Derivative works — US Patent 7822639

Defensive Disclosure Document for US Patent 7,822,639

Publication Date: April 28, 2026
Subject: Derivative Methods and Systems for Distributed, Cross-Platform Content Delivery and Monetization

This document discloses novel methods, systems, and applications that build upon, and are derivative of, the core concepts described in US Patent 7,822,639. The purpose of this disclosure is to place these concepts into the public domain, thereby establishing prior art against future patent applications claiming these incremental innovations.

Derivatives of Core Claim 1: Method for Off-site Content Delivery

The core method involves: an agency facilitating identification; a first broadcaster tagging a visitor; and a second broadcaster recognizing the tag and accepting off-site content for that visitor. The following derivatives expand upon this method.

Axis 1: Material & Component Substitution

Derivative 1.1: Quantum Dot and Biometric Tagging

Enabling Description: This method replaces ephemeral software-based "tags" (like HTTP cookies) with persistent, hardware-level identifiers. A user's device (e.g., smartphone, IoT device) is tagged using a unique Quantum Dot (QD) identifier embedded in the display screen or a biometric signature (e.g., a cryptographic hash of a fingerprint or iris scan) captured via device sensors. The "first broadcaster" (a mobile app or secure website) is granted permission to associate its user ID with this hardware-level tag via a secure enclave. When the user interacts with a "second broadcaster" (another app or service), that broadcaster requests authentication against the secure enclave. The "agency," implemented as a decentralized identity oracle, validates the tag and authorizes the second broadcaster to pull personalized content—not just ads, but encrypted messages, access tokens, or verified credentials—linked to the user's activity on the first broadcaster's platform.

Mermaid Diagram:

sequenceDiagram
    participant UserDevice as User Device
    participant FirstBroadcaster as First Broadcaster (App A)
    participant SecureEnclave as Secure Enclave
    participant AgencyOracle as Agency (Decentralized Oracle)
    participant SecondBroadcaster as Second Broadcaster (App B)

    UserDevice->>FirstBroadcaster: Initial Interaction
    FirstBroadcaster->>SecureEnclave: Request to associate UserID with QD/Biometric Tag
    SecureEnclave-->>FirstBroadcaster: Association Confirmed (Tag Set)
    UserDevice->>SecondBroadcaster: Later Interaction
    SecondBroadcaster->>SecureEnclave: Query for associated tags
    SecureEnclave->>AgencyOracle: Validate tag and request content rules
    AgencyOracle-->>SecureEnclave: Return Authorization & Content Pointer
    SecureEnclave-->>SecondBroadcaster: Provide secure token for content
    SecondBroadcaster->>AgencyOracle: Fetch content using token
    AgencyOracle-->>SecondBroadcaster: Deliver personalized content

Derivative 1.2: Server-Side Tagging via Network Infrastructure

Enabling Description: This variation eliminates client-side tagging entirely to bypass cookie blockers and enhance privacy. The "tagging" is performed at the network level by an Internet Service Provider (ISP) or a Content Delivery Network (CDN), acting as the "agency." When a user's traffic is routed to the "first broadcaster," the agency's edge servers log the anonymized user identifier (e.g., a rotating hash of the IP address and user-agent string) and associate it with the first broadcaster's domain. When the same user's traffic is later routed to the "second broadcaster," the agency's edge server recognizes the identifier, matches it to the stored association, and performs real-time content injection or redirection at the TCP/IP or HTTP layer before the data packets reach the user's device. This enables off-site content delivery without any state being stored on the client.

