US 8784113

US patent 8784113, titled "Open and interactive e-learning system and method," was issued to its current assignee, OPENSESAME Inc. The patent was filed on June 9, 2011, and granted on July 22, 2014. The inventors are Aaron H Bridges, Jason S Day, Joshua D Blank, and Donald S Spear.

Abstract:
The patent describes a system and method that facilitate widespread and easy access by learners to e-learning content created by authors, thereby fostering an e-learning marketplace. Content is centrally stored and updated, then distributed to local content servers via a content delivery network (CDN). A proprietary server provides interfaces and a "SESAMESEED" proxy that can be loaded into a user's server, which is connected to one or more Learning Management Systems (LMSs). Training managers can subscribe to content, authors receive payment, and learners participate in courses. The system tracks completion status and grades, which are reportable to the LMSs. The invention also provides security and enables interaction among various users.

Plain-language overview of independent claims:

• Claim 1: E-learning Delivery System
  This claim describes a system for delivering e-learning content. It includes a central server for managing licenses and reporting user activity, and a content player that delivers content from a content delivery network (CDN). A crucial component is a "proxy" software module, initially stored on the network but executed on a user's device. This proxy is configured to identify specific licensed content, allow a user to access and interact with that content through a web browser, and report the user's progress and interaction status back to both the central licensing/reporting server and the user's local Learning Management System (LMS). When a user requests content, the proxy asks the central server to verify the user's license. If the license is valid, the server provides the proxy with information to access the content player, which the proxy then uses to instruct the user's browser. The proxy also relays information about the content playback status to the client-side LMS.

• Claim 5: Method for Delivering E-learning Content
  This claim outlines a method for delivering e-learning content that complies with industry standards. The method begins by receiving a request from a user's Learning Management System (LMS) to access content located on a Content Delivery Network (CDN). The claim then continues to describe "configuring a proxy with license..." [The provided patent text for claim 5 is truncated, leading to uncertainty regarding its full scope].

USPTO and CAFC Docket Search Results (as of April 26, 2026):

The USPTO provides a Patent Public Search tool to search its database of patents and patent application publications.

Regarding litigation concerning US8784113, the Federal Circuit recently vacated a Patent Trial and Appeal Board (PTAB) decision. The PTAB had found that Go1 Pty, Ltd. failed to prove the challenged claims of US Patent No. 8,784,113 unpatentable as obvious. The Federal Circuit's decision, issued on Thursday (May 28, 2026), found that the Board's finding that expert testimony on step sequencing was conclusory was not supported by substantial evidence.

Litigation involving US patent 8784113 includes:

• Case Number: IPR2022-01439

  • Petitioner: Unified Patents (This entity's role is to deter Non-Practicing Entities (NPEs) and protect against "frivolous patent litigation.")
  • Patent Owner: Go1 Pty, Ltd. (This is inferred from the PTAB's decision that Go1 Pty, Ltd. failed to prove the claims unpatentable).
  • Jurisdiction: Patent Trial and Appeal Board (PTAB)
  • Filing Date: The IPR case was filed on an unspecified date in 2022, but the Final Written Decision was issued at some point before May 28, 2026.
  • Outcome/Current Status: The PTAB initially found that Go1 Pty, Ltd. failed to prove the challenged claims unpatentable. However, the Federal Circuit vacated this decision on May 28, 2026, finding that the Board's conclusion regarding conclusory expert testimony on step sequencing was not supported by substantial evidence.

• Case Number: 3:21-cv-01258

  • Plaintiff(s): OPENSESAME, Inc.
  • Defendant(s): GO1 Pty, Ltd.
  • Jurisdiction: Oregon District Court
  • Filing Date: 2021
  • Outcome/Current Status: An "Opinion and Order on Claim Construction" was issued on May 5, 2026.

• Case Number: 24-1762

  • Jurisdiction: Court of Appeals for the Federal Circuit
  • Outcome/Current Status: This case is active, as noted in the patent's information, and relates to the appeal of the PTAB decision in IPR2022-01439.

It is important to note that the Federal Circuit exclusively hears appeals in patent infringement cases.

Proceedings overview

There is one AIA trial proceeding on file for US patent 8784113. This Inter Partes Review (IPR) proceeding resulted in the PTAB's initial finding that the challenged claims were not proven unpatentable, but this decision was subsequently vacated by the Federal Circuit. This gives a defendant a mixed defensive posture; while the claims were initially sustained by the PTAB, the Federal Circuit's vacatur reopens the question of their patentability.

IPR2022-01439 — Unified Patents v. Go1 Pty, Ltd.

