US 8271315

US Patent 8271315: Personal Information Utilization System for Commodity-Based Identification

Title: Personal information utilization system and personal information utilization program for commodity based identification

Assignee: Keysoft Inc.

Inventors: Yoshimitsu Kagiwada

Filing Date: November 5, 2002

Issue Date: September 18, 2012

Abstract: The patent aims to enhance customer service quality by enabling the sharing and utilization of customer personal information across various industries. It describes a system comprising a personal information storage means, a communication means, and an information processing means. The personal information storage means stores not only personal information of individuals (information disclosing persons) but also commodity provision information related to services or goods provided to them. The processing means is configured to receive personal information from an information search side terminal, verify it against stored data, identify the information disclosing person, and then transmit their associated commodity provision information back to the search terminal. An alternative embodiment allows searching by commodity provision information to identify associated individuals and return their personal information. The system also incorporates disclosure limits for personal information, allowing individuals to control their privacy.

Plain-Language Overview of Independent Claims:

US Patent 8271315 contains two independent claims: Claim 1 and Claim 2.

Independent Claim 1: Personal Information Utilization System
This claim describes a system designed to help a "second commodity provider" (e.g., a furniture store) identify potential customers based on past purchases from a "first commodity provider" (e.g., a housing vendor).

In plain language, the system works as follows:

• It has a central storage area (personal information storage means) that holds people's personal details and records of items or services ("first commodity provision information") they've received from various businesses ("first commodity provider").
• A computer processor manages this storage and communication.
• The system receives information about a product or service ("second commodity provision information") from a different company ("second commodity provider") that is looking for customers. This information includes details about a product similar to what the first provider offers (e.g., knowing someone bought a house implies they might need furniture).
• The system then compares this incoming "second commodity provision information" with its stored "first commodity provision information."
• If there's a match (meaning the "second commodity provision information" partially or completely aligns with stored "first commodity provision information"), the system identifies individuals ("specifically identified information disclosing person") who received the matching product or service from the "first commodity provider."
• Finally, the system retrieves a portion of the personal information of these identified individuals and sends it to the "second commodity provider's" terminal. This helps the second provider find customers who have a demonstrated need for their products or services based on past purchases from other providers.

Independent Claim 2: Non-Transitory Computer-Readable Medium with Program
This claim is directed to a computer program stored on a non-transitory computer-readable medium (like a hard drive or SSD) that, when run, performs the steps of a similar personal information utilization method.

In plain language, this means:

• A computer program exists on a storage device.
• When this program is executed, it carries out a series of steps:
  • It receives "second commodity provision information" from a "second commodity provider" (a company searching for customers).
  • It compares this "second commodity provision information" with existing "first commodity provision information" (records of what people have purchased from other companies).
  • Based on this comparison, it identifies individuals who are associated with the matching "first commodity provision information."
  • It retrieves personal information for these identified individuals from a database.
  • It then transmits at least some of this personal information to the "second commodity provider."
• Essentially, this claim covers the software aspect that enables the same functionality described in Claim 1, allowing for cross-industry customer identification based on shared (with consent) purchase history.

CAFC 2026 Dockets for US8271315:

A targeted search for US patent 8271315 in the CAFC 2026 dockets did not yield specific litigation directly associated with this patent number as of April 26, 2026. General searches for CAFC 2026 dockets show various patent-related cases, but none explicitly mention US8271315. Accessing detailed CAFC docket information often requires specific systems like PACER, which were not directly utilized in this general web search.

As of April 26, 2026, known litigation involving US patent 8271315 includes the following cases filed in the Delaware District Court:

1. Plaintiff(s): Keysoft, Inc.
   Defendant(s): Amazon.com, Inc.
   Jurisdiction: Delaware District Court
   Case Number: 1:24-cv-00256
   Filing Date: February 26, 2024
   Current Status: The case is pending.

2. Plaintiff(s): Keysoft, Inc.
   Defendant(s): Salesforce, Inc.
   Jurisdiction: Delaware District Court
   Case Number: 1:24-cv-00257
   Filing Date: February 26, 2024
   Current Status: The case is pending.

The initial check of the "PTAB proceedings on file" section explicitly states that the USPTO ODP API returns no AIA trial proceedings for US8271315. My web searches for "US8271315 IPR", "US8271315 PTAB", "US8271315 inter partes review", "US8271315 post-grant review", and "US8271315 covered business method" also did not yield any specific PTAB proceedings (IPR, PGR, or CBM) directly associated with this patent number. The search results provided general information about IPR, PGR, and CBM processes, but no case numbers or details for US8271315.

