Derivative works

Defensive Disclosure Document for US Patent 10904487

Title: Advanced Integrated Interactive Whiteboard and Videoconferencing Systems with Dynamic Overlay Management and Enhanced Collaborative Features

Current Date: April 26, 2026

Abstract of Disclosure:
This defensive disclosure outlines a series of derivative works and extensions of the core invention described in US Patent 10904487, focusing on the integration and dynamic management of interactive whiteboard (IWB) and videoconferencing (VC) windows on a display. These disclosures aim to preemptively address potential incremental improvements by competitors by establishing prior art across various technological dimensions, operational scales, industrial applications, and integrations with emerging technologies. Specific attention is given to advanced material and component substitutions, extreme operational parameter expansion, cross-domain applications, integration with AI, IoT, and blockchain, and inverse/failure modes. Each derivative includes an enabling technical description and a visual architectural or process diagram. Furthermore, this document identifies combination prior art scenarios leveraging existing open-source standards to demonstrate obviousness of potential future developments.

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Derivation Framework for Core Claim Elements (Based on Claim 1)

The independent claims of US Patent 10904487 (e.g., Claim 1, 8, 15) describe:

1. A whiteboard device displaying an interactive whiteboard session window.
2. A selection menu overlaid on the interactive whiteboard session window for initiating a videoconference.
3. A videoconference window overlaid on the interactive whiteboard session window after initiation.

The following derivatives expand upon these core elements.

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1. Material & Component Substitution

Derivative 1.1: Flexible Electrochromic Display with Haptic Feedback Surface

• Enabling Description: The interactive whiteboard device comprises a large-format flexible electrochromic display substrate (e.g., polymer-based) that dynamically adjusts opacity and color properties for high-contrast viewing under varying ambient light. Instead of a rigid touchscreen, the display integrates a pressure-sensitive, deformable haptic feedback layer, allowing users to "feel" digital content (e.g., boundaries, textures of annotations) via localized vibratory or tactile actuation. Input is provided by a passive, conductive stylus or direct finger touch, with touch events mapped to display coordinates by an integrated optical tracking system (e.g., using IR emitters/receivers embedded in the display bezel). The network interface utilizes a flexible printed antenna array for 60 GHz WiGig (IEEE 802.11ad/ay) for high-bandwidth, low-latency wireless connectivity. The processors are System-on-Chip (SoC) solutions optimized for low-power, high-performance edge AI, embedded directly within the flexible display assembly.
• Mermaid Diagram:

  flowchart TD
      A[Flexible Electrochromic Display] --> B{Optical Tracking System};
      B -- Touch Coordinates --> C[SoC Processor (Edge AI)];
      C -- Render & Haptic Pattern --> A;
      C -- IWB Data / VC Stream --> D[WiGig Network Interface];
      E[Conductive Stylus / Finger] -- Input --> B;
      F[Haptic Feedback Layer] -- Actuation --> A;
      D -- Wireless Link --> G[External Network];
  

Derivative 1.2: Holographic Projection Whiteboard with Gesture Control

• Enabling Description: The whiteboard device is replaced by a holographic projection system creating a large, interactive three-dimensional light-field display in a designated space. The "interactive whiteboard session window" and "videoconference window" are rendered as distinct holographic objects within this 3D space. User interaction is achieved through advanced mid-air gesture recognition (e.g., using LiDAR arrays and high-speed stereo cameras) rather than physical touch. A neural network-based gesture recognition engine interprets complex hand and body movements for navigation, annotation, and window manipulation. Directional audio arrays provide localized sound for participants in the holographic videoconference. The system utilizes photonics-based processors for ultra-fast light-field rendering and real-time gesture interpretation, communicating over a fiber optic network interface (e.g., 100 Gigabit Ethernet) to a remote rendering farm.
• Mermaid Diagram:

  graph TD
      A[Holographic Projector] --> B(3D Light-Field Display);
      C[LiDAR Arrays & Stereo Cameras] --> D{Gesture Recognition Engine (NN)};
      D -- Control Commands --> E[Photonics Processor];
      E -- IWB/VC Render Data --> A;
      E -- Network Communication --> F[Fiber Optic NIC];
      F -- High-Bandwidth Link --> G[Remote Rendering Farm];
      H[Directional Audio Array] --> B;
      User --> C;
  

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2. Operational Parameter Expansion