• Type: Inter Partes Review
• Filed: The IPR case was filed on an unspecified date in 2022.
• Status: Vacated by Federal Circuit. The PTAB initially found that Go1 Pty, Ltd. failed to prove the challenged claims unpatentable, but the Federal Circuit vacated this decision on May 28, 2026.
• Judge panel: Information about the specific judge panel for IPR2022-01439 is not publicly available in the provided snippets. However, James A. Tartal is listed as a PTAB Judge associated with Unified Patents cases in general.
• Petition grounds: The petition challenged claims of US Patent No. 8,784,113 as unpatentable based on obviousness, specifically regarding "expert testimony on step sequencing."
• Institution decision: Details of the institution decision (e.g., date, full reasoning) are not available in the provided information. However, IPR was instituted since a Final Written Decision was issued.
• Final Written Decision (if issued): The PTAB issued a Final Written Decision finding that Go1 Pty, Ltd. failed to prove the challenged claims of US Patent No. 8,784,113 unpatentable.
• Settlement / termination: No information regarding settlement or termination is provided.
• Appeal: Yes, the FWD was appealed to the Court of Appeals for the Federal Circuit under case number 24-1762. The Federal Circuit vacated the PTAB's decision on May 28, 2026, finding that the Board's conclusion regarding conclusory expert testimony on step sequencing was not supported by substantial evidence.
• Defensive value: The Federal Circuit's vacatur means that the PTAB's initial finding of patentability for the challenged claims is no longer definitive. This reopens the door for a defendant to challenge the patentability of these claims, potentially leveraging the Federal Circuit's reasoning regarding expert testimony on step sequencing.

Strategic summary

Currently, the status of claims from US8784113 is in flux due to the Federal Circuit's vacatur of the PTAB's Final Written Decision in IPR2022-01439. While the PTAB initially sustained the challenged claims by finding them not unpatentable, this decision has been overturned on appeal. This means no claims have been definitively canceled by the PTAB in this proceeding, nor have they been conclusively sustained against the obviousness challenge raised. The specific claims challenged in IPR2022-01439 are not enumerated in the provided text. All claims of the patent, therefore, remain "untested" by a finalized PTAB decision.

The estoppel landscape is complex due to the Federal Circuit's vacatur. Generally, 35 U.S.C. § 315(e)(2) bars petitioners and their privies from raising any ground they raised or reasonably could have raised in a proceeding that results in a final written decision. However, with the Federal Circuit vacating the PTAB's decision, it is unclear if statutory estoppel would apply, as there is no longer a "final written decision" affirming the patentability of the claims. This could potentially leave the prior-art grounds raised by Unified Patents available for future challenges, either by Unified Patents (or its privies) in a new proceeding or by other defendants in district court litigation. Unified Patents is known as a defensive aggregator that aims to deter Non-Practicing Entities (NPEs) and protect against "frivolous patent litigation."

Recommended next steps

Given the Federal Circuit's vacatur of the PTAB's Final Written Decision in IPR2022-01439, a defendant facing assertion of this patent should closely monitor the remanded proceedings at the PTAB. The original PTAB decision (which is now vacated) found that Go1 Pty, Ltd. failed to prove the challenged claims unpatentable, but the Federal Circuit explicitly stated that the Board's finding regarding conclusory expert testimony on step sequencing was not supported by substantial evidence. This indicates a potential weakness in the patent owner's previous arguments or evidence presented to the PTAB.

A defendant should investigate the specific claims challenged in IPR2022-01439 to understand the grounds of obviousness raised and the details of the expert testimony that the Federal Circuit found problematic. This could provide a roadmap for future invalidity arguments. The absence of a finalized PTAB decision upholding the patentability of these claims means they are not "hardened" against prior art challenges in the same way claims surviving a Federal Circuit-affirmed FWD would be.

Inventors

• Aaron H Bridges
• Jason S Day
• Joshua D Blank
• Donald S Spear

Their employer at the time of filing is not explicitly stated in the provided text. The original assignee is listed as "Individual," which suggests the inventors may have held the patent rights initially, or a corporate employer was not immediately identified in the provided details.

Original assignee

The original assignee is listed as "Individual" (from the Google Patents "Original Assignee" field). This typically means the patent was initially assigned to the inventors personally, rather than a corporate entity at the time of filing. The provided information does not specify if the "Individual" shipped a product embodying the claims, their primary line of business, or their current status. However, based on the assignment timeline, the patent was assigned to Blue Tech, LLC on the same day it was filed.

Assignment timeline

• 2011-06-09 (executed) / recorded 2011-06-09 — Reel 026778/0500 (from Google Patents)

  • Conveyance: Assignment
  • Assignor: BLANK, JOSHUA D., BRIDGES, AARON H., DAY, JASON S., SPEAR, DONALD S.
  • Assignee: Blue Tech, LLC
  • Correspondent: Not specified in the provided text.
  • Context: Transfer from inventors to a new entity.

• 2014-01-22 (executed) / recorded 2014-01-22 — Reel 031649/0517 (from Google Patents)

  • Conveyance: Assignment
  • Assignor: BLUE TECH LLC
  • Assignee: OPENSESAME INC.
  • Correspondent: Not specified in the provided text.
  • Context: Acquisition of patent rights.

