These patents address the foundational infrastructure of the AR ecosystem, including air rights management, hardware optimization, and non-inventory-based search.
Patents: 7, 13, 21, 26
This patent discloses a system for managing and monetizing digital "air rights" by overlaying a 3D geospatial grid (voxels) onto the physical world. It divides the atmosphere into addressable units and vertical "Digital Columns" that correspond to physical property boundaries. A client-side "Exclusionary Rendering Engine" ensures that AR content is only displayed if the provider has the verified rights to that specific volumetric zone, effectively creating a marketplace for AR real estate.
The current AR ecosystem is an "open loop" where any developer can superimpose digital content (ads, games, or overlays) onto any physical location without the owner's consent. This leads to "Digital Squatting," where a competitor could place a virtual ad directly over a physical store or trade show booth. Existing platforms are siloed and do not recognize physical property rights, creating a chaotic environment with no standardized way to enforce or monetize digital space.
The system introduces Geospatial Tessellation, dividing the world into discrete 3D voxels. It establishes "Usage Tiers" (e.g., Pedestrian, Commercial Signage, and Skyline layers) within these columns. When a user's AR device attempts to render content, the Exclusionary Rendering Engine queries a registry; if the content lacks the proper "Voxel Token," it is automatically clipped or suppressed at the boundary, creating a "Digital Wall" that protects the leased space.
1. Virtual Billboards & Ad Space Leasing
Property owners can lease the "Commercial Signage Tier" of their digital column to advertisers, ensuring only authorized, high-quality AR ads appear on their building.
2. Trade Show & Exhibition Management
Event organizers can sell "Transient Indoor Zones," allowing exhibitors to protect their booth space from digital encroachment by competitors.
3. Personal Privacy Bubbles
Homeowners can establish "Exclusionary Zones" around their property that suppress all unauthorized AR recording or data overlays, ensuring digital privacy in their physical space.
4. R Real Estate Marketplace
A platform for the fractionalized trading and tokenization of volumetric rights, where users can buy, sell, or rent specific altitudes of digital air.
5. Smart City Zoning & Navigation
Municipalities can use "Altitude-Based Tiers" to reserve specific voxels for public safety alerts, municipal signage, or drone flight paths.

The invention coordinates a plurality of AI agents distributed across heterogeneous devices (e.g., TVs, phones, wearables) and remote servers to independently analyze contextual input. An aggregation and convergence control layer iteratively reconciles these outputs based on collaboration rules, trust criteria, and safety policies. No AI output is presented or executed unless it meets specific convergence and authorization requirements.
Modern AI ecosystems often employ multiple independent models that vary in architecture, training data, and accuracy. This leads to inconsistencies, where different models provide contradictory, biased, or "hallucinated" responses to the same query. Existing simple voting or averaging mechanisms fail to account for contextual relevance or safety, creating significant risks when AI is used to trigger real-world actions or display information in a user's field of view.
The system ensures high-confidence results by orchestrating multiple AI agents into a structured "AI Jury" that assigns functional roles like generation, evaluation, and arbitration to reconcile divergent outputs. Reliability is bolstered through Adversarial Dissent, where agents attempt to falsify results to verify robustness, and Safety Gates that vet content for ethical compliance before authorization. To optimize performance, Speculative Consensus initiates validation in the background based on gaze-inferred intent, while Physiological Trust Debt de-weights agents associated with negative physical reactions detected via wearables.
1. "AI Jury" for Safety-Critical Decisions Autonomous systems or industrial monitors require multiple AIs to reach a consensus on hazard alerts before warning a user or halting machinery.
2. Smart Glasses Personal Assistant Gaze-triggered interactions use speculative consensus to ensure that when a user looks at an object, the AI information is already validated and ready to display instantly.
3. Cross-Device "State Handoff" A user can start a complex AI task on a TV and have the entire "reasoning state" seamlessly transfer to their smart glasses as they walk away, without restarting the analysis.
4. Privacy-Preserving Enterprise AI
A "Privacy Guardian" agent sanitizes sensitive data (like faces or financial info) on-device before sending an "intent packet" to cloud-based AI agents for further processing.
5. Multi-Device Health Monitoring
Health recommendations from a wearable are only authorized if multiple AI agents agree and the advice aligns with a pre-validated safety policy.

The system enables a device to proactively generate, explain, and refine conceptual solutions based on interactive user feedback. By maintaining a durable "Intent Representation," the AI moves from simple retrieval to creating and evolving hypothetical software, services, or products through natural language and visual interaction.
Traditional search engines and AI assistants are reactive; they rely on matching a user's query to an existing database of products or answers. This limits discovery to what is already available and often leaves users struggling to articulate complex, non-standardized needs. Furthermore, current "black box" AI models often fail to explain why they suggest a particular solution, leading to a lack of user trust and an inability to refine the suggestion effectively.
The system enables a proactive “Intent-to-Realization” pipeline by shifting from traditional search to Intent-First Discovery, where AI creates conceptual representations of solutions tailored to user needs. These are paired with Explainable Attributes that provide clear, natural-language justifications to build trust. A Durable Intent Representation maintains an evolving model of user goals across sessions, supporting an Interactive Refinement Loop where users adjust attributes through dialogue or gestures to converge on final realization.
1. AI-Driven Product Design & Prototyping
Industrial designers use the system to describe a need, and the AI generates and explains a hypothetical prototype that the designer can then refine in real-time.
2. Hyper-Personalized "Intent" Shopping
Consumers describe a solution to a problem (e.g., "a device to help me manage my unique diet while traveling"), and the AI conceptualizes a bespoke service or product bundle, explaining why each part was chosen.
3. Proactive Software Synthesis
A developer describes a desired function, and the AI generates a conceptual software architecture, explaining the logic of each module before the first line of code is written.
4. Bespoke Travel & Experience Planning
The system generates "hypothetical itineraries" based on vague preferences, explaining the thematic choices and refining the plan as the user interacts with the concepts.
5. Interactive Educational Curricula
Teachers can use the system to conceptualize custom lesson plans that adapt as the student asks "why" or "how" about certain topics, maintaining a persistent model of the student's learning intent.

A unified intelligence layer that integrates real-time perception of physical environments with the analysis of digital content and personal data sources. The system utilizes a wearable or computing device to detect objects and entities, generating real-time insight overlays tailored to the user’s personal context, spatial location, and situational awareness.
Modern computing is largely application-centric, requiring users to manually search across fragmented siloes like emails, documents, and cloud services to find relevant information. This interaction model increases cognitive load and results in personal data being underutilized during real-world interactions with objects, people, or digital content.
The invention establishes a proactive "Second Brain" architecture that correlates physical and digital stimuli with a structured personal knowledge graph. It features Episodic Memory Recall to reconstruct past interactions linked to current stimuli and Privacy-Sphere Enforcement to mask sensitive content from unauthorized observers. A distilled, on-device model ensures intelligence continuity and privacy by performing local contextual inference.
1. Professional Productivity
Proactively surfacing prior communications, related files, and meeting talking points when interacting with collaborators or emails.
2. Procedural Guidance
Delivering real-time, step-by-step instructions for complex tasks (e.g., maintenance or medical) based on the user's current skill level and task context.
3. Environmental Privacy Enforcement
Automatically blurring or masking sensitive AR data when the system detects the gaze or proximity of an unauthorized third party.
4. Enhanced Situational Awareness
Providing "episodic cues" that remind a user of prior events or discussions associated with a specific physical location or object.
5. Collaborative Intelligence
Enabling multiple users to share and aggregate contextual insights during meetings without exposing their raw, private personal data.

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