Therefore, I can confidently state that there are no PTAB proceedings on file for US8271315 based on the provided authoritative information and my web search.

Proceedings overview

There are no AIA trial proceedings on file for US Patent 8271315. This indicates that the patent has not been challenged through Inter Partes Review (IPR), Post-Grant Review (PGR), or Covered Business Method (CBM) review at the Patent Trial and Appeal Board (PTAB). For a defendant, this means the claims of the patent remain untested by these administrative processes, and there is no PTAB decision on their validity.

Strategic summary

As of May 19, 2026, all claims (Claims 1-17) of US8271315 remain untested by PTAB proceedings. No claims have been canceled or sustained through IPR, PGR, or CBM. The absence of PTAB activity means there is no estoppel landscape established under § 315(e)(2) for potential petitioners, as no grounds were raised or could have been raised in an instituted trial.

The lack of PTAB proceedings suggests that the patent has not yet faced the scrutiny common for patents actively asserted in litigation. This could be due to various reasons, such as the patent owner's enforcement strategy, the nature of the claimed invention, or the timing of the assertions relative to the availability of AIA trials. Given the recent litigation filings in February 2024, it is possible that defendants in those cases may consider filing PTAB petitions as a defensive strategy.

Recommended next steps

Since no PTAB activity exists for US8271315, a defendant currently facing assertion of this patent should:

• Conduct a thorough prior art search: Without PTAB review, the patent's validity has not been challenged using the administrative review processes. A comprehensive prior art search is crucial to identify potential invalidity grounds under 35 U.S.C. §§ 102 and 103 (for IPR) or additional grounds including §§ 101, 112 (for PGR or CBM, if applicable).
• Evaluate eligibility for IPR/PGR/CBM:
  • IPR: The patent was issued on September 18, 2012. IPR can be filed after 9 months of the patent's grant, and applies to patents issued before, on, or after September 16, 2012. This patent is eligible for IPR.
  • PGR: PGR must be filed within nine months of the patent's issuance and applies to patents with an effective filing date on or after March 16, 2013. Given the patent's issue date of September 18, 2012, and priority date of November 5, 2002, it is not eligible for PGR.
  • CBM: CBM review was a transitional program available until September 15, 2020. Although it allowed challenges to business method patents on broad grounds (including § 101 and § 112), the deadline for filing such petitions has passed.
• Consider filing an Inter Partes Review (IPR) petition: If strong prior art is found, an IPR petition could be a viable strategy to challenge the patentability of claims 1-17 under 35 U.S.C. §§ 102 or 103 based on patents or printed publications. This could offer a faster and potentially less expensive alternative to district court litigation for challenging validity. However, it's important to note the one-year time limit for filing an IPR petition after being served with a complaint alleging infringement.
• Monitor for future PTAB filings: Given the ongoing litigation, other defendants may choose to file PTAB petitions, which could impact the patent's validity.

Inventors

• Yoshimitsu Kagiwada (Keysoft Inc.)

Original assignee

The original assignee is Keysoft Inc. It is unclear from the patent text or general web search whether Keysoft Inc. shipped a product embodying the claims. Their primary line of business, as inferred from the patent, appears to be software development related to personal information utilization systems. Keysoft Inc. is currently an operating company and the plaintiff in ongoing litigation related to this patent.

Assignment timeline

• 2012-06-13 (executed) / recorded 2012-08-10 — Reel 028769/0019
  • Conveyance: Assignment
  • Assignor: KAGIWADA, YOSHIMITSU
  • Assignee: KEYSOFT, INC.
  • Correspondent: NOT RECORDED.
  • Context: Transfer from inventor to original assignee.

Timeline diagram

timeline
    title Ownership of US 8271315
    2002 : Filed by Keysoft Inc
    2012 : Issued to Keysoft Inc
         : Inventor assigned to Keysoft Inc
    2024 : First infringement suit filed

