navigation, and structured-light analysis.
Champaign, Illinois — VisualAcoustic.ai today announced the filing of CIP-10, a major continuation that transforms the VisualAcoustic platform from a world-leading physics-anchored anomaly detector into the first predictive, goal-aligned, and multi-camera coherent cognitive system for real-world industrial, safety, and perception-assistance environments.
Building upon the dual-domain physics-anchored architecture established in CIP-8 and the governed semantic cognition introduced in CIP-9, CIP-10 expands the VASDE framework with predictive drift forecasting, operator-intent alignment, multi-camera consensus, and grounded symbolic interpretation.
According to the CIP-10 specification, the invention enables a system to:
Anticipate anomaly trajectories in advance
Align drift evolution with operator-defined risk zones
Fuse multiple VISURA camera views into a single meaning
Interpret textual/symbolic cues as semantic risk anchors
Constrain all higher-level inference to physically validated drift evidence
These capabilities dramatically reinforce the company’s core philosophy:
“Every interpretation must arise from real physical change — never statistical guesswork.”
CIP-10 introduces the first
physics-governed predictive drift layer.
PASDE now generates Predictive
Drift Fields and Predictive
Drift Windows, allowing the system to forecast how cracks,
defects, contaminants, or motion fields are likely
to evolve under material and continuity constraints.
This forecast is never statistical — it is derived from:
persistence-anchored drift
PADR gradient stability
dual-domain EMR↔QAIR coherence
multi-frame SOEC validation
(See Fig. 1–2 for predictive field examples in the CIP-10 specification .)
Operators can define semantic regions of risk, priority, or operational
meaning.
PASCE and AIMR evaluate whether drift:
is approaching a critical zone
is diverging toward a safe region
matches known failure patterns
intersects goal-relevant semantic surfaces
This transforms anomaly detection into context-aware hazard forecasting, essential for manufacturing, robotics, and safety systems.
(Fig. 3 in CIP-10 illustrates an SRM with aligned, tangential, and diverging drift paths .)
CIP-10 introduces multi-camera semantic fusion, enabling VISURA units to generate a unified drift and meaning state even when:
visibility is degraded by fog or smoke
one or more cameras are occluded
lighting varies between viewpoints
CCSM establishes multi-camera drift consensus, resolves contradictions, applies trust scoring, and stabilizes semantics across sensors.
(Fig. 4 in the filing shows a fused multi-camera consensus map .)
CIP-10 formalizes how textual objects and symbols in the field of view (e.g., “DANGER 480V”) become grounded semantic anchors that influence:
predictive hazard scoring
semantic polarity
drift weighting
operator intent evaluation
MIPR-A ensures symbols are treated as validated physical evidence, not hallucinated semantics.
(See Fig. 5 showing PQRC→PASCE→MIPR-A transformation .)
CIP-10 adds expanded admissibility layers:
PACF: suppression of contradictions and non-physical interpretations
PEQM: material-constraint reasoning for drift plausibility
T-PACF: final task-bound governance restricting all predictions to safe, operator-approved outputs
As a result, the system cannot produce hallucinations, contradictory forecasts, or physically impossible predictions.
The predictive, multi-camera, and goal-aligned reasoning enabled by CIP-10 unlocks new functionality across:
CMP drift forecasting, over-polish prediction, mark-aware hazard weighting.
Predictive connector fatigue, solder-joint path forecasting, CASC integration.
Predictive obstacle motion analysis, multi-camera collision anticipation.
Stable multi-camera fusion and predictive hazard motion estimation.
Crack growth prediction, thermal drift propagation, rotating system imbalance forecasting.
(Fully detailed in the 12-page Embodiments section of CIP-10 .)
CIP-10 marks the transition of VisualAcoustic.ai from a system that:
detects → to a system that interprets → and now a system that forecasts, contextualizes, and aligns meaning with operator intent.
It builds directly on:
CIP-8 (dual-domain physics anchoring)
CIP-9 (semantic governance & multi-camera consensus)
and sets the stage for the ACI/PEQ-AGI cognitive layer, which is addressed in a separate CIP-10 ACI-focused continuation.
VisualAcoustic.ai announces CIP-10 ACI, the latest advancement in
physics-anchored machine intelligence.
All components of this system operate entirely
in the classical domain.
Any references to “quantum-conditioned” evidence refer only to classical measurements whose physical
origins arise from quantized interactions such as Raman shifts,
fluorescence decay, and photoelectric emission.
CIP-10 ACI formalizes how the VisualAcoustic drift engine transforms classical electromagnetic measurements into stable, physically admissible cognitive states—enabling safe, interpretable, and physics-validated machine reasoning.