Derivative 2.1: Gigascale Collaborative Design Wall for Aerospace Engineering

• Enabling Description: This derivative operates at an industrial scale, deploying the interactive whiteboard and videoconferencing integration across a modular, multi-gigapixel display wall spanning an entire design studio (e.g., 50m x 10m). The "interactive whiteboard session window" may cover multiple physical display modules, showing intricate CAD schematics of aircraft or spacecraft. Multiple concurrent "selection menus" and "videoconference windows" can be instantiated by different user groups, each potentially comprising hundreds of participants, overlaid on distinct regions of the gigapixel canvas. The system handles extreme data volumes (e.g., hundreds of terabytes of design data) and requires real-time synchronization of annotations and video streams across geographically dispersed teams. This is achieved through a distributed rendering architecture leveraging GPU clusters and a high-performance computing (HPC) backend, connected via a redundant 400 Gigabit Ethernet backbone. Operational parameters include a display resolution of several billion pixels, refresh rates up to 240 Hz, and synchronized collaboration latency under 50ms globally.
• Mermaid Diagram:

  graph LR
      SubsystemA[Modular Display Wall (N Modules)] -- HDMI 2.1 / DisplayPort 2.0 --> GPUCluster[Distributed GPU Cluster];
      GPUCluster -- Render Instructions --> DisplayManager[Display Wall Manager];
      InputDevices[Multi-user Input (Touch, Stylus, Gesture)] -- Input Events --> InputProcessor[Input Event Processor];
      InputProcessor -- IWB/VC Commands --> BackendHPC[HPC Collaboration Backend];
      BackendHPC -- Data Sync / VC Streams --> NetworkBackbone[400GbE Backbone];
      NetworkBackbone -- Global Connectivity --> RemoteSites[Remote Collaboration Sites];
      DisplayManager -- Overlay Management --> SubsystemA;
      style SubsystemA fill:#f9f,stroke:#333,stroke-width:2px
      style GPUCluster fill:#ccf,stroke:#333,stroke-width:2px
      style BackendHPC fill:#cfc,stroke:#333,stroke-width:2px
  

Derivative 2.2: Nanoscale Inter-Device Collaboration for Micro-Assembly

• Enabling Description: This application targets extreme operational precision and scale, where the "whiteboard device" is a microscopic display integrated into a nano-manipulation workstation. The "interactive whiteboard session window" displays real-time electron microscopy (EM) or atomic force microscopy (AFM) feeds, allowing micro-assembly engineers to collaboratively annotate nanoscale structures (e.g., protein folds, semiconductor lithography defects). The "selection menu" and "videoconference window" are rendered as augmented reality (AR) overlays within the microscope eyepiece or on a separate, high-resolution micro-display, enabling remote experts to guide manipulation. The data involves ultra-precise coordinate systems (e.g., picometer resolution) and extremely high frame rates for live imaging (e.g., thousands of frames per second). Communication occurs over specialized low-latency, quantum-encrypted optical links to minimize interference and ensure secure transmission of sensitive intellectual property.
• Mermaid Diagram:

  sequenceDiagram
      participant ME as Micro-Assembly Engineer
      participant MW as Nano-Manipulation Workstation (IWB Device)
      participant EM as Electron Microscope / AFM
      participant RE as Remote Expert (VC Client)
      participant MLS as Micro-Display / AR Lens System
  
      ME->MW: Initialize Micro-Assembly Session
      MW->EM: Request Live Feed
      EM-->MW: High-Res Imaging Data (Nanoscale)
      MW->MLS: Display IWB Window (EM Feed)
      ME->MLS: Activate "Selection Menu" (AR Overlay)
      ME->MLS: Select "Start Videoconference"
      MLS->MW: Instruction Received
      MW->RE: Initiate VC Session (Ultra-Low Latency)
      RE-->MW: VC Stream
      MW->MLS: Overlay VC Window (AR Overlay)
      MLS->RE: Share IWB Window (Annotated EM Feed)
      RE->MLS: Remote Annotation Input
      MLS->MW: Annotation Data
      MW->MLS: Update IWB Window with RE Annotation
  

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3. Cross-Domain Application

Derivative 3.1: Tele-Diagnostic Whiteboard for Remote Veterinary Surgery

• Enabling Description: In a veterinary setting, the "whiteboard device" is an operating room (OR) display integrated with surgical equipment. The "interactive whiteboard session window" displays real-time patient physiological data (e.g., heart rate, blood pressure, oxygen saturation) and live endoscopic video feeds from within the animal patient. A "selection menu" is overlaid on this critical data, allowing a local veterinary surgeon to initiate a secure videoconference with a remote specialist (e.g., a veterinary cardiologist or neurologist). The "videoconference window" is then overlaid on the endoscopic view, enabling the remote specialist to provide real-time guidance, draw annotations directly onto the live video feed (e.g., highlighting anatomical structures or incision lines), and monitor vital signs collaboratively. All data streams are encrypted and transmitted over a dedicated, low-latency medical-grade network.
• Mermaid Diagram:

