Patent 6199048

Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Defensive Disclosure and Prior Art Generation

Pertaining to the Art Disclosed in U.S. Patent 6,199,048

Publication Date: April 28, 2026
Subject Matter: Derivatives, extensions, and combinations related to systems and methods for linking physical objects to network resources via an indexed database lookup, thereby rendering obvious incremental or future improvements in the art.

Axis 1: Material & Component Substitution

1.1. Derivative: Spectroscopic Signature as a Data Carrier

  • Enabling Description: A system wherein the data carrier is a chemical composition or a set of molecular markers embedded within or applied to an article of commerce. The index is not visually encoded but is a function of the material's inherent spectroscopic signature. An input device, such as a handheld Raman spectrometer or a miniaturized Fourier-Transform Infrared (FTIR) spectrometer, irradiates the material with a laser or infrared source. The backscattered light is analyzed to generate a unique spectral fingerprint (e.g., a set of Raman shifts and their intensities). This spectral data is processed through a hashing algorithm (e.g., SHA-256) to produce a unique alphanumeric index. This index is then used to query a database to retrieve a pointer to a remote computer, in accordance with the core method. This is particularly useful for authenticating products where a visible barcode is undesirable or susceptible to replication, such as luxury goods, pharmaceuticals, or mission-critical components.

  • Mermaid Diagram: Data Flow

    flowchart TD
    A[Handheld Spectrometer] -- Emits Laser --> B{Product Material with Chemical Markers};
    B -- Backscatters Light --> A;
    A -- Generates Spectral Data --> C[Processor];
    C -- Applies Hashing Algorithm (SHA-256) --> D[Generated Index];
    D -- Transmits to Network --> E[Remote Database];
    E -- Index Lookup --> F[Pointer / URL Retrieved];
    F -- Returns to User Device --> G[Establish Communication];
    G -- Connects to --> H[Remote Computer];

1.2. Derivative: Embedded NFC with Volatile Index Storage

  • Enabling Description: A system where the data carrier is a passive Near Field Communication (NFC) tag (compliant with ISO/IEC 14443) embedded within a product. The tag contains a volatile memory module (e.g., SRAM) that is only powered when in the presence of an RF field from an NFC reader. The "index" is written to this volatile memory. An authorized device can update this index at various points in the supply chain. For example, a product's index can point to a logistics manifest while in transit, and be updated at the point of sale to point to a consumer-facing warranty registration page. The user's computing device (e.g., a smartphone) acts as the NFC reader, providing power to the tag, reading the current index, and using it to access the corresponding network resource via the database. This allows for a single physical product to have a dynamically changing network link throughout its lifecycle.

  • Mermaid Diagram: State Transition

    stateDiagram-v2
    [*] --> In_Transit
    In_Transit: Index points to Logistics DB
    In_Transit --> For_Sale : POS Device Update
    For_Sale: Index points to Warranty Page
    For_Sale --> In_Use : User Registration
    In_Use: Index points to User Manual
    In_Use --> End_of_Life : Time/Usage Trigger
    End_of_Life: Index points to Recycling Info

1.3. Derivative: Acoustic Resonance as Index

  • Enabling Description: A system where the unique physical structure of an object serves as its own data carrier. An input device, comprising a piezoelectric transducer and a sensitive acoustic receiver, makes contact with or is placed in close proximity to the object. The transducer excites the object with an ultrasonic chirp signal across a predefined frequency range. The receiver captures the object's resonant response. A Fast Fourier Transform (FFT) is performed on the received signal to identify the dominant resonant frequencies and their amplitudes. A feature vector is extracted from this spectral data and hashed to create a unique index. This method is effective for objects with a consistent and complex internal structure, such as ceramic components or metallic castings, allowing for identification without any external markings.

  • Mermaid Diagram: Process Flow

    sequenceDiagram
    participant Reader
    participant Object
    participant Processor
    participant Database
    Reader->>Object: Excite with Ultrasonic Chirp
    Object-->>Reader: Return Acoustic Response
    Reader->>Processor: Forward Raw Response Signal
    Processor->>Processor: Perform FFT on Signal
    Processor->>Processor: Extract Feature Vector & Hash
    Processor->>Database: Query with Hashed Index
    Database-->>Processor: Return Pointer (URL)
    Processor->>Reader: Initiate Connection

Axis 2: Operational Parameter Expansion

2.1. Derivative: Nanoscale Quantum Dot Array as Data Carrier

  • Enabling Description: A system operating at the nanoscale, where the data carrier is an array of colloidal quantum dots (QDs) deposited on a substrate using inkjet or lithographic techniques. Each QD is engineered to emit light at a specific, narrow wavelength when excited by a UV or blue light source. The "index" is encoded by the spatial arrangement (x,y coordinates) and the specific emission wavelength (color) of the QDs in the array. A confocal fluorescence microscope coupled with a CCD sensor acts as the reader. It excites the array and decodes the index from the pattern of multi-wavelength emissions. This allows for extremely high-density data storage in a covert manner, suitable for anti-counterfeiting applications on pharmaceuticals, currency, or microelectronic chips.