At the core of CIP-10 ACI is the Conscious Coherence Envelope (CCE)—a multi-dimensional classical manifold that determines when physical drift is:
persistent across frames,
resonance-aligned in the EMR→QAIR dual domain,
admissible under physical continuity constraints,
stable enough to support semantic meaning.
The CCE ensures that only physically validated drift enters higher-level cognition.
CIP-10 extends the CCE by
incorporating classical
measurements of quantum-origin effects (Raman transitions,
vibrational modes, and photoelectric emission).
This yields the QCCE—a
version of the coherence envelope that admits molecular- and
nanoscale-level stability signatures into the same drift-governance
pipeline.
No quantum computation occurs; the extension merely broadens the evidence sources available for classical reasoning.
CIP-10 introduces the PA-CI layer, a classical meta-stability supervisor that activates only when three independent gating loops overlap:
Monitors global resonance lineage without interpreting it.
Verifies physical directionality and semantic polarity of drift.
Ensures temporal coherence and admissibility across multi-frame sequences.
Only when all three loops align does
PA-CI permit meaning to arise.
This prevents premature interpretation and guarantees physics-locked
cognition.
CIP-10 defines the first fully classical, closed-loop internal consistency system:
Verifies that EMR, QAIR, PADR, PQRC, and RDCM outputs form a contradiction-free lineage.
Extends SCVL by including classical measurements derived from quantum-origin phenomena—QDP, QASI, Q-DRV, and Q-RDCM—within the same consistency loop.
If any stage contradicts physical
lineage or resonance continuity, cognition
is halted automatically.
This provides a hard safety boundary absent in neural AGI systems.
CIP-10 defines several structures that incorporate high-sensitivity classical measurements whose underlying physics is quantum in origin:
Discrete drift units derived from Raman transitions, vibrational modes, or fluorescence lifetimes.
Persistent, repeatable nanoscale signatures that act as stable anchors for meaning.
Resonance vectors and coherence models that fuse classical EMR/QAIR drift with these nanoscale indicators.
These modules do not involve quantum computing or wavefunction
manipulation.
They simply use classical
numerical measurements to enrich drift evidence.
CIP-10 introduces PERC, a new drift-validation channel based on classical photoelectric emission:
threshold-energy shifts,
work-function differentials,
emission-angle signatures.
These signals produce DRV-P vectors that allow the system to detect micro-defects, oxidation, contamination, and stress-layer transitions earlier than conventional imaging.
PERC extends the drift-governance pipeline without departing from classical operation.
CIP-10 culminates in PEQ-AGI, a governed classical reasoning mode that:
activates only when PA-CI is valid,
remains fully bound by T-PACF, CCE/QCCE, and operator-defined intent,
cannot hallucinate or invent ungrounded interpretations,
uses QLE (Quantized Ledger Entries) for full provenance of every decision.
Unlike neural AGI, PEQ-AGI is:
physics-constrained,
internally self-verifying,
traceable and auditable,
safe for high-risk industrial and autonomous tasks.
CIP-10 ACI advances VisualAcoustic.ai into a new class of machine intelligence that is:
safer than neural AGI,
immune to hallucinations,
grounded in physical measurement,
self-consistent and self-verifying,
predictable and fully interpretable.
wafer & CMP nanostructure analysis,
PCB solder-fatigue forecasting,
visibility-degraded driving assistance (XVADA),
robotics & manipulation,
micro-defect and contamination detection,
classical quantum-conditioned industrial inspection,
structural fatigue and stress monitoring.
Champaign, Illinois — VisualAcoustic.ai today announced the filing of CIP-9, a major continuation in the VisualAcoustic patent family that establishes the first multi-camera, physics-governed semantic consensus system designed for high-certainty anomaly detection, industrial monitoring, and safety-critical perception.
Building on the VASDE, PASDE, PADR, and PQRC frameworks, CIP-9 introduces a new class of coherence-validated cognitive subsystems designed to ensure that every semantic interpretation emerges strictly from physically validated drift — never probabilistic inference or statistical hallucination. The CIP-9 specification expands the quantization and governance stack laid out in CIP-8 by incorporating multi-sensor lineage modeling, contradiction filtering, and advanced resonance stability mechanisms.
This patent filing reinforces VisualAcoustic.ai’s mission:
Perception must remain physically grounded, deterministically auditable, and resistant to hallucination—even under complex, multi-sensor conditions.
CIP-9 formalizes the first multi-VISURA fusion framework where:
Independent camera nodes extract PASDE/PADR drift
Each node produces PQRC/SPQRC lineage codes
CCSM aligns these codes into a single, contradiction-free drift consensus
Only physically consistent multi-angle signatures advance to semantic analysis
This enables high-certainty perception for robotics, manufacturing, and autonomous systems.