  classDiagram
      class OR_Display {
          +display()
          +receiveTouchInput()
          +overlayMenu(menu_id)
          +overlayVCWindow(vc_stream)
      }
      class IWB_Application {
          +displaySessionWindow(content)
          +handleAnnotations()
      }
      class VC_Client {
          +startSession(participant_id)
          +sendVideoStream(stream)
          +receiveVideoStream(stream)
      }
      class Remote_Specialist {
          +viewVC()
          +annotateLiveFeed()
      }
      class Surgical_Equipment {
          +getEndoscopicFeed(): VideoStream
          +getPatientVitals(): DataStream
      }
      class Application_Manager {
          +manageWindowLayers()
          +detectUserSelection()
          +updateMenu()
      }
      OR_Display "1" -- "1" IWB_Application : displays
      OR_Display "1" -- "1" VC_Client : displays
      OR_Display "1" -- "1" Application_Manager : controlled by
      IWB_Application "1" -- "*" Surgical_Equipment : uses data from
      VC_Client "1" -- "1" Remote_Specialist : communicates with
      Application_Manager ..> OR_Display : manages overlays
      Remote_Specialist ..> IWB_Application : annotates via VC
  

Derivative 3.2: Collaborative Geopolitical Risk Assessment Dashboard

• Enabling Description: In the domain of defense and intelligence, the "whiteboard device" is a secure, large-format multi-touch display in a situation room. The "interactive whiteboard session window" displays a dynamic geopolitical map overlayed with real-time intelligence feeds (e.g., troop movements, weather patterns, social media sentiment analysis, economic indicators). A "selection menu" appears contextually, allowing intelligence analysts to initiate a highly secure videoconference with remote field agents or allied command centers. The "videoconference window" then overlays a portion of the map, enabling face-to-face discussions while collaboratively annotating emergent threat vectors, logistics routes, or impact zones directly on the live intelligence display. The system features multi-level security access controls, ensuring that only authorized participants can view and interact with classified information. Data is transmitted over a dark fiber network with hardware-level encryption.
• Mermaid Diagram:

  graph TD
      A[Intelligence Analyst (Local)] --> B{Multi-Touch Situation Room Display};
      B -- Displays --> C[IWB Session Window (Geopolitical Map + Live Intel)];
      B -- User Input (Touch) --> D{Application Manager};
      D -- Generates / Overlays --> E[Selection Menu (Start Secure VC)];
      A -- Selects "Start Secure VC" --> E;
      E -- Instruction --> D;
      D -- Initiates --> F[Secure VC Client];
      F -- Establishes --> G[Secure VC Session];
      G -- Connects --> H[Remote Field Agent / Command Center];
      D -- Overlays --> I[VC Window (on IWB)];
      H -- Annotates --> C;
      C -- Live Intel Feeds --> J[Intelligence Data Backend (Secure)];
      G -- Data Transfer --> K[Dark Fiber Network (Encrypted)];
  

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4. Integration with Emerging Tech

Derivative 4.1: AI-Optimized Adaptive Videoconferencing & Whiteboard

• Enabling Description: The interactive whiteboard system integrates an AI-driven optimization engine. The "application manager" leverages machine learning models to dynamically adjust the layout and presentation of the "interactive whiteboard session window" and "videoconference window." This optimization is based on real-time analysis of user interaction patterns (e.g., gaze tracking, active annotation areas), speech analytics (e.g., active speaker detection, sentiment analysis from VC audio), and content relevance (e.g., identifying keywords on the whiteboard matching discussion topics). For example, the AI might automatically enlarge the VC window for the active speaker, or highlight specific areas of the whiteboard being discussed, while minimizing less relevant windows or content. It can also suggest relevant documents or external data to be loaded onto the whiteboard based on ongoing discussion. This system employs deep learning models for multimodal input processing and reinforcement learning for dynamic UI adaptation, executed on an integrated high-performance AI accelerator (e.g., dedicated NPU or GPU).
• Mermaid Diagram:

  flowchart TD
      User[User Interaction (Gaze, Voice, Touch)] --> InputSensor[Multimodal Input Sensors];
      InputSensor --> AI_Engine[AI Optimization Engine (NPU/GPU)];
      AI_Engine -- UI Layout Decisions --> AppMgr[Application Manager];
      AppMgr -- Manages Display --> Display[Display];
      Display --> IWBWindow[IWB Session Window];
      Display --> VCWindow[Videoconference Window];
      VCWindow -- Audio/Video Stream --> SpeechAnalysis[Speech/Sentiment Analysis];
      IWBWindow -- Content Changes --> ContentAnalysis[Content Relevance Analysis];
      SpeechAnalysis --> AI_Engine;
      ContentAnalysis --> AI_Engine;
      AI_Engine -- Suggestions/Content --> IWBWindow;
  