• 2018-06-12 (executed) / recorded 2018-06-12 — Reel 043236/0074 (from Google Patents)

  • Conveyance: Security Interest
  • Assignor: OPENSESAME INC.
  • Assignee: SILICON VALLEY BANK
  • Correspondent: Not specified in the provided text.
  • Context: Patent used as collateral for a loan.

• 2018-06-14 (executed) / recorded 2018-06-14 — Reel 043282/0252 (from Google Patents)

  • Conveyance: Security Interest
  • Assignor: OPENSESAME INC.
  • Assignee: PIVOTAL CAPITAL FUND, LP
  • Correspondent: Not specified in the provided text.
  • Context: Patent used as collateral for a loan.

• 2019-11-12 (executed) / recorded 2019-11-12 — Reel 047640/0178 (from Google Patents)

  • Conveyance: Release By Secured Party
  • Assignor: SILICON VALLEY BANK
  • Assignee: OPENSESAME INC.
  • Correspondent: Not specified in the provided text.
  • Context: Release of security interest.

Timeline diagram

timeline
    title Ownership of US 8784113
    2011 : Filed by Individual inventors
         : Assigned to Blue Tech LLC
    2014 : Assigned to OPENSESAME Inc
    2018 : Security interest to Silicon Valley Bank
         : Security interest to Pivotal Capital Fund LP
    2019 : Release by Silicon Valley Bank

NPE / troll-pattern signals

1. Shell-entity transfer — Unclear. Blue Tech, LLC (2011-06-09 / 026778/0500) served as an intermediary between the inventors and OPENSESAME Inc. However, there's insufficient information in the provided text to determine if Blue Tech, LLC was a shell entity (e.g., no products, registered-agent address). OPENSESAME Inc. appears to be an operating company based on the patent description and the nature of the e-learning system.
2. Known asserter in the chain — Not present. None of the assignees (Blue Tech, LLC, OPENSESAME Inc., Silicon Valley Bank, Pivotal Capital Fund, LP) are explicitly identified as known NPEs in the provided information or common public lists. Go1 Pty, Ltd. is noted as a defendant in litigation, not an assignee in the provided timeline.
3. Repeat correspondent across the chain — Unclear. Correspondent information is not provided for any of the recorded assignments.
4. Cascading transfers — Not present. The transfers occur over several years, not in rapid succession.
5. Pre-litigation transfer — Not present. The most recent assignment (release of security interest) was in 2019, while the district court litigation against Go1 Pty, Ltd. began in 2021.
6. Bankruptcy fire-sale — Not present. The transfers do not appear to be associated with bankruptcy proceedings.
7. Privateering — Unclear. There is no information in the provided text to suggest that OPENSESAME Inc. transferred the patent to an NPE to assert on its behalf.
8. Defensive aggregator (anti-NPE) — Not present. The chain does not terminate at a known defensive aggregator. Unified Patents is a petitioner in an IPR, which is an anti-NPE action, but they are not an assignee in the chain of ownership.

Verdict

Operating-company assertion

The patent was transferred from the inventors to Blue Tech, LLC, and then to OPENSESAME Inc., which is described as the current assignee and the provider of the "OPENSESAME" e-learning system detailed in the patent. The ongoing litigation in Oregon District Court (3:21-cv-01258) shows OPENSESAME, Inc. as the plaintiff against GO1 Pty, Ltd., indicating an operating company asserting its patent against a competitor. [cite: https://patents.google.com/patent/[US8784113](/patent/US8784113)/en]

For verification, you can search the USPTO Assignment Center using patent number 8784113: https://assignmentcenter.uspto.gov/

The most relevant prior art for US patent 8784113 is determined by examining the patent's own citations. To do this, I will access the USPTO database for patent 8784113 and then review the "Cited By" or "References Cited" sections.

Since I cannot directly interact with a live USPTO database search tool to pull all cited prior art and their details in a structured format, I will explain the process a human analyst would follow.

Steps to identify and describe the most relevant prior art:

1. Access USPTO Patent Public Search: I would navigate to the USPTO's Patent Public Search website.
2. Search for US8784113: Using the "Basic Search" or "Advanced Search" function, I would input the patent number "8784113" to locate the full patent document.
3. Locate "References Cited" Section: Within the retrieved patent document, I would navigate to the "References Cited" section. This section lists all the prior art documents (patents, patent applications, and sometimes non-patent literature) that the examiner and applicant considered during prosecution.
4. Extract Information for Each Reference: For each listed reference, I would extract the following:
   • Full Citation: The patent number, inventor(s), issue date, and title.
   • Publication/Filing Date: The earliest relevant date (either filing or publication) for prior art purposes.
   • Brief Description: A summary of the invention disclosed in the prior art document, often obtainable from its abstract or first few paragraphs.
   • Potential Anticipation (35 U.S.C. § 102): I would then compare the elements of the prior art reference to the independent claims of US8784113 (specifically Claims 1 and 5, as provided in the summary). A prior art reference "anticipates" a claim if it discloses every single element of that claim, either explicitly or inherently, in a single document.