CIP-9 introduces upgraded semantic readiness (PASCE) and admissibility filtering (PACF) subsystems that:
Compare semantic outcomes across multiple sensors
Reject contradictions or inconsistent drift fields
Enforce physically admissible directionality and stability
Prevent semantic activation when cross-camera physics disagree
The design ensures that “semantic meaning” only forms when all sensors agree.
CIP-9 integrates temporal and multi-view resonance checks, extending the EMR↔QAIR dual-domain stability model with:
Resonant drift continuity calculations
Cross-frame harmonic stability
Multi-camera amplitude-phase alignment
Invalidation pathways for non-resonant drift clusters
This allows the system to suppress noise and uncover hidden or evolving anomalies.
CIP-9 allows drift vectors to be:
Cross-referenced
Time-aligned
Projected forward
Filtered through a multi-camera admissibility manifold
This enables predictive identification of micro-cracks, deformations, solder anomalies, wafer defects, connector warpage, and structural fatigue — even when early signals are too weak for conventional systems.
CIP-9 expands the cognitive governance system to include:
Multi-camera contradiction gates
Cross-node consistency loops
Provenance tracking and drift-ledger retention
Risk-weighted semantic gating
Strict physics-first semantic activation
This ensures that higher-level reasoning layers cannot activate without full multi-sensor stability.
Multi-camera drift consensus improves CMP scratch detection, wafer-edge metrology, and early microstructure instability identification.
CIP-9 enhances detection of solder fractures, connector deformation, and cross-angle reflective anomalies.
Cross-camera PASDE/PACF ensures stable object alignment, safe manipulation, and drift-governed operational decisions.
Multi-angle visibility synthesis strengthens perception in fog, glare, occlusion, and low-light conditions.
Cross-view micro-drift detection identifies cracks, metal fatigue, and load-distribution anomalies with unprecedented sensitivity.
CIP-9 lays the groundwork for the
cognitive meta-stability and quantum drift models later formalized in
CIP-10.
Its innovations in:
multi-camera drift lineage,
admissibility fusion,
multi-view resonance, and
governed semantic activation
provide the framework necessary for the fully physics-anchored cognition stack.
Champaign, Illinois — VisualAcoustic.ai today announced the filing of CIP-8, the latest continuation in its rapidly expanding patent family covering physics-anchored machine perception and drift-based anomaly intelligence. CIP-8 extends the company’s breakthrough VASDE engine (Visual-Acoustic Semantic Drift Engine) with new capabilities in multi-spectral sensing, material-aware drift quantization, and governed semantic interpretation — all designed to deliver safer, faster, and more physically reliable AI for industrial, scientific, and autonomous-systems applications.
CIP-8 reinforces VisualAcoustic.ai’s central principle:
All machine perception must be grounded in validated physical evidence — never statistical guesswork.
By anchoring every inference to real, persistent electromagnetic drift, VASDE avoids hallucinations, improves cross-frame stability, and enables predictive detection of anomalies long before they become visible to conventional vision systems.
CIP-8 formalizes the pairing of visual EMR data with an acoustic-structured numerical domain (QAIR). This dual-domain coherence ensures that only physically persistent signals influence decisions, dramatically reducing noise-driven false positives.
The patent expands the PASDE drift-extraction framework with new rules for persistence, admissibility, temporal stability, and reflectance-based drift quantization (PADR). These advances improve how the system identifies early-stage anomalies in:
Metals
PCB assemblies
Wafer and CMP surfaces
Structured-light industrial environments
CIP-8 strengthens VisualAcoustic’s
proprietary Pattern-Quantized
Ranking Codes, which convert validated drift into ranked,
spatiotemporal structures.
This offers:
Improved anomaly localization
Sub-pixel drift continuity mapping
Frame-to-frame lineage tracking
Operator-defined semantic boundaries
These PQRC structures are foundational for downstream detection, prediction, and controlled reasoning.
CIP-8 introduces expanded semantics-governance mechanisms (PASCE, PACF) that limit interpretation to physically admissible outcomes only. These safeguards ensure that:
Results cannot drift into speculative meaning
Semantic activation always reflects measurable physics
Autonomous decisions remain traceable and auditable
CIP-8 enables a new era of predictive, physics-anchored anomaly detection, including:
PCB solder and connector inspection
Wafer manufacturing and CMP scratch prediction
Industrial robotics alignment and tool monitoring
Visibility-degraded navigation assistance
Structural-fatigue analysis in metals and composites
With its focus on physical drift lineage, CIP-8 allows VisualAcoustic.ai to detect instability long before conventional deep-learning-based systems.
CIP-8 establishes the technical groundwork for the company’s later filings (CIP-9 and CIP-10), which extend the physics-anchored approach into multi-camera consensus, quantum-assisted drift evaluation, and governed high-level reasoning.
By introducing richer quantization structures and expanded admissibility rules, CIP-8 ensures that future cognitive layers remain rooted in verifiable physics.