NPE / troll-pattern signals

1. Shell-entity transfer — not present. The patent was assigned from the inventor to Keysoft Inc., the original assignee named on the patent. There is no evidence of a subsequent transfer to a shell entity.
2. Known asserter in the chain — not present. Keysoft Inc. is the current assignee and there is no record of the patent being assigned to a known NPE from public lists.
3. Repeat correspondent across the chain — not present. The initial assignment from the inventor to Keysoft Inc. does not have a recorded correspondent. There are no subsequent assignments to check for recurring correspondents.
4. Cascading transfers — not present. Only one assignment from the inventor to the original assignee is recorded.
5. Pre-litigation transfer — not present. The assignment from the inventor to Keysoft Inc. occurred in 2012, long before the first litigation filing in 2024. There are no recorded transfers immediately preceding the litigation.
6. Bankruptcy fire-sale — not present. There is no indication that Keysoft Inc. has filed for bankruptcy, and the assignment on record is from the inventor to the company, not as part of bankruptcy proceedings.
7. Privateering — unclear. While Keysoft Inc. is asserting the patent, it is not clear whether this is on behalf of another operating company or in its own capacity as a direct competitor.
8. Defensive aggregator (anti-NPE) — not present. The patent is currently owned and being asserted by Keysoft Inc., not a defensive aggregator.

Verdict

Operating-company assertion

The recorded assignment history only shows the transfer from the individual inventor to Keysoft Inc., the original assignee. Keysoft Inc. is currently asserting the patent in litigation, indicating active enforcement by the original patent owner. [cite: https://patents.google.com/patent/[US8271315](/patent/US8271315)/en]

The search results provided information about "priority dates" in the context of immigration, which is not relevant to patent analysis. I need to rely on the priority date information directly from the patent document itself, which I have already done.

As previously determined, the effective priority date for US8271315 is May 7, 2001.
I will now list the most relevant prior art from the patent's own citations, ensuring they pre-date this priority date, and provide the requested details and a conceptual overlap analysis, with the explicit disclaimer about the legal determination of anticipation.

Most Relevant Prior Art for US Patent 8271315

The analysis of prior art for US Patent 8271315 (priority date: May 7, 2001) focuses on the citations that predate this effective priority date, making them potential prior art under 35 U.S.C. § 102. It is important to note that a definitive determination of anticipation under § 102 requires a detailed, element-by-element legal comparison of the prior art disclosure to each claim of US8271315, which is beyond the scope of this technical analysis. The following descriptions highlight conceptual overlaps that suggest potential anticipation.

1. US20010037294A1 - System and method for syndicated transactions

• Full Citation: US20010037294A1 (Freishtat)
• Publication/Filing Date: Publication: November 1, 2001; Priority: April 25, 2000.
• Brief Description: This patent application describes a system for facilitating "syndicated transactions" by sharing information about goods or services among multiple participants, such as retailers and manufacturers. It emphasizes the sharing of customer data (with consent) to create integrated offerings and provide bundled products or services.
• Potential Anticipation (Conceptual Overlap): This reference is highly relevant as it explicitly addresses the sharing of customer data among "multiple participants" from different industries to facilitate related transactions. This directly aligns with the core objective of US8271315 to improve customer service by "sharing and utilizing personal information on customers among variety of industries" (US8271315 Abstract). The mechanism of a "second commodity provider" searching for customers based on information from a "first commodity provider" in US8271315's Independent Claims 1 and 2 appears to be conceptually anticipated by US20010037294A1's disclosure of syndicated transactions where customer information is shared to facilitate the sale of related goods/services.

2. US20050240492A1 - Systems, methods and computer program products for facilitating the sale of commodity-like goods/services

• Full Citation: US20050240492A1 (Zipandshop L.L.C.)
• Publication/Filing Date: Publication: October 27, 2005; Priority: August 2, 2000.
• Brief Description: This application describes a system for facilitating sales of "commodity-like" goods and services, particularly in contexts like real estate, by collecting user preferences and property information to match users with suitable offerings and ancillary services (e.g., mortgages, moving services).
• Potential Anticipation (Conceptual Overlap): This reference is relevant because it describes a system for connecting customers with ancillary services based on a primary purchase, such as a house. This mirrors the example in US8271315 where a house purchaser might need furniture and bedding, and various vendors (second commodity providers) could identify these prospective customers. The concept of identifying user needs for related commodities/services from different providers is a strong conceptual overlap with Claims 1 and 2 of US8271315.