What I expect to find in the "References Cited" section:

The "References Cited" section of US8784113 would likely include patents and publications related to:

• E-learning systems: Previous platforms for delivering educational content online.
• Learning Management Systems (LMS): Existing LMS architectures and functionalities.
• Content Delivery Networks (CDN): Technologies for distributing content, especially for multimedia.
• Proxy technologies: Systems using proxies for various purposes, including content access and security.
• SCORM and AICC standards: Documents or patents detailing the implementation and challenges of these e-learning standards.
• Digital Rights Management (DRM): Systems for managing access and licensing of digital content.

Without direct access to the "References Cited" section of US8784113 from the USPTO database, I cannot provide the specific details of the most relevant prior art. However, a manual review of that section would be the definitive way to determine this.

The "Prior art" section of this analysis explicitly states that without direct access to the "References Cited" section of US8784113 from the USPTO database, the specific details of the most relevant prior art cannot be provided.

Therefore, I cannot perform an obviousness analysis under 35 U.S.C. § 103, as this requires identifying and combining specific prior art references and explaining the motivation to do so. The necessary foundational information (i.e., the actual prior art references) is not available in the provided context.

To detail the patent term adjustments (PTA), patent term extensions (PTE), continuation applications, divisional applications, related family members, and the projected expiration date for US patent 8784113, I will search the USPTO database.

USPTO Patent Information for US8784113:

Based on the publicly available information, here's a breakdown for US patent 8784113:

• Patent Number: US8784113B2
• Filing Date: June 9, 2011
• Publication Date: July 22, 2014
• Granted Date: July 22, 2014
• Priority Date: June 15, 2010 [cite: https://patents.google.com/patent/US8784113/en]

Patent Term Adjustments (PTA):
Patent Term Adjustment (PTA) can extend the term of a U.S. patent to compensate for delays caused by the USPTO during the examination process. These delays can include the USPTO failing to take certain actions within specific timeframes, such as issuing a first office action within 14 months or a patent within three years of the application filing date. The patent text for US8784113 does not explicitly state the amount of PTA granted. To determine the exact PTA, one would typically need to review the patent's file history on the USPTO Patent Center.

Patent Term Extensions (PTE):
Patent Term Extensions (PTE) are distinct from PTA and are primarily available for patents covering pharmaceutical products, food additives, color additives, or medical devices that undergo regulatory review (e.g., FDA approval) prior to commercial marketing. Since US8784113 pertains to an e-learning system and method, it is highly unlikely to be eligible for a Patent Term Extension under 35 U.S.C. § 156. The provided patent information does not indicate any PTE for this patent.

Continuation Applications:
A continuation application claims priority to an earlier non-provisional application and contains the same disclosure. This allows an applicant to pursue additional claims based on the same invention disclosed in the parent application. The patent information for US8784113 indicates a priority claim to US13/156,607, which is the application number for US8784113 itself. [cite: https://patents.google.com/patent/US8784113/en] It also lists a priority to US20110306027A1, which is an earlier publication of this patent. The patent also claims priority to PCT/US2011/039966 and EP11796218.3A, and CA2802683A. Additionally, there is a priority claim to US14/261,122, filed on April 24, 2014. [cite: https://patents.google.com/patent/US8784113/en] This indicates that US14/261,122 might be a continuation or related application to US8784113. Without further access to the USPTO's Patent Center or Public Search, it's not possible to definitively determine if US14/261,122 is specifically a continuation, continuation-in-part, or divisional application.

Divisional Applications:
A divisional application is filed when an examiner determines that a single patent application contains more than one patentable invention and issues a restriction requirement, forcing the applicant to elect one invention for examination. The unelected inventions can then be pursued in divisional applications, which share the same filing date as the parent application. The provided information does not explicitly state that US8784113 resulted from or has given rise to any divisional applications.

Related Family Members:
The patent lists the following as "Other versions" and priority claims, which are typically considered related family members:

• US20110306027A1 [cite: https://patents.google.com/patent/US8784113/en]
• PCT/US2011/039966 [cite: https://patents.google.com/patent/US8784113/en]
• EP11796218.3A [cite: https://patents.google.com/patent/US8784113/en]
• CA2802683A [cite: https://patents.google.com/patent/US8784113/en]
• US14/261,122 [cite: https://patents.google.com/patent/US8784113/en]

These documents represent different stages of the application process (e.g., published application, PCT application, European and Canadian counterparts) and a later-filed US application claiming priority.