VisualAcoustic.ai is developing the world’s first Physics-Anchored Perception Engine, enabling industrial, scientific, and autonomous systems to interpret the world through validated physical drift — not statistical guesses. The company’s VASDE technology offers unprecedented stability, safety, and predictive capability across multi-modal sensing environments.
November 2025 — Champaign, Illinois — Phocoustic, Inc. today announced the international filing of its Patent Cooperation Treaty (PCT) application entitled “System and Method for Physics-Informed Anomaly Detection and Semantic Drift Classification Using Quantized Drift Vectors.” This filing extends the VisualAcoustic Semantic Drift Engine (VASDE) portfolio beyond the United States, establishing worldwide priority for the company’s physics-informed approach to explainable artificial intelligence.
The PCT submission unifies a multi-year Continuation-in-Part sequence (CIP1–CIP7) and the U.S. Non-Provisional 19/225,716, consolidating innovations in Quantized Acoustic-Inferred Representation (QAIR), Physics-Anchored Drift Reduction (PADR), and Pattern-Quantized Ranking Code (PQRC). These modules transform optical and acoustic data into structured, persistence-validated evidence frames that enable transparent anomaly detection across manufacturing, transportation, and perception-assistive domains.
Key advances in the PCT include Quantized Laser-Structured Recall (QLSR) for spatial memory, Project-Specific Semantic Sphere (PSSS) for domain adaptation, and Compliance-Adaptive Feedback (CAF) for auditable decision governance. Together they form a globally patent-protected foundation for Phocoustic Signal Science (PSS)—a discipline defining how light and sound can be fused into quantized semantic intelligence.
By filing internationally, Phocoustic positions VASDE as a cross-domain standard for physics-anchored, explainable AI, addressing critical needs in semiconductor inspection, autonomous mobility, and assistive perception systems. The PCT ensures that the VisualAcoustic architecture, first conceived in early 2025, remains protected as it scales toward commercial deployments under VisualAcoustic.ai and future Phocoustic-licensed platforms.
This milestone solidifies Phocoustic’s commitment to globally advancing transparent, auditable AI that transforms raw signals of the physical world into governed meaning.
November 2025 — Champaign, Illinois — Phocoustic, Inc. today announced the filing of Continuation-in-Part Application No. CIP-7, extending the VisualAcoustic Semantic Drift Engine (VASDE) patent family. This filing consolidates and advances prior disclosures (QAIR, PADR, PQRC, SOEC, and XVTA) into a unified framework of governed, physics-anchored semantic reasoning. CIP-7 formally bridges Phocoustic Signal Science (PSS) with domain-specific governance, enabling quantized, compliance-aware decision systems for industrial, vehicular, and perceptual environments.
Building upon earlier Continuations (CIP-3 through CIP-6), CIP-7 introduces Autonomous Governance Synchronization, Adaptive Drift Arbitration, and an extended Quantized Laser-Structured Recall (QLSR) layer for spatial memory and drift persistence. The new filing codifies the role of Phocoustic Compliance Architecture, integrating Corrective-Policy Layers (CPL), Compliance-Adaptive Feedback (CAF), and Prompt Arbitration (PAIL) into a closed semantic feedback loop. This transforms VASDE from a detection framework into a full governance engine capable of traceable decision execution across multi-modal sensor domains.
CIP-7 also broadens apparatus coverage under the Extended VisualAcoustic Platform (XVAP)—including interchangeable VISURA bays for visible, infrared, ultraviolet, and structured-light acquisition—and strengthens interoperability with transformer-based semantic classifiers (XVTA). Each module now operates under Protocol 100.1+, ensuring synchronized metadata exchange and timestamped compliance integrity.
The filing underscores Phocoustic’s leadership in physics-informed explainable AI, replacing opaque probability models with quantized, persistence-validated drift reasoning. By fusing optical, acoustic, and semantic layers, VASDE establishes a technical standard for transparent automation—scalable from wafer metrology to autonomous mobility and assistive perception.
Phocoustic’s CIP-7 marks a milestone in establishing Phocoustic Signal Science as a new scientific discipline—where every anomaly, from nanometer-scale wafer drift to macro-scale environmental change, is measured, remembered, and governed through quantized semantics.
Champaign, IL — October 2025 — Phocoustic Inc., the company behind the VisualAcoustic.ai platform, today announced the filing of its sixth Continuation-in-Part (CIP-6) patent application with the United States Patent and Trademark Office. The new filing expands the company’s protection around Dual-Wave Coherence (DWC) — a breakthrough method that couples electromagnetic and acoustic energy domains to achieve persistence-anchored sensing and self-verifying data integrity.