3. US20020019817A1 - Method and system for trading in personal information and storage medium therefor

• Full Citation: US20020019817A1 (International Business Machines Corporation)
• Publication/Filing Date: Publication: February 14, 2002; Priority: August 8, 2000.
• Brief Description: This application details a system and method enabling users to selectively disclose their personal information to businesses, often in exchange for incentives. It encompasses managing personal information, user preferences for disclosure, and facilitating transactions involving personal data.
• Potential Anticipation (Conceptual Overlap): This reference is highly relevant due to its focus on managing personal information and user-controlled disclosure. While US8271315 emphasizes provider-side sharing to find customers, US20020019817A1 highlights the consumer's control over personal information disclosure. This directly overlaps with the "information on disclosure limits" feature in US8271315's Dependent Claims 5 and 8, which allow information disclosing persons to protect their privacy. The underlying system for managing personal information and facilitating its (controlled) exchange for commercial purposes also presents conceptual overlap with the broader functionality described in Independent Claims 1 and 2 of US8271315.

4. US7031934B2 - Electronic commerce system and method for providing commercial information in electronic commerce system

• Full Citation: US7031934B2 (Hitachi, Ltd.)
• Publication/Filing Date: Publication: April 18, 2006 (Granted); Priority: March 25, 1997.
• Brief Description: This patent describes an electronic commerce system that manages commercial information, including product and customer data. It focuses on delivering targeted commercial information to users based on their attributes and preferences, often by accumulating purchasing history for personalized recommendations.
• Potential Anticipation (Conceptual Overlap): This patent broadly covers systems for managing customer information and providing commercial information based on purchase history, aiming for targeted marketing. This conceptually overlaps with US8271315's goals of utilizing past "commodity provision information" for future offerings. Independent Claims 1 and 2 of US8271315, which involve storing personal and commodity provision information and using it to identify individuals for marketing, share conceptual similarities with the broader targeting mechanisms disclosed in this reference.

5. US7284063B2 - Information processing apparatus, information processing method, and transmitting medium

• Full Citation: US7284063B2 (Sony Corporation)
• Publication/Filing Date: Publication: October 16, 2007 (Granted); Priority: October 14, 1997.
• Brief Description: This patent describes a system for providing information, such as product or service information, to users. It involves storing user profile information and matching it with product information to deliver relevant advertisements or recommendations, thereby improving the efficiency of information delivery.
• Potential Anticipation (Conceptual Overlap): Similar to US7031934B2, this patent deals with user profiles and targeted information delivery. The broad concept of matching user information with product/service information for personalized recommendations conceptually relates to the objectives of US8271315. Claims 1 and 2 of US8271315, particularly the steps of identifying information disclosing persons based on commodity provision information and transmitting personal information, bear a conceptual resemblance to systems described for targeted information delivery in this patent.

6. US20020103806A1 - Data supply controlling device, data supplying method, storage medium for data supplying program, and data supplying system

• Full Citation: US20020103806A1 (Yamanoue, Masafumi)
• Publication/Filing Date: Publication: August 1, 2002; Priority: October 18, 2000.
• Brief Description: This application describes a system for controlling the supply of data, including personal information, to users based on various criteria. It focuses on providing relevant information while also addressing data privacy and access management.
• Potential Anticipation (Conceptual Overlap): This reference broadly covers data supply and control, which includes personal information management and privacy. Its focus on controlling data supply and managing privacy aligns with the general architectural elements and the privacy features (disclosure limits) in US8271315 (Dependent Claims 5 and 8). The system described could facilitate the exchange of "commodity provision information" and "personal information" as envisioned in US8271315, although it may not explicitly detail the "cross-industry second provider" scenario in the same specific manner.

7. JP2002170035A - Information providing method, its apparatus, and recording medium recording the data

• Full Citation: JP2002170035A (Hitachi Ltd)
• Publication/Filing Date: Publication: June 14, 2002; Priority: November 30, 2000.
• Brief Description: This Japanese application describes a system for providing information, potentially commercial information, to users. It involves collecting user data and preferences to deliver targeted information or recommendations.
• Potential Anticipation (Conceptual Overlap): Without a full English translation, a precise analysis is difficult. However, based on the title and typical scope of such systems, it likely involves matching user profiles with available information for targeted provision. This broad function of matching and providing information conceptually relates to the identification and transmission steps of US8271315's Independent Claims 1 and 2.

Note on JP2002329058A: This Japanese patent application (JP2002329058A) has the same priority date (May 7, 2001) as US8271315 and is by the same inventor. It is a family member or a very closely related application and would typically not be considered prior art for anticipation under 35 U.S.C. § 102 against its own claims or claims of a family member sharing the same effective priority date.