Projected Expiration Date:
For U.S. utility patents filed on or after June 8, 1995, the patent term generally expires 20 years from the earliest filing date of the patent application. If the patent claims priority to an earlier application, the 20-year term starts from the filing date of the earliest priority application.

US patent 8784113 was filed on June 9, 2011, and claims priority to U.S. Provisional Patent Application No. 61/397,797, filed on June 15, 2010. [cite: https://patents.google.com/patent/US8784113/en] Therefore, the patent term is calculated from the earliest priority date, which is June 15, 2010.

• 20 years from the earliest priority date (June 15, 2010) is June 15, 2030.

However, the Google Patents legal status section for US8784113 states the patent "expires 2031-12-10" and is "Active." [cite: https://patents.google.com/patent/US8784113/en] This adjusted expiration date suggests that Patent Term Adjustment (PTA) has been granted, extending the patent's life beyond the standard 20 years from its priority date. PTA compensates for delays in prosecution caused by the USPTO.

Therefore, the projected expiration date for US8784113 is December 10, 2031, due to Patent Term Adjustment. [cite: https://patents.google.com/patent/US8784113/en]

Defensive Disclosure: US Patent 8784113 - Open and Interactive E-learning System and Method

This defensive disclosure document outlines various derivative works and technical variations of US patent 8784113, "Open and interactive e-learning system and method." The purpose of this disclosure is to expand the existing body of prior art, making incremental improvements by competitors in the e-learning domain obvious or non-novel, thereby strengthening the public domain. This document focuses on generating novel technical disclosures stemming from the core inventive concepts of Claims 1 and 5 (as derived from the available truncated text and description).

Derivative Variations for Core Claims

Derivatives for Claim 1: E-learning Delivery System

1.1. Material & Component Substitution: Decentralized Content and Serverless Licensing

• Enabling Description: The network-side content delivery network (CDN) is substituted with a decentralized content distribution network (DCDN) utilizing peer-to-peer protocols such as IPFS (InterPlanetary File System) or BitTorrent for storing and retrieving e-learning content. Content chunks are hashed and distributed across a multitude of participant nodes. The licensing/reporting server functionalities (license verification, status aggregation, location designator provision) are implemented as a collection of serverless functions (e.g., AWS Lambda, Google Cloud Functions, Azure Functions) operating on a cloud-native platform, triggered by HTTP requests. The proxy, executing on the client-side, is adapted to resolve content identifiers (CIDs for IPFS) and request signed access tokens from the serverless licensing functions, rather than static URLs from a monolithic server. Player components are loaded dynamically based on content metadata.

graph TD
    A[Client-side Computing Device] --> B{Browser}
    B -- Request Access --> C[SESAMESEED Proxy (Client-side)]
    C -- Request License Verification (Serverless Invocation) --> D[Serverless Licensing Function]
    D -- Verify License --> E[Decentralized License Store]
    D -- If Valid: Provide Signed Access Token + Content CID --> C
    C -- Instruct Browser (Token + CID) --> B
    B -- Request Content (CID + Token) --> F[DCDN (IPFS/BitTorrent)]
    F -- Deliver Content Chunks --> B
    B -- Render/Interact --> A
    C -- Report Status (Serverless Invocation) --> G[Serverless Reporting Function]
    G -- Aggregate Status --> D
    G -- Update LMS --> H[Client-side LMS]

1.2. Operational Parameter Expansion: Sub-Millisecond Latency Immersive VR Training System

• Enabling Description: The e-learning system is optimized for real-time, sub-millisecond latency interactive virtual reality (VR) training, supporting hundreds of concurrent learners in a shared virtual space. The licensing/reporting server and content player operate on edge computing nodes geographically co-located with learner groups to minimize network hops. The content delivery network utilizes ultra-low latency streaming protocols (e.g., WebRTC, optimized UDP-based protocols) for volumetric video and interactive 3D model delivery, rather than traditional HTTP/progressive download. The proxy on the client-side is a thin client embedded within the VR headset's runtime environment, configured to pre-fetch and cache anticipated content segments based on predictive learner behavior models, and report granular pose, gaze, and interaction data to the licensing/reporting server at >100Hz frequency for highly detailed performance assessment.

sequenceDiagram
    participant L as Learner (VR Headset)
    participant P as SESAMESEED Proxy (VR Client)
    participant LS as Edge Licensing/Reporting Server
    participant CDN as Ultra-Low Latency CDN (Edge)
    participant VRP as VR Content Player (Edge)

    L->>P: Launch VR Course
    P->>LS: Request License Verification (User ID, Course ID)
    LS->>LS: Verify License (Local Cache/Fast DB)
    LS-->>P: If Valid: Signed VR Content Stream URL + Parameters
    P->>VRP: Instruct VR Player to Load (URL)
    VRP->>CDN: Request VR Content Stream (Volumetric Video, 3D Models)
    CDN-->>VRP: Deliver VR Content Stream (sub-ms)
    VRP-->>L: Render Immersive VR Experience
    L-->>VRP: Real-time Interaction (Pose, Gaze, Input)
    VRP->>P: Stream Interaction Data
    P->>LS: Report Granular Status Updates (>100Hz)
    LS->>LMS: Push Aggregate Status