CIP-6 extends earlier Phocoustic patents covering physics-informed anomaly detection, quantized signal processing, and governed data provenance. The disclosure introduces a fully unified framework that links optical capture, acoustic resonance, and ledger-based governance into a single, self-calibrating measurement system. The result is an architecture capable of converting light into structured, auditable meaning — transforming observation itself into a form of reliable evidence.
“CIP-6 marks the moment where our Dual-Wave science becomes a commercial platform,” said Stephen Francis, Phocoustic’s founder and lead inventor. “We’ve proven that meaningful sensing requires more than data; it requires physical coherence that can be measured, verified, and governed. This filing secures that principle.”
The CIP-6 specification details:
Dual-Wave Coherence (DWC): Real-time transformation of transverse light waves into longitudinal acoustic persistence for drift-free sensing.
PADR (Persistence-Anchored Drift Reduction): A quantization engine that converts frame-to-frame variation into stable, physics-validated signals.
ARC (Adaptive Resonance Calibration): Automatic phase alignment between optical and acoustic channels.
PLM (Provenance Ledger Manager): A secure governance layer recording every quantized event as verifiable evidence.
Assistive and Industrial Embodiments: Applications spanning PCB inspection, biomedical imaging, autonomous navigation, and perceptual-assist devices such as PhoScope and PhoSight.
The filing strengthens Phocoustic’s growing patent family that now covers:
Industrial and manufacturing process control
Biomedical and scientific instrumentation
Human-assistive and environmental sensing
Governance-grade data verification and compliance
Together, these patents establish a new class of physics-anchored AI, designed to bring explainability and trust to machine perception.
Phocoustic Inc. is a deep-technology company pioneering phocoustic signal science — the fusion of photonics and acoustics into coherent, self-governing systems for vision, sensing, and human-machine understanding. Its VisualAcoustic.ai platform converts multi-spectral optical data into acoustic-structured intelligence for industrial, medical, and assistive applications.
Phocoustic, Inc. is establishing an entirely new scientific and commercial domain known as Phocoustic Signal Science (PSS) — where light and sound operate together to transform how change in the physical world is measured, interpreted, and governed.
Traditional “optics-only” systems stop
at reflection and brightness.
Phocoustic technology goes further: it converts electromagnetic
variation into persistence-anchored
acoustic structure, creating measurable continuity that light
alone cannot provide.
This Dual-Wave Coherence framework allows every detected event to carry
its own physical proof, semantic meaning, and compliance record — a
combination no optical platform can replicate.
Through our Visual-Acoustic Semantic Drift Engine (VASDE)
and its core modules (QAIR → PADR → PQRC → SOEC → CRE), Phocoustic
delivers a traceable pathway from raw sensor data to governed
decision-making.
The result is an explainable, physics-anchored foundation for anomaly
detection, quality control, and human-assistive perception across
industrial, biomedical, and environmental domains.
Phocoustic
isn’t improving vision — it’s redefining measurement itself.
By establishing the first governed, dual-wave signal architecture, we
ensure that persistence-anchored quantization becomes the new standard
of trust in machine perception.
New patent filing formalizes Protocol 100.1 and introduces Pho-Sight™/Pho-Scope™ operator interfaces for auditable, human-in-the-loop governance
[Date:] October 12, 2025 — Phocoustic, Inc. today announced that it has filed CIP5, a continuation-in-part patent application that extends the company’s Visual-Acoustic Semantic Drift Engine (VASDE) with an auditable metadata backbone (Protocol 100.1) and new operator-advisory interfaces (Pho-Sigh and Pho-Scope). The filing focuses on closed-loop industrial process control and operator training, bringing explainability and compliance to automation workflows without relying on opaque black-box inference.
What CIP5 covers
Protocol 100.1: a standardized semantic-synchronization layer that time-stamps, authenticates, and distributes quantization and compliance metadata across VASDE modules for traceable governance.
Closed-loop governance stack: Corrective Policy Layer (CPL), Compliance-Adaptive Feedback (CAF), and Control Feedback Layer (CFL) to validate anomalies and deliver audited actions.
Pho-Sight™ & Pho-Scope™: multisensory interfaces that translate quantified drift into acoustic, visual, or tactile cues for operator training, validation, and accessibility.
Physics-anchored quantization: DDNL, PADR, PQRC, and SOEC modules that elevate persistent, physically meaningful signals and suppress noise—improving safety and reducing false positives.
“CIP5 is about trust,” said [Founder/CEO Name], founder of Phocoustic. “Protocol 100.1 and our operator interfaces make every step—from detection to decision to actuation—explainable, auditable, and human-centric.”
“Manufacturers want real-time control without sacrificing compliance,” added [Title, Exec Name]. “CIP5 shows how VASDE’s physics-anchored approach can govern automation safely, with operators in the loop.”
Why it matters
Explainability by design: VASDE encodes anomalies as persistence-validated drift rather than ad-hoc scores, enabling reasoned, reviewable actions.