  • Mermaid Diagram: Component Architecture

    graph TD
    subgraph Reader_Device
        A[UV Excitation Source] --> B(QD_Array_on_Product);
        B --> C{Confocal Microscope};
        C --> D[Dichroic Mirror];
        D -- Reflected Light --> E[Waste];
        D -- Emitted Fluorescence --> F[Filter_Array];
        F --> G[CCD Sensor];
        G --> H[Image Processor];
    end
    H -- Decodes Position & Wavelength --> I[Index];
    I --> J[Database Lookup];
    J --> K[Retrieve Pointer];

2.2. Derivative: High-Pressure Subsea Indexing

  • Enabling Description: An application of the system in extreme high-pressure, deep-sea environments. The data carrier is a transponder affixed to a subsea asset (e.g., a wellhead, pipeline section, or remotely operated vehicle). The "index" is the unique acoustic signature of the transponder. A sonar interrogation system on a surface vessel or autonomous underwater vehicle (AUV) sends a coded acoustic signal. The transponder replies with its unique ID (the index). This index is relayed via satellite link to a terrestrial database. The database returns a pointer to the asset's real-time operational dashboard, including pressure readings, temperature, and structural integrity data, accessible by engineers onshore.

  • Mermaid Diagram: Sequence Diagram

    sequenceDiagram
    participant Onshore_Engineer
    participant AUV
    participant Subsea_Asset
    participant Terrestrial_DB
    Onshore_Engineer->>AUV: Command: 'Query Asset X'
    AUV->>Subsea_Asset: Acoustic Interrogation
    Subsea_Asset-->>AUV: Reply with Unique ID (Index)
    AUV->>Terrestrial_DB: Transmit Index via Satellite Link
    Terrestrial_DB-->>AUV: Return Pointer to Control Dashboard
    AUV->>Onshore_Engineer: Relay Pointer
    Onshore_Engineer->>Terrestrial_DB: Access Dashboard via Pointer

Axis 3: Cross-Domain Application

3.1. Derivative: Aerospace Digital Twin Linkage

  • Enabling Description: In aerospace maintenance, a component such as a turbine blade is marked with a laser-etched Data Matrix code capable of withstanding extreme temperatures. This code contains the component's serial number (the index). A maintenance technician uses a ruggedized tablet with a high-resolution camera to scan the index. The tablet's software accesses a secure database that links the index to a specific pointer. This pointer does not lead to a static webpage, but rather to a live, interactive digital twin of the specific component, rendered in an augmented reality overlay on the tablet's screen. The AR view displays real-time data such as accumulated stress cycles, thermal exposure history, and maintenance records, pulled from the aircraft's flight data recorder and maintenance logs.

  • Mermaid Diagram: Entity Relationship

    erDiagram
    COMPONENT ||--o{ "DATA MATRIX" : contains
    "DATA MATRIX" ||--|{ INDEX : encodes
    INDEX }|--|| DATABASE : queries
    DATABASE ||--|{ POINTER : provides
    POINTER }|--|| "DIGITAL TWIN" : links_to
    "DIGITAL TWIN" }o--|| "MAINTENANCE LOG" : displays
    "DIGITAL TWIN" }o--|| "SENSOR DATA" : displays

3.2. Derivative: AgTech Precision Irrigation

  • Enabling Description: In precision agriculture, an in-field soil sensor (e.g., a TDR probe for moisture) is the data carrier. It has a unique identifier broadcast via LoRaWAN. A gateway receiver collects these identifiers (indices) from hundreds of sensors across a field. Each index is sent to a cloud-based agricultural platform (the database). The database correlates the index with the sensor's known GPS coordinates and its latest soil moisture reading. The platform's logic then retrieves a pointer corresponding to a specific command for an irrigation control system. This pointer might be an API endpoint call that instructs a specific valve in a drip irrigation system to open for a calculated duration, delivering a precise amount of water only to the area that needs it.

  • Mermaid Diagram: Flowchart

    flowchart TD
    A((Soil Sensor)) -- LoRaWAN --> B[Gateway];
    B -- Sensor ID (Index) --> C[Cloud Platform];
    C -- Correlates Index with GPS & Moisture Data --> D{Decision Logic};
    D -- Moisture Low --> E[Retrieve Pointer for 'Irrigate' API Call];
    D -- Moisture OK --> F[Retrieve Pointer for 'Standby' Command];
    E --> G[Irrigation Control System];
    F --> G;
    G -- Actuates Valve --> H((Specific Field Zone));

Axis 4: Integration with Emerging Tech

4.1. Derivative: AI-Driven Predictive Pointer Generation

  • Enabling Description: A system where the database is replaced by a predictive machine learning model. A user scans a standard UPC barcode (the index) on a food product. This index, along with contextual data streams (time of day, user's location from device GPS, user's saved dietary preferences, recent purchase history), is fed as input to a trained neural network. The model does not perform a simple lookup. Instead, it generates a pointer on-the-fly to a resource it predicts will be most useful. For example, scanning a carton of eggs at 8 AM might generate a pointer to a breakfast recipe. Scanning the same product after visiting a gym (inferred from location data) might generate a pointer to a high-protein meal plan. The "database" becomes a dynamic, context-aware inference engine.