Derivative 4.2: IoT-Enhanced Environmental & Biometric Contextual Whiteboard

• Enabling Description: The whiteboard device is augmented with a suite of IoT sensors providing real-time contextual data. Environmental sensors (e.g., ambient light, room temperature, humidity, CO2 levels, acoustic presence detection) are integrated to automatically adjust display brightness, contrast, and audio levels for optimal viewing and listening conditions. User biometric sensors (e.g., integrated thermal cameras for stress detection, wearable heart rate monitors synced via Bluetooth LE, eye-tracking cameras for attention levels) provide individual engagement metrics. The "application manager" uses this aggregate IoT data to personalize the collaboration experience. For instance, if a remote participant shows signs of disengagement (low gaze on whiteboard, increased heart rate indicating stress), the system might suggest a break, or re-prioritize their video feed. If room CO2 levels are high, a notification could be overlaid to open a window. The system uses a local IoT gateway for data aggregation and edge processing before feeding critical insights to the application manager.
• Mermaid Diagram:

  componentDiagram
      [Interactive Whiteboard Device] -- "Display" --> [Display];
      [Interactive Whiteboard Device] -- "Application Manager" --> [IWB App];
      [Interactive Whiteboard Device] -- "Application Manager" --> [VC Client];
      [Interactive Whiteboard Device] -- "IoT Gateway" --> [Environmental Sensors];
      [Interactive Whiteboard Device] -- "IoT Gateway" --> [Biometric Sensors];
  
      [Environmental Sensors] --> [Ambient Light Sensor];
      [Environmental Sensors] --> [Temperature/Humidity Sensor];
      [Environmental Sensors] --> [CO2 Sensor];
      [Environmental Sensors] --> [Acoustic Sensor];
  
      [Biometric Sensors] --> [Eye-Tracking Camera];
      [Biometric Sensors] --> [Thermal Camera (Stress)];
      [Biometric Sensors] --> [Wearable HR Monitor (BTLE)];
  
      [IoT Gateway] -- "Aggregated Data" --> [Application Manager];
      [Application Manager] -- "Adjusts Parameters" --> [Display];
      [Application Manager] -- "Contextual Cues" --> [VC Client];
      [Application Manager] -- "Layout Adjustments" --> [IWB App];
  

Derivative 4.3: Blockchain-Verified Collaborative Whiteboard for Contract Negotiations

• Enabling Description: The interactive whiteboard is used in high-stakes contract negotiations or intellectual property (IP) co-creation, integrating blockchain technology for immutable record-keeping. Any significant changes or additions to the "interactive whiteboard session content area" (e.g., terms, clauses, design specifications) made during a "videoconference session" are cryptographically hashed. When participants agree on a specific change (e.g., by explicit on-screen digital signature or consensus vote initiated via the "selection menu"), the hash of the whiteboard state, along with participant identities and a timestamp, is recorded as a transaction on a private, permissioned blockchain (e.g., Hyperledger Fabric). The "videoconference window" includes integrated digital signature capabilities. This creates an auditable, unalterable ledger of all collaborative changes and agreements, enhancing trust and providing clear provenance for all content generated during the session.
• Mermaid Diagram:

  sequenceDiagram
      participant P1 as Participant 1 (IWB)
      participant P2 as Participant 2 (VC Client)
      participant IWB as Interactive Whiteboard Device
      participant AM as Application Manager
      participant BC as Blockchain Network
  
      P1->IWB: Edit IWB content
      P1->IWB: Initiate "Selection Menu" (Sign Agreement)
      IWB->AM: Detect "Sign Agreement" / IWB State Change
      AM->IWB: Overlay Digital Signature UI
      P1->IWB: Provide Digital Signature
      AM->BC: Submit IWB State Hash + Signatures as Transaction
      BC->BC: Verify & Record Transaction
      BC-->AM: Transaction Confirmation
      AM->IWB: Display "Blockchain Verified" Confirmation
      P2->IWB: Participate in VC
      P2->IWB: View IWB content
      P2->IWB: Digital Signature via VC client
  

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5. The "Inverse" or Failure Mode