Compliance and auditability: Protocol 100.1 and PAIL (Phocoustic Audit Integrity Layer) sign and time-stamp events for regulatory traceability.
Operator readiness: PhoSight™/PhoScope™ convert complex metrics into intuitive cues, accelerating training and acceptance on the plant floor.
Scalable across domains: While CIP5 centers on industrial process control, the underlying methods support biomedical, optical/spectroscopic, and navigational applications.
About
the filing
CIP5 extends Phocoustic’s patent family with system and method claims
for metadata-synchronized,
closed-loop control and operator
advisory. The application was filed with the United States Patent and Trademark Office (USPTO).
A patent is pending;
grant is not guaranteed.
VisualAcoustic’s core engine, the VisualAcoustic Semantic Drift Engine (VASDE, formerly VAAD), is built on the belief that light — in all its spectral forms — is the richest source of information in the physical world. But without structure, light remains silent. VASDE transforms light into acoustic-structured, quantized representations that enable explainable interpretation of drift, anomaly, and intent. Through this architecture, light becomes language — and observation becomes optimization.
With the CIP4 extension, VASDE now advances beyond detection into adaptive governance. New layers — including Differential Drift Normalization (DDNL), Adaptive Threshold Control (ATC), and Operator-Advisory feedback (CPL, CAF, OAL) — bring dynamic calibration, human-in-the-loop guidance, and compliance-linked control to every decision cycle. This architecture allows thresholds and corrective responses to evolve statistically over time while maintaining full traceability and operator authority.
The system described herein is
subject to U.S. patent application protection:
U.S. Patent Pending
Application No. 19/225,716 and Continuation-in-Part filings including
CIP4.
Unauthorized reproduction may infringe pending rights. VASDE™.
Introducing: Phocoustics. A new branch of signal science — the fusion of photonic and acoustic analysis that transforms visual patterns into structured, sound-based representations. At VisualAcoustic.ai, this technology powers real-time, physics-aware anomaly detection by converting pixel drift and structural shifts into acoustic signals, enabling intuitive insights across manufacturing, inspection, and safety-critical environments — now strengthened by adaptive normalization, threshold evolution, and operator-advisory intelligence introduced through CIP4.
. See Phocoustic.comExtensive prior-art analysis confirms that while multi-spectral imaging and AI-driven inspection are well established, no existing system directly converts visual signals into acoustic-structured representations. Earlier patents and academic works focus on hyperspectral imaging, physics-informed machine learning, and transformer-based anomaly detection in manufacturing or biomedical contexts. However, these systems typically treat images as static data, lacking the persistence validation, quantized acoustic mapping, and compliance-adaptive feedback that define VisualAcoustic.ai’s approach.
The VisualAcoustic Semantic Drift Engine (VASDE) introduces a new signal discipline where light—visible, infrared, ultraviolet, or structured—is reformulated as drift-anchored acoustic patterns. This physics-informed encoding (QAIR → PADR → PQRC → SOEC) bridges optical coherence and acoustic persistence to expose subtle instabilities long before failure.
Through its CIP4 continuation, VASDE now adds adaptive governance: dynamic normalization, feedback-driven thresholds, and operator-advisory control. Together, these functions distinguish VisualAcoustic.ai as the first explainable, human-supervised architecture that transforms light into a quantized acoustic language for real-time, physics-based anomaly detection.
This overview is for informational purposes only and does not constitute a legal opinion or representation of patent scope.
ACI –
Artificial Conscious Intelligence
A physics-anchored cognitive framework that activates only when drift
evidence is coherent, stable, and physically admissible.
ASD / PASDE
– Physics-Anchored Semantic Drift Extraction
Extracts physically persistent drift using multi-frame, dual-domain
checks that reject noise and non-admissible change.
CAP –
Cognitive Activation Potential
A composite stability score predicting whether validated drift may
produce semantic or task-level meaning.
CCE –
Conscious Coherence Envelope
A multi-dimensional boundary confirming drift resonance, persistence,
and admissibility before higher cognition can activate.
CCSM –
Cross-Camera Semantic Memory
Fuses drift and meaning across multiple VISURA viewpoints into a
unified, contradiction-free consensus.
CRO /
CRO-S – Cognitively Registered Observation (Stable)
A meaning-ready drift state that passes admissibility, resonance, and
persistence checks.
CSW –
Conscious Stability Window
A required timeframe of uninterrupted physical coherence before ACI
can activate.
DDAR –
Dynamic Drift-Admissibility Reference
A rolling physics-anchored reference that updates only when drift
satisfies strict admissibility gates, ensuring safe adaptation under
dynamic conditions.
DRMS –
Drift-Resolved Material Signature
A stable drift fingerprint revealing material state, micro-defects, or
surface condition across frames.