1.3. Cross-Domain Application: Industrial Robotics Training System for Manufacturing

• Enabling Description: This system delivers e-learning content for operating and maintaining complex industrial robots on a manufacturing floor. The "user" is a robotics technician, and the "content" includes interactive 3D schematics, diagnostic simulations, and procedural video guides for specific robot models (e.g., KUKA, FANUC). The proxy is a dedicated module within the Human-Machine Interface (HMI) panel of the robot or a ruggedized tablet. The licensing/reporting server grants access based on technician certification levels and specific robot serial numbers, preventing unauthorized access to sensitive maintenance procedures. Status reporting includes successful completion of simulated repairs, time taken for diagnostic steps, and adherence to safety protocols.

flowchart TD
    subgraph Client-side (Manufacturing Floor)
        HMI[Robot HMI Panel / Rugged Tablet] --> P_MAN[SESAMESEED Proxy (HMI Module)]
        P_MAN --> L_MAN[LMS (Local HMI/Plant Server)]
    end

    subgraph Network-side (Cloud/Datacenter)
        LS_MAN[Licensing/Reporting Server (Industrial)]
        CDN_MAN[CDN (Industrial Content)]
        CP_MAN[Content Player (Industrial Spec)]
    end

    HMI -- Launch Training --> P_MAN
    P_MAN -- Request Authorization (Tech ID, Robot SN) --> LS_MAN
    LS_MAN -- Verify License (Certification, Robot Access) --> LS_MAN
    LS_MAN -- Access Granted (Player URL, Params) --> P_MAN
    P_MAN -- Instruct HMI Browser --> HMI
    HMI -- Load CP_MAN --> CP_MAN
    CP_MAN -- Request Industrial Content (3D Schematics, Sims) --> CDN_MAN
    CDN_MAN -- Deliver Content --> HMI
    HMI -- Technician Interacts --> CP_MAN
    CP_MAN -- Report Status (Simulation Progress, Time on Task) --> P_MAN
    P_MAN -- Relay Status --> L_MAN
    P_MAN -- Report Status to Network --> LS_MAN

1.4. Integration with Emerging Tech: AI-Driven Adaptive Learning System with Blockchain Licensing

• Enabling Description: The system integrates AI-driven adaptive learning algorithms to personalize content delivery and pace. The licensing/reporting server includes an AI module that analyzes learner performance data (from the proxy status reports) and dynamically adjusts the "location designator" parameters to retrieve content segments from the CDN tailored to the learner's proficiency and learning style. For instance, if a learner struggles, the AI might direct the player to a remedial module; if proficient, to advanced content. Licensing is managed via a blockchain (e.g., Ethereum smart contracts). A license is a non-fungible token (NFT) or a specific smart contract state, verifiable by the licensing/reporting server. The proxy is equipped with a blockchain wallet light client to attest to content access and status reports directly on the blockchain, creating an immutable record of learning achievements and license usage.

sequenceDiagram
    participant L as Learner
    participant P as SESAMESEED Proxy (Client)
    participant BL as Blockchain Ledger (e.g., Ethereum)
    participant LS as Licensing/Reporting Server (with AI Module)
    participant CDN as Content Delivery Network
    participant CP as Content Player

    L->>P: Request Adaptive Course
    P->>LS: Request License Verification (via BL Wallet)
    LS->>BL: Verify License NFT/Smart Contract State
    BL-->>LS: License Status (Valid/Invalid)
    LS->>LS: Analyze Learner Data (from past P reports)
    LS-->>P: Adaptive Location Designator (Player URL + AI-determined Content Params)
    P->>CP: Instruct Browser to Load CP (with Params)
    CP->>CDN: Request Content (AI-determined path)
    CDN-->>CP: Deliver Tailored Content
    CP-->>L: Display/Interact
    L->>CP: User Interaction/Progress
    CP->>P: Status Update
    P->>LS: Report Status to LS
    P->>BL: Log Learning Event/License Usage (Transaction)
    LS->>LS: Update Learner Model (AI)

1.5. The "Inverse" / Failure Mode: Offline-First Limited Functionality E-learning Cache

• Enabling Description: This derivative focuses on an "offline-first" mode for environments with unreliable internet connectivity. The SESAMESEED proxy, when initially configured, can pre-fetch a limited, essential subset of content for a specific course (e.g., critical safety procedures, core concepts) and store it in a local, encrypted cache on the client-side computing device. The licensing/reporting server, upon verifying a license, provides a time-limited cryptographic key allowing the proxy to decrypt and access this cached content even without an active internet connection. In this "limited-functionality" mode, the proxy records learner interaction status locally. Once connectivity is re-established, the proxy automatically synchronizes these cached status updates with the network-side licensing/reporting server and the client-side LMS. If content is accessed offline beyond the key's validity or after a remote license revocation, the proxy will enter a "read-only" or "restricted access" mode, displaying only high-level outlines or warning messages.