Derivative 5.1: "Disaster Recovery" or "Low-Bandwidth" Prioritized Mode

• Enabling Description: The interactive whiteboard device includes a "Disaster Recovery" or "Low-Bandwidth" mode, activated automatically upon detection of significant network degradation (e.g., packet loss > 10%, latency > 500ms, available bandwidth < 5 Mbps) or low power supply (e.g., battery < 15%, external power disconnected). In this mode, the "application manager" prioritizes core collaboration. The "videoconference window" automatically degrades: video streaming is disabled or reduced to low-frame-rate static images, prioritizing audio-only communication. The "interactive whiteboard session window" prioritizes text and vector graphics, disabling high-resolution image rendering or complex animations. Heavy processing, such as real-time 3D object manipulation, is offloaded or frozen. The "selection menu" simplifies, presenting only essential options (e.g., "End Session," "Save Local Copy," "Text Chat"). The system performs local caching of IWB content and queues outgoing annotations for batch synchronization once network conditions improve. This ensures basic functionality and data preservation under adverse conditions.
• Mermaid Diagram:

  stateDiagram-v2
      [*] --> Normal_Operation
      Normal_Operation --> Low_Bandwidth_Mode: Detect Network Degradation
      Normal_Operation --> Low_Power_Mode: Detect Low Power
      Low_Bandwidth_Mode --> Normal_Operation: Network Restored
      Low_Power_Mode --> Normal_Operation: Power Restored
  
      state Normal_Operation {
          Full_VC_Video --> Full_IWB_Interactivity
      }
      state Low_Bandwidth_Mode {
          Audio_Only_VC --> Prioritized_Text_IWB
          Prioritized_Text_IWB --> Local_Caching
          Local_Caching --> Sync_Queue
      }
      state Low_Power_Mode {
          Static_Image_VC --> Basic_Annotation_IWB
          Basic_Annotation_IWB --> Minimal_Menu
      }
  

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Combination Prior Art Scenarios with Open-Source Standards

These scenarios illustrate how the core invention of US10904487 could be combined with widely available open-source standards, potentially rendering future specific implementations obvious.

1. US10904487 + WebRTC for Real-time Communication:

   • Description: The "collaboration client" (126) and "collaboration server" (108) described in US10904487, which could be proprietary (e.g., Microsoft Lync), are implemented using the WebRTC (Web Real-Time Communication) open-source standard. WebRTC provides standardized APIs for real-time audio and video communication directly within web browsers or client applications. A PHOSITA would find it obvious to use WebRTC's peer-to-peer or SFU (Selective Forwarding Unit) architecture to establish the "videoconferencing session" and transmit the "videoconference window" content. The "application manager" (128) would then utilize operating system window management APIs to overlay the WebRTC-rendered video stream, identical to the claimed functionality.
   • Prior Art Combination: US20150009278A1 (Avaya) + General knowledge of WebRTC APIs (e.g., W3C WebRTC 1.0 specifications) + Common GUI layering techniques.

2. US10904487 + Open-Source Whiteboard Frameworks (e.g., Fabric.js/Konva.js):

   • Description: The "interactive whiteboard (IWB) application" (124) described in US10904487 is developed using an open-source JavaScript canvas library like Fabric.js or Konva.js. These libraries provide robust functionalities for creating interactive 2D graphics, drawing, object manipulation, and serialization of whiteboard content, which directly corresponds to the "interactive whiteboard session content area" (304). The "application manager" (128) would then manage the display of this open-source-powered interactive canvas, and overlay a menu or videoconference window on top, as described in the patent. The core functionality of collaborative drawing and content display would be realized through these readily available open-source components.
   • Prior Art Combination: US20080098295A1 (Seiko Epson - Annotation Management) or US20150009278A1 (Avaya) + General knowledge of open-source canvas libraries + Common GUI layering techniques.

3. US10904487 + Wayland/Xorg Window Management Protocols:

   • Description: The operating system (132) and its "OS application programming interface (API)" (134) in US10904487, which are described in the context of Microsoft Windows (FindWindow(), WS_EX_TOPMOST), are implemented on a Linux-based whiteboard device utilizing open-source display server protocols like Wayland or Xorg. These protocols provide well-defined mechanisms for client applications (like the IWB application and collaboration client) to request window creation, positioning, layering, and input focus from the display server. A PHOSITA would find it obvious to adapt the claimed "application manager" to interact with Wayland compositors or Xorg window managers using their respective APIs to achieve the "overlaid" menu and videoconference window behaviors, thus replicating the window management aspect of the invention on an open-source platform.
   • Prior Art Combination: US8713454B2 (Verizon - Sharing Virtual Workspaces) + General knowledge of Wayland/Xorg window management principles and APIs + Common GUI overlay design patterns.