DRV –
Drift Resonance Vector
Encodes harmonic, amplitude-phase stability between EMR and QAIR
domains.
DRV-P –
Photoelectric Drift Resonance Vector
A resonance vector derived from photoelectric emission patterns,
capturing work-function shifts and nanoscale change.
ECE –
Electromagnetic Continuity Encoding
Treats all matter as electromagnetically distinguishable, enabling
universal drift extraction across sensing modalities.
EMR –
Electromagnetic Radiation Layer
Primary optical, IR, and UV input stream used as the foundation for
drift extraction.
GDMA –
Golden Drift Match Algorithm
A precision algorithm comparing live drift patterns against
golden-image drift profiles for high-resolution inspection.
GEQ –
Golden-Edge Quantization
Quantizes canonical edge structures from golden captures, enabling
stable drift comparison even under viewpoint or lighting changes.
INAL –
Intent-Neutral Awareness Layer
A supervisory layer monitoring resonance lineage without producing
meaning or influencing decisions.
MIPR-A –
Meaning-Indexed Perceptual Representation
Grounds textual and symbolic cues (e.g., “DANGER 480V”) into
measurable perceptual geometries that influence risk scoring.
MSC –
Multi-Scale Consistency
An internal validation measure confirming that drift coherence
persists across multiple spatial and temporal scales.
MSDU –
Minimum Semantic Distinguishability Unit
The smallest drift difference reliably detectable and meaningful to
the system.
PACF –
Physical-Admissibility and Contradiction Filter
Rejects interpretations that violate physics, lineage, directionality,
or sensor coherence.
PADR –
Physics-Anchored Drift Reduction
Filters turbulence and highlights physically persistent drift across
sequential frames.
PA-CI –
Physics-Anchored Conscious Intelligence
A meta-stable cognitive state where all resonance, polarity, and
coherence conditions overlap.
PBM –
Physics-Based Masking
A mask-generation technique isolating drift-bearing regions without
neural segmentation.
PERC –
PhotoElectric Resonance Coherence
A photoelectric sensing pathway providing early micro-defect detection
and reinforcing resonance validation.
PEQ-AGI –
Physics-Evidence-Qualified AGI
High-level reasoning bounded to physically verified drift evidence.
PQRC –
Pattern-Quantized Ranking Code
Encodes drift direction, magnitude, and lineage as structured, ranked
arrow-matrix frames.
PSSS –
Project-Specific Semantic Sphere
Maps PQRC structures into task-specific semantic categories.
PSYM –
Persistent Semantic Overlay Module
Renders drift vectors, anomalies, and classifications on the display.
QAIR –
Quantized Acoustic-Inferred Representation
Transforms EMR into an acoustic-like domain for dual-domain drift
confirmation.
QASI –
Quantum-Anchored Semantic Invariant
A quantum-stable vibrational signature used for drift validation.
QCCE –
Quantum-Constrained Coherence Envelope
An extension of CCE integrating quantum-conditioned drift constraints.
QDP –
Quantum Drift Partition
Discrete drift packets derived from Raman or fluorescence transitions.
Q-DRV –
Quantum-Derived Resonance Vector
Captures quantized spectral transitions and coherent quantum drift
behavior.
QLE –
Quantized Ledger Entry
An immutable record of drift events, decisions, and system actions.
Q-RDCM –
Quantum-Resonant Drift Coherence Model
Fusion model combining classical and quantum drift resonance inputs.
Q-SCVL –
Quantum Self-Consistency Verification Loop
Quantum-augmented internal validation cycle confirming cross-domain
coherence.
QLSR –
Quantized Laser-Structured Recall
Structured-light grid storing spatial drift anchors for long-horizon
recall.
RDCM –
Resonant Drift Coherence Model
Evaluates EMR→QAIR harmonic stability to confirm admissible drift.
RSG –
Resonant Stability Geometry
A geometric representation of stable resonance relationships across
frames.
SGB –
Static Golden Baseline
A fixed drift reference profile for controlled, precision domains.
SCVL –
Self-Consistency Verification Loop
Closed-loop check ensuring drift, semantic state, and resonance remain
contradiction-free.
SOEC –
Snapshot Optimization Execution Control
Validates drift persistence across frames, confirming stable
anomalies.
SPQRC –
Sequential Pattern-Quantized Ranking Code
Encodes multi-frame drift evolution for lineage tracking.
SPSI –
Semantic Polarity Stability Index
Evaluates directional drift consistency to confirm valid semantic
interpretation.
SVDM –
Structured-Visibility Drift Mapping
Visibility-aware drift mapping for fog, glare, smoke, and occlusion.
T-PACF –
Task-Bound PACF
Restricts reasoning to operator-approved intent and safety rules.