Note on other cited US applications (US20020184108A1, US20030055730A1/US7523049B2, US20030070180A1, US7233955B2): These references have priority dates that are after the effective priority date of US8271315 (May 7, 2001). Therefore, they are not considered prior art for anticipation under 35 U.S.C. § 102 relative to the claims of US8271315. They may have been cited by the examiner for other reasons, such as for obviousness analysis under § 103, or for general background information.

Obviousness Analysis of US Patent 8271315 Under 35 U.S.C. § 103

This analysis identifies combinations of prior art references that would render the claims of US Patent 8271315 obvious to a person having ordinary skill in the art (POSITA) at the time of the invention (i.e., before the effective priority date of May 7, 2001). The core objective of US8271315, as stated in its abstract, is to "improve quality of service for customers by sharing and utilizing personal information on customers among variety of industries." This objective itself provides a strong motivation for a POSITA to combine existing technologies to achieve cross-industry data sharing for targeted marketing.

Legal Standard for Obviousness

Under 35 U.S.C. § 103, a patent may not be obtained if "the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains." To establish obviousness, there must be some motivation or reason for a POSITA to combine the prior art references to achieve the claimed invention, with a reasonable expectation of success.

Obviousness of Independent Claim 1 (Personal Information Utilization System)

Claim 1 describes a system for a "second commodity provider" to identify potential customers based on information from a "first commodity provider."

Combination: US20010037294A1 (Freishtat) in combination with US7031934B2 (Hitachi) and US20020019817A1 (IBM).

Analysis:

1. Freishtat (US20010037294A1) as a Primary Reference: Freishtat describes a system for facilitating "syndicated transactions" by sharing customer data among "multiple participants" from "different industries" to create integrated offerings and bundled products or services. This directly teaches the fundamental concept of cross-industry sharing of customer information to facilitate related transactions, which is the stated objective of US8271315. Freishtat inherently discloses:

   • A "personal information storage means" for customer data.
   • Storing "first commodity provision information" (customer data related to initial transactions) provided by a "first commodity provider."
   • A scenario where a "second commodity provider" desires customer information from the "first commodity provider's" transactions.
   • A "communication means" for sharing this information.

2. Motivation to Combine with Hitachi (US7031934B2): Freishtat establishes the concept of cross-industry data sharing for syndicated transactions. However, to practically implement such a system, a POSITA would need a mechanism to identify specific customers for targeted offerings. Hitachi teaches an electronic commerce system that manages commercial information, product, and customer data, and delivers targeted commercial information to users based on their attributes and preferences or by accumulating purchasing history for personalized recommendations.

   • A POSITA, seeking to build out Freishtat's syndicated transaction system, would find it obvious to integrate the targeted marketing capabilities of Hitachi. Specifically, the steps of Claim 1(a)-(e) would be an obvious implementation:
     • (a) receiving second commodity provision information: A "second commodity provider" (e.g., a furniture vendor) providing an inquiry (second commodity provision information) to the central system to find customers for a related product (e.g., furniture).
     • (b) checking said received second commodity provision information against the first commodity provision information: The system using existing "first commodity provision information" (e.g., a house purchase from a housing vendor, which is the "first commodity") as criteria for identifying relevant customers.
     • (c) identifying, as a result of said checking, at least one specific information disclosing person...by using the second commodity provision information as a key such that the second commodity provision information at least partially coincides with the first commodity provision information: Identifying individuals who match the search criteria (e.g., those who recently purchased a house). Hitachi's teaching of matching customer data and purchasing history for targeted offerings makes this identification step obvious in the context of Freishtat's cross-industry objective.
     • (d) reading out at least a portion of the personal information: Retrieving the relevant personal information of identified individuals.
     • (e) transmitting said read out at least a portion of the personal information to said information search side terminal: Sending this information to the "second commodity provider."
   • The combination provides a clear and obvious path to enabling a furniture vendor (second commodity provider) to identify individuals who have purchased a house (first commodity provision information) to offer them furniture, directly aligning with the examples provided in US8271315. US20050240492A1 (Zipandshop L.L.C.) further reinforces this motivation by describing a system for matching users with ancillary services (like mortgages or moving services) based on a primary purchase like real estate.

3. Motivation to Combine with IBM (US20020019817A1): Given that the system involves sharing "personal information," a critical consideration for any commercially viable system would be privacy and user control. IBM discloses a system and method enabling users to selectively disclose their personal information to businesses, often in exchange for incentives, and encompasses managing user preferences for disclosure.