stateDiagram-v2
    state "Online Operation" as Online
    state "Offline Cache Initialization" as InitCache
    state "Limited Functionality (Offline)" as Offline
    state "Connection Re-established" as Reconnect
    state "Restricted Access / Locked" as Locked

    [*] --> Online: System Start
    Online --> InitCache: Initial Content Request + Stable Connection
    InitCache --> Offline: Cache Content + Obtain Offline Key
    Offline --> Reconnect: Connectivity Detected
    Reconnect --> Online: Sync Status Data
    Online --> Offline: Network Disruption
    Offline --> Locked: Offline Key Expired OR License Revoked
    Online --> Locked: License Revocation
    Locked --> Online: New License Purchased / Key Renewed

Derivatives for Claim 5: Method for Delivering E-learning Content (Truncated)

Given the truncation of Claim 5, I will infer the method includes: receiving a request, configuring a proxy with license information, verifying the license, accessing a content player, and reporting status. The derivatives below will adapt the previous system-level ideas to these method steps.

5.1. Method for Decentralized Content Access with Serverless Orchestration

• Enabling Description: The method involves: (a) receiving a request from an LMS for access to e-learning content, wherein the content resides on a decentralized content distribution network (DCDN) identified by a content identifier (CID); (b) configuring a SESAMESEED proxy with a cryptographic signature mechanism and a license containing a DCDN content resolver; (c) the proxy requesting a short-lived, signed access token from a serverless licensing function, the request including the user's decentralized identity and the content CID; (d) the serverless licensing function verifying the user's entitlement against a decentralized license store; (e) if verified, the serverless function issuing a signed access token and the CID to the proxy; (f) the proxy instructing the browser to load a content player and providing the player with the token and CID; (g) the content player retrieving content chunks from the DCDN using the CID and token; and (h) the proxy reporting interaction status updates to a serverless reporting function, which then updates the LMS.

sequenceDiagram
    participant LMS as User LMS
    participant P as SESAMESEED Proxy
    participant SLR as Serverless Licensing/Reporting
    participant DCDS as Decentralized Content & Data Store
    participant B as Browser
    participant CP as Content Player

    LMS->>P: Request Course (CID)
    P->>SLR: Request Signed Access Token (User DID, CID)
    SLR->>DCDS: Verify User Entitlement / License
    DCDS-->>SLR: Entitlement Status
    SLR-->>P: If Valid: Signed Token + CID
    P->>B: Instruct Browser to Load CP (Token, CID)
    B->>CP: Load Content Player
    CP->>DCDS: Request Content Chunks (CID, Token)
    DCDS-->>CP: Stream Content
    CP->>B: Render Content
    B->>CP: User Interaction
    CP->>P: Status Update
    P->>SLR: Report Interaction Status
    SLR->>DCDS: Store Status Data
    SLR->>LMS: Push Aggregate Status Update

5.2. Method for Real-time Edge-based VR Training with Biofeedback

• Enabling Description: A method for delivering e-learning content comprising: (a) an LMS receiving a request for an immersive VR training module; (b) configuring a SESAMESEED proxy embedded in a VR headset's runtime with a license enabling access to edge-hosted VR content streams; (c) the proxy, in response to the request, establishing a low-latency connection to a nearby edge licensing/reporting server; (d) the edge server verifying the learner's license and providing parameters for an ultra-low latency VR content player and dynamic content streams from an edge CDN; (e) the proxy instructing the VR headset's rendering engine to initialize the VR player and begin streaming volumetric data and interactive elements; (f) during interaction, the proxy collecting real-time biofeedback data (e.g., heart rate, galvanic skin response) from integrated headset sensors; (g) the proxy continuously reporting granular VR interaction and biofeedback status to the edge licensing/reporting server for performance analytics and adaptive content adjustment; and (h) the edge server aggregating and periodically pushing summarized status to the LMS.

flowchart TD
    A[LMS Receives VR Request] --> B{Configure VR Proxy (Headset)}
    B --> C[Proxy Connects to Edge LS]
    C --> D{Edge LS Verifies License}
    D -- Valid --> E[Edge LS Provides VR Player Params + Stream Info]
    E --> F[Proxy Instructs VR Headset to Load Player]
    F --> G[VR Player Streams Content from Edge CDN]
    G --> H[Learner Interacts in VR]
    H --> I[Proxy Collects VR Interaction & Biofeedback]
    I --> J[Proxy Reports Status to Edge LS]
    J --> K[Edge LS Aggregates & Pushes to LMS]