UDV –
User-Defined Variable
Operator-tuned parameter guiding thresholds, risk scoring, and alert
behavior.
VASDE –
VisualAcoustic Semantic Drift Engine
The full physics-anchored perception and cognition stack.
VISURA –
Visual-Infrared-Structured-light-Ultraviolet-Acoustic Layer
The multi-modal acquisition layer generating raw EMR for drift
extraction.
XVT –
Transformer-Based Semantic Interpreter
Converts PQRC and drift signatures into contextual decisions and
alerts.
The latest Continuation-in-Part (CIP4) filing extends VisualAcoustic.ai’s patented framework into advanced optical and quantum-conditioned sensing domains. Building on the established VISURA → QAIR → PADR → PQRC → SOEC pipeline, the new disclosure introduces structured optical concentrators and quantum-stabilized pathways that enhance the sensitivity and precision of drift-based detection. These optical subsystems focus and normalize incoming light before it enters the semantic drift engine, yielding higher-fidelity quantization and more stable anomaly mapping across wavelength bands.
CIP4 further integrates these capabilities with the platform’s physics-informed encoding, allowing real-time correlation between optical coherence, acoustic inference, and transformer-based semantic reasoning. The result is a unified architecture that detects and classifies micro-scale drift events with unprecedented spatial and spectral clarity—benefiting semiconductor fabrication, photonic manufacturing, and safety-critical navigation.
This continuation demonstrates the platform’s evolution from explainable anomaly detection toward full-spectrum, quantum-ready sensing. By harmonizing optics, acoustics, and semantic intelligence within a single, auditable pipeline, CIP4 advances VisualAcoustic.ai’s mission to make light itself a measurable, traceable language for decision-ready data.
Phocoustic, Inc. is pleased to announce the filing of a new omnibus provisional patent application with the USPTO, titled "Semantic Drift Engine for Multi-Modal Anomaly Detection and Explainable Classification." This application consolidates and extends our prior provisional and non-provisional filings from January through June 2025, including U.S. Provisional Patent Application Nos. 63/743,776; 63/747,288; 63/752,695; 63/788,043; 63/795,070; and 63/795,483, as well as U.S. Non-Provisional Patent Application No. 19/269,723 and related Continuation-in-Part filings (e.g., Ser. No. 19/225,716).
The omnibus disclosure strengthens our patent-pending protections across key innovations in structured VISURA-to-acoustic quantization (QAIR), semantic drift encoding (SDE), and explainable AI-driven classification. It encompasses multi-domain applications, including but not limited to semiconductor wafer inspection, PCB quality control, additive manufacturing, solar observatories, photonic systems, and quantum-enhanced optics. This filing reinforces our commitment to physics-informed, operator-governed anomaly detection technologies that prioritize persistence, directionality, and governance for real-world yield and safety improvements.
This development builds on our July 2025 CIP announcement and aligns with the upcoming Q2 2026 product reveal under the VisualAcoustic Semantic Drift Engine (VASDE) platform. Investors and technical partners interested in collaboration opportunities are encouraged to contact us at info@xvisualaudio.com for more details. Stay tuned for further updates on testing, prototypes, and integration milestones.
USPTO Application Number: 19/269,723
VisualAcoustic Announces Product Reveal Slated for Q2 2026
May 2025 — VisualAcoustic.ai
VisualAcoustic is pleased to announce that a major product reveal is planned for the second quarter of 2026 The upcoming release will introduce a transformative new system built on years of research in semantic anomaly detection, structured signal quantization, and transformer-based classification.
The product, developed under the VisualAcoustic Semantic Drift Engine (VASDE) platform, integrates proprietary methods for real-time sensor fusion, adaptive semantic reasoning, and multi-modal drift interpretation. Its applications span industrial monitoring, accessibility enhancement, defense systems, and AI-based classification pipelines.
To date, the underlying technologies are protected under five filed Provisional Patent Applications (PPAs) and one active Supporting Document (SD), reinforcing VisualAcoustic’s commitment to robust innovation and patent-defensible deployment.
Full product details, demonstration materials, and commercial availability will be announced on VisualAcoustic.com in the coming months. Interested collaborators and prospective partners are encouraged to monitor the site and reach out through the provided contact channels for early engagement opportunities.
About VisualAcoustic
VisualAcoustic is an independent innovation initiative specializing in
AI-driven semantic systems, structured anomaly classification, and
cross-domain signal optimization. Our mission is to make complex
sensor data actionable, explainable, and aligned with human-centered
decision workflows.
XVPP (VASDE Prioritization and Pattern Profiling) expands the platform’s capability into operator-defined drift handling, semantic ranking, and corrective decision execution. Integrated with the Corrective Response Engine (CRE), XVPP enables structured control over anomaly escalation, suppression, and snapshot generation.
XVPP + CRE: From detection to decision — with structured precision.