  • Mermaid Diagram: Architecture

    graph TD
    subgraph User_Device
        A[Barcode Scanner] --> B(Index: UPC);
        C[GPS] --> D(Context: Location);
        E[Clock] --> F(Context: Time);
    end
    B & D & F --> G[Feature Vector];
    G --> H{ML Inference Engine};
    H -- Generates --> I(Predicted Pointer / URL);
    I --> J[Web Browser];

4.2. Derivative: Blockchain-Verified Provenance

  • Enabling Description: For supply chain verification, a product is labeled with a QR code containing a unique identifier (the index). This index corresponds to a specific asset on a permissioned blockchain (e.g., Hyperledger Fabric). A user's device scans the code and submits the index to a web service. This service (the "database") is an oracle that queries the blockchain. It retrieves the full transaction history for the asset associated with that index. The service then returns a pointer to a web-based dApp that visualizes this immutable history, showing every step from origin to retail, complete with timestamps and cryptographic verification. This allows a consumer to instantly verify the authenticity and ethical sourcing of a product.

  • Mermaid Diagram: Sequence Diagram

    sequenceDiagram
    participant User
    participant Product_QR_Code
    participant Oracle_Service
    participant Blockchain
    User->>Product_QR_Code: Scan Index
    User->>Oracle_Service: Query with Index
    Oracle_Service->>Blockchain: GetTransactionHistory(Index)
    Blockchain-->>Oracle_Service: Return Provenance Data
    Oracle_Service-->>User: Return Pointer to dApp
    User->>User: Access dApp via Pointer
    Note right of User: View Immutable Supply Chain History

Axis 5: The "Inverse" or Failure Mode

5.1. Derivative: Graceful Degradation with Embedded Fallback

  • Enabling Description: A system designed for high-reliability or offline environments. The data carrier on an industrial chemical drum consists of two parts: a high-density Data Matrix code (primary index) and a larger, lower-density QR code (secondary index). In normal operation, a scanner reads the primary index and connects to an online database to retrieve the full, up-to-date Safety Data Sheet (SDS). If the device has no network connectivity, the application automatically fails over. It then scans the secondary QR code. This code does not contain an index for a database, but instead directly encodes a vCard-like data structure containing critical offline information: the chemical name, primary hazards, emergency contact number, and basic first-aid instructions. This ensures that essential safety information is always accessible, even upon failure of the primary network-based system.

  • Mermaid Diagram: State Diagram

    stateDiagram-v2
    state "Online Mode" as Online
    state "Offline Mode" as Offline

    [*] --> Initializing
    Initializing --> Online: Network Detected
    Initializing --> Offline: No Network

    Online --> Offline: Network Lost
    Online: Scan Primary Index -> Access Remote DB -> Display Full SDS
    Offline --> Online: Network Regained
    Offline: Scan Secondary Index -> Decode Embedded Data -> Display Basic Safety Info

Combination Prior Art Scenarios

  • 1. Combination with IETF RFC 8141 (URNs): The method is implemented where the index read from the data carrier is used to query a database that returns not a direct URL, but a Uniform Resource Name (URN). The user's computing device then uses a Resolution Discovery System (RDS) client to resolve this persistent, location-independent URN into a currently accessible URL based on context such as user language preference, geographic location, or available content formats. This decouples the product's identity from a specific server address, making the link more robust over time.

  • 2. Combination with W3C Verifiable Credentials: The system is used for authentication. A QR code on a certificate or ID card contains a Decentralized Identifier (DID) as the index. A verifier's device scans the DID and uses it to discover a DID-controlled service endpoint (the "database"). The device engages in a cryptographic challenge-response protocol with the endpoint to prove control of the associated private key. Upon successful verification, the service returns a "pointer" which is a temporary URL to a W3C-compliant Verifiable Credential, proving the authenticity of the physical document.

  • 3. Combination with GS1 Digital Link Standard: The system is a direct implementation of the open GS1 Digital Link standard. The data carrier is a QR code encoding a URL that contains a GS1 identifier (e.g., GTIN, SSCC). This URL itself acts as the "index." When scanned, the device's browser is pointed to this URL, which leads to a resolver (the "database"). This resolver, following the GS1 standard, redirects the user's browser to different final URLs ("pointers") based on link types requested or inferred, allowing a single barcode to link to nutritional facts, assembly instructions, or promotional offers. The core method of index-to-pointer lookup is performed by a standardized, interoperable web protocol rather than a proprietary database.

Generated 4/28/2026, 2:36:15 AM