Mermaid Diagram:

flowchart TD
    subgraph Agency_Network_Infrastructure [Agency Network (ISP/CDN)]
        A[User Request for First Broadcaster] --> B{Edge Server Intercept};
        B --> C[Log Anonymized ID & Associate with First Broadcaster];
        C --> D[Forward Request to First Broadcaster];
        E[User Request for Second Broadcaster] --> F{Edge Server Intercept};
        F --> G{Recognize Anonymized ID};
        G -- Yes --> H[Inject/Redirect to Off-site Content];
        H --> I[Forward Modified Request to Second Broadcaster];
        G -- No --> J[Forward Request to Second Broadcaster];
    end
    User --> A;
    User --> E;
    First_Broadcaster[First Broadcaster] <--> D;
    Second_Broadcaster[Second Broadcaster] <--> I;
    Second_Broadcaster <--> J;

Axis 2: Operational Parameter Expansion

Derivative 1.3: Millisecond-Scale Ad Bidding in High-Frequency Trading Environments

Enabling Description: This derivative applies the off-site advertising model to the domain of high-frequency trading (HFT). The "first broadcaster" is a financial data feed (e.g., Bloomberg Terminal, Reuters Eikon) that a trader is viewing. The "tag" is an in-memory flag on the trading platform indicating the trader's current focus (e.g., viewing quotes for AAPL stock). The "second broadcaster" is the trading execution venue itself (e.g., NYSE, NASDAQ). The "agency" is an ultra-low-latency bidding platform. When the trader's algorithm initiates a trade, the "tag" is recognized, triggering a sub-millisecond auction where market makers or liquidity providers ("advertisers") bid to offer a slight price improvement or guaranteed fill ("the off-site content") for that specific trade, based on the knowledge that this trader is highly interested in AAPL at this exact moment. The winning bid is programmatically accepted and alters the trade execution parameters in real-time.

Mermaid Diagram:

sequenceDiagram
    participant Trader as Trader's Terminal
    participant TradingPlatform as Trading Platform (First Broadcaster)
    participant Agency as Low-Latency Agency
    participant MarketMakers as Market Makers (Advertisers)
    participant Exchange as Exchange (Second Broadcaster)

    Trader->>TradingPlatform: Views quotes for AAPL stock
    TradingPlatform->>TradingPlatform: Sets in-memory tag: "Focus=AAPL"
    Trader->>TradingPlatform: Submits trade order for AAPL
    TradingPlatform->>Agency: Signal: Trade initiated with "Focus=AAPL" tag
    Agency->>MarketMakers: Announce micro-auction for AAPL liquidity
    MarketMakers-->>Agency: Submit bids (price improvements)
    Agency->>TradingPlatform: Transmit winning bid to execution logic
    TradingPlatform->>Exchange: Route modified trade order
    Exchange-->>TradingPlatform: Confirm trade execution

Axis 3: Cross-Domain Application

Derivative 1.4: Aerospace - Predictive Maintenance Alerting

Enabling Description: An aircraft's diagnostic system ("first broadcaster") logs a non-critical but anomalous sensor reading from an engine component and "tags" the component's unique serial number in the airline's maintenance database. The "agency" is a global logistics and parts network (e.g., an Airbus or Boeing system). When the aircraft lands at an airport, the airport's ground crew management system ("second broadcaster") queries the maintenance database for the aircraft's status. It recognizes the "tag" on the component and, via the agency's network, automatically displays a maintenance alert ("off-site content") to the ground crew, pre-orders the specific replacement part for delivery to that gate, and schedules a technician, all before the aircraft has even taxied to the terminal.

Mermaid Diagram:

flowchart TD
    A[Aircraft Engine Sensor] --> B(Onboard Diagnostic System - First Broadcaster);
    B --> C{Log Anomaly & Tag Component ID};
    C --> D[Maintenance Database];
    E[Aircraft Lands] --> F(Airport Ground Crew System - Second Broadcaster);
    F --> G{Query Maintenance DB for Aircraft Status};
    G --> H{Recognize Tagged Component ID};
    H -- Tag Found --> I(Agency - Global Parts Logistics);
    I --> J[Pre-order Part for Gate Delivery];
    I --> K[Schedule Technician];
    K & J --> L(Display Alert & Work Order to Ground Crew);