5.3. Method for Adaptive Skill-Tree Progress Tracking with AI

• Enabling Description: A method for delivering e-learning content comprising: (a) receiving an e-learning course request from an LMS; (b) configuring a SESAMESEED proxy with a license linked to a dynamic "skill-tree" model for the requested content; (c) the proxy requesting authorization from a licensing/reporting server that includes an AI-driven adaptive learning engine; (d) the server verifying the license and, based on the learner's historical performance data (managed by the AI engine), generating a personalized content path (location designator) and initial skill-tree state; (e) the proxy instructing the browser to load a content player according to the personalized path; (f) the learner interacting with content, generating progress events; (g) the proxy continuously reporting granular progress events (e.g., correct answers, time on task for specific sub-skills) to the AI engine; (h) the AI engine dynamically updating the learner's skill-tree, potentially re-evaluating and modifying subsequent content paths, and storing aggregated skill progression in the licensing/reporting server for the LMS.

stateDiagram-v2
    state "Course Request" as Request
    state "Proxy Configuration" as ProxyConfig
    state "License & AI Path Generation" as AIPath
    state "Content Delivery & Interaction" as Interaction
    state "Progress Reporting" as Reporting
    state "Skill Tree Update & Path Re-evaluation" as AIUpdate

    [*] --> Request: LMS Receives Request
    Request --> ProxyConfig: Configure Proxy (Skill-Tree License)
    ProxyConfig --> AIPath: Proxy Requests Auth (to AI Engine)
    AIPath --> Interaction: AI Generates Path, Proxy Loads Player
    Interaction --> Reporting: Learner Interacts
    Reporting --> AIUpdate: Proxy Reports Progress
    AIUpdate --> Interaction: AI Re-evaluates, Updates Path
    AIUpdate --> [*]: Course Complete / End Session

Combination Prior Art Scenarios

Here are three combination prior art scenarios where the concepts of US8784113 can be combined with existing open-source standards to make further innovations obvious:

1. Combination with Moodle LMS and Nginx Reverse Proxy

• Scenario: An e-learning system as described in US8784113 (Claim 1) is implemented where the Learning Management System (LMS) is the open-source Moodle platform. The proprietary content delivery network (CDN) functionality, particularly the "single domain using a reverse-proxy server configuration" aspect (as described in the patent), is realized using Nginx as an open-source reverse proxy. The SESAMESEED proxy (24) interacts with the Moodle LMS via its standard SCORM/AICC API, and Nginx is configured to serve content from various upstream origin servers (e.g., dedicated storage nodes) under a unified domain, providing the CDN abstraction. The technical implementation of the proxy's communication with the LMS, player, and licensing server, as detailed in the patent, would be made obvious by combining the known capabilities of Moodle's extensible architecture and Nginx's flexible reverse proxy configurations for content delivery.

2. Combination with SCORM Cloud (Rustici Software) and OpenSSL

• Scenario: The e-learning delivery system (Claim 1) is combined with the widely available Rustici SCORM Cloud service (which itself uses SCORM and AICC standards, explicitly mentioned as suitable players in the patent). The security schemes provided by CDNs, including "time-based access, signing/hashing of URL parameters with a shared key," are implemented using cryptographic functions from the OpenSSL library. Specifically, the licensing/reporting server (14) generates time-limited, signed URLs for content access using HMAC (Hash-based Message Authentication Code) derived from a shared key and timestamps, as enabled by OpenSSL. The proxy (24) and OPENSESAME player (18) verify these signatures using OpenSSL's functions before accessing content from the CDN. The integration of OpenSSL's standard cryptographic primitives for URL signing and verification with SCORM Cloud's runtime environment (as a content player) would render specific implementations of the patent's security features obvious.

3. Combination with Hyperledger Fabric for License Management and IPFS for Content Storage

• Scenario: The method for delivering e-learning standard-compliant content (Claim 5) is enhanced by utilizing Hyperledger Fabric as the underlying blockchain for managing and verifying licenses, and IPFS (InterPlanetary File System) for decentralized content storage. The step of "configuring a proxy with license" would involve the proxy generating a transaction on Hyperledger Fabric to record a learner's enrollment or license purchase, with the licensing/reporting server as an endorsing peer. License verification (by the licensing/reporting server) would involve querying the Hyperledger Fabric ledger for the learner's current license state. The content residing on a CDN is replaced by content addressed via IPFS Content Identifiers (CIDs). The content player then retrieves content directly from the IPFS network using these CIDs. The status updates reported by the proxy are immutably recorded as transactions on the Hyperledger Fabric blockchain, providing a transparent and verifiable record of course completion and scores. This combination makes explicit the integration of decentralized ledger technology for license management and distributed file systems for content delivery with the patent's proxy-based e-learning delivery model.