Derivative 1.5: AgTech - Precision Irrigation and Fertilization

Enabling Description: A satellite imagery provider ("first broadcaster") analyzes a farmer's field and identifies a specific quadrant showing signs of nitrogen deficiency, "tagging" that GPS coordinate set in a central farm management platform. The "agency" is an agricultural data clearinghouse. Later, an autonomous tractor ("second broadcaster") performing a different task (e.g., weeding) traverses the field. As its GPS passes through the "tagged" coordinates, the system recognizes the tag via the agency. This triggers the tractor's onboard sprayer to dispense a targeted micro-dose of nitrogen fertilizer ("off-site content"), a function it would not normally be performing. This achieves real-time, variable-rate application of resources based on third-party analysis.

Mermaid Diagram:

graph LR
    subgraph Farm
        A[Satellite - First Broadcaster] -- Scans Field --> B(Farm Mgmt Platform);
        B -- Identifies Deficiency --> C(Tags GPS Coordinates);
        D[Autonomous Tractor - Second Broadcaster] -- Traverses Field --> E{GPS location matches tagged coordinates?};
        E -- Yes --> F[Dispense Nitrogen Micro-dose];
        E -- No --> G[Continue Weeding Task];
        C -- Provides Tag Data --> H((Agency - Ag Data Clearinghouse));
        H -- Syncs with --> D;
    end

Axis 4: Integration with Emerging Tech

Derivative 1.6: AI-Optimized Proactive Content Delivery

Enabling Description: The "agency" is replaced by a predictive AI model. The "first broadcaster" (e.g., a user's streaming music service) doesn't just tag a user's past behavior (e.g., listening to a certain artist), but feeds this data into the AI agency. The AI model predicts the user's next likely context (e.g., likely to go for a run in the next hour). The AI agency then proactively pushes a "tag" to potential "second broadcasters" (e.g., the user's fitness app, smart shoes with IoT sensors). The first of these second broadcasters to detect the predicted context (the fitness app is opened) recognizes the proactive tag and delivers relevant content (e.g., a high-energy playlist sponsored by the music service). This inverts the model from reactive recognition to proactive, AI-driven placement.

Mermaid Diagram:

stateDiagram-v2
    [*] --> Idle
    Idle --> Listening: User plays music on App A (First Broadcaster)
    Listening --> Predicting: Streaming data sent to AI Agency
    Predicting --> Tag_Pushed: AI predicts 'imminent run'
    Tag_Pushed --> [*]: AI pushes tag to Fitness App B (Second Broadcaster)

    state FitnessApp {
        [*] --> Inactive
        Inactive --> Active: User opens app
        Active --> Content_Delivered: App recognizes proactive tag, plays sponsored playlist
    }

Derivative 1.7: Blockchain-Verified Ad Impressions and Payments

Enabling Description: The entire three-party system is implemented as a set of smart contracts on a public blockchain.
1. Contract 1 (Advertiser-Agency): An advertiser deposits cryptocurrency into a smart contract, defining targeting criteria and payment-per-impression.
2. Contract 2 (Agency-First Broadcaster): The "first broadcaster" tags a user by writing an anonymous, encrypted identifier to the blockchain, associated with the user's wallet address. This transaction is the "tag."
3. Contract 3 (Agency-Second Broadcaster): The "second broadcaster" reads the tag from the blockchain when the user connects their wallet. It serves the ad and triggers a function in the smart contract. A decentralized oracle (e.g., Chainlink) verifies the impression occurred. Upon verification, the smart contract automatically executes a three-way micropayment, instantly transferring funds from the advertiser's deposit to the wallets of the first broadcaster, the second broadcaster, and the agency, providing a transparent, immutable, and auditable record of the entire transaction.

Mermaid Diagram:

sequenceDiagram
    participant Advertiser
    participant AdContract as Smart Contract (Agency)
    participant User
    participant FirstBroadcaster
    participant SecondBroadcaster
    participant Oracle

    Advertiser->>AdContract: Deposit funds, define rules
    User->>FirstBroadcaster: Visits site
    FirstBroadcaster->>AdContract: Write encrypted tag to blockchain (user's wallet)
    User->>SecondBroadcaster: Visits site, connects wallet
    SecondBroadcaster->>AdContract: Read tag from blockchain
    SecondBroadcaster->>User: Display Ad
    SecondBroadcaster->>Oracle: Request impression verification
    Oracle->>AdContract: Confirm valid impression
    AdContract-->>FirstBroadcaster: Execute micropayment
    AdContract-->>SecondBroadcaster: Execute micropayment
    AdContract-->>AdContract: Retain agency fee

Axis 5: The "Inverse" or Failure Mode

Derivative 1.8: Low-Power, Privacy-Preserving Mode

Enabling Description: This derivative operates in a "limited functionality" mode focused on user privacy. The "tag" contains no personal information, only a one-time-use, expiring cryptographic nonce and a generic interest category (e.g., "automotive"). The "first broadcaster" generates this nonce. The "agency" is a simple matching service that does not store user profiles. When the user visits the "second broadcaster," the site sends the nonce to the agency. The agency validates its authenticity and expiration and returns a generic, non-personalized piece of content from the corresponding category (e.g., an ad for a car, but not a hyper-targeted one). The nonce is then immediately destroyed. This provides a mechanism for coarse-grained off-site content delivery that fails safely (expires and is non-reusable) and preserves user anonymity.

Mermaid Diagram:

graph TD
    A[First Broadcaster] --> B{Generate expiring nonce & category tag};
    B --> C[User's Browser];
    C --> D[User visits Second Broadcaster];
    D --> E{Send nonce to Agency};
    subgraph Agency
        E --> F{Validate Nonce (exists & not expired?)};
        F -- Yes --> G[Return generic content for category];
        F -- No --> H[Return no-op];
        G --> I{Destroy Nonce};
    end
    G --> J[Second Broadcaster displays content];
    H --> K[Second Broadcaster displays default content];

Combination Prior Art Scenarios

1. Combination with OpenRTB (Real-Time Bidding) Standard:
The method of US 7,822,639 is combined with the IAB's OpenRTB protocol. The "first broadcaster" acts as a Data Management Platform (DMP), tagging the user and creating a segment ID. When this user visits the "second broadcaster" (a publisher in the RTB ecosystem), the publisher's ad exchange sends out a bid request compliant with the OpenRTB standard. This bid request is enriched by the "agency" (acting as a Supply-Side Platform or SSP) to include the segment ID created by the first broadcaster in the user.ext.data object. Bidders (DSPs) can then recognize this ID and place a higher value on the impression, effectively executing the patent's method within the standardized, open framework of real-time programmatic advertising.

2. Combination with OAuth 2.0 (Open Authorization):
The patent's method is implemented using the OAuth 2.0 framework to manage user consent and identification. A user on the "first broadcaster's" site grants permission via an OAuth flow for an "agency" application to access their user ID. This grant and the resulting access token serve as the "tag." When the user visits the "second broadcaster," they use a "Sign in with Agency" feature (another OAuth flow). The agency, recognizing the user's identity via the second sign-in, uses the previously granted permission from the first broadcaster to serve targeted content. The entire process of tagging and recognition is handled through open, standardized, consent-based authorization protocols.

3. Combination with W3C's Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs):
The system is built on open W3C standards. A user's browser wallet holds a DID. The "first broadcaster" issues a Verifiable Credential to the user's DID, attesting that "this DID visited a site about topic X." This VC is the "tag." The "agency" is a trust registry that lists public keys of valid broadcaster issuers. When the user visits the "second broadcaster," they present the VC. The second broadcaster checks the agency's trust registry to verify the issuer's signature on the VC is valid. Upon verification, it delivers content relevant to "topic X." This combination creates a decentralized, user-controlled, and cryptographically secure version of the patent's method using open standards.