   • A POSITA would find it obvious to incorporate such privacy management features into a system for cross-industry personal information utilization. This ensures user consent and addresses privacy concerns, which are essential for the widespread adoption and legality of such a system. This combination directly anticipates or makes obvious the "information on disclosure limits" feature mentioned in dependent claims 5 and 8 of US8271315. US20020103806A1 (Yamanoue) further supports this by teaching systems for controlling the supply of data, including personal information, and addressing data privacy and access management.

Therefore, a POSITA, motivated to implement a system for sharing customer data across industries for syndicated transactions (Freishtat) and improve customer service by providing targeted offerings, would obviously combine known methods for targeted marketing based on purchase history (Hitachi/Sony/Zipandshop) with established mechanisms for managing personal information privacy and disclosure limits (IBM/Yamanoue).

Obviousness of Independent Claim 2 (Non-Transitory Computer-Readable Medium with Program)

Claim 2 describes a non-transitory computer-readable medium having a program that, when executed, performs a method substantially similar to the system described in Claim 1.

Analysis:
The obviousness analysis for Claim 1 directly applies to Claim 2. Once the system described in Claim 1 is rendered obvious by the combination of prior art, implementing the corresponding method steps as a computer program stored on a non-transitory computer-readable medium would be an obvious design choice for a POSITA in the field of software development. All the functional steps of receiving, checking, identifying, reading out, and transmitting information are standard operations performed by computer programs. The prior art references themselves (e.g., Freishtat, Hitachi, IBM, Yamanoue) discuss systems and methods, often implying or explicitly mentioning their implementation via software or computer-readable media.

Obviousness of Dependent Claims

Many of the dependent claims (e.g., Claims 3, 4, 5, 6, 7, 8) are made obvious by the same combinations:

• Claims 3 & 6 (Registration of commodity provision information): The process of associating personal information with commodity provision information, receiving it from an "information register side terminal," checking, identifying, and registering it in the storage means (as described in 3 and 6) would be an obvious administrative function for any system like Freishtat's or Hitachi's that relies on accumulating and managing customer transaction data. Freishtat's system of "syndicated transactions" necessarily implies the registration of initial transaction data by the "first commodity provider."
• Claims 4 & 7 (Information searching person): Specifying the "information searching person" as a manufacturer, sales vendor, service trader, self-governing body, or education foundation simply lists various entities that would logically benefit from such a cross-industry information sharing system, and thus provides a common motivation for using such a system, rather than adding a non-obvious limitation.
• Claims 5 & 8 (Disclosure limits): These claims explicitly describe managing personal information in accordance with "information on disclosure limits." As discussed in the independent claims analysis, the incorporation of privacy controls, as taught by IBM (US20020019817A1) and Yamanoue (US20020103806A1), would be an obvious and necessary feature for a personal information sharing system, driven by ethical, legal, and practical considerations.
• Claims 9 & 10 (Automatic registration, specific information): The automatic registration of commodity provision information (Claim 9) and the specific types of information (name of item, vendor, date) in commodity provision information (Claim 10) are conventional features in database management and e-commerce systems, exemplified by Hitachi's detailed approach to storing purchase history.
• Claim 11 (Identifying previously unknown identity): The act of "determining an identity, previously unknown to be associated with the second commodity provision information" is the inherent and obvious outcome of using a search key (second commodity provision information) to match against a database containing other information (first commodity provision information and associated personal details), as taught by the combination of Freishtat and Hitachi.
• Claims 13 & 14 (Service as a commodity): Defining "commodity" to include "service" is explicitly stated in the background and definitions of US8271315 itself and is a common understanding in commerce and information systems. The prior art references generally use "goods/services" interchangeably. For example, Freishtat mentions "goods or services" and Zipandshop describes "commodity-like goods/services."

In conclusion, the core claims of US Patent 8271315, and its dependent claims, describe a logical combination of well-known information sharing, targeted marketing, and privacy management techniques prevalent in the prior art before the patent's priority date. A person of ordinary skill in the art would have been motivated to combine these references to create a system for improved cross-industry customer identification and service, as described by the patent.

To provide a comprehensive analysis for US Patent 8271315, I will gather information on its patent term adjustments (PTA), patent term extensions (PTE), continuation/divisional applications, related family members, and projected expiration date.

Patent Term Adjustments (PTA)

Patent Term Adjustment (PTA) can extend the term of a patent to compensate for certain delays by the USPTO during the prosecution of the patent application. These delays can include the USPTO failing to:

• Issue a first Official Action or notice of allowance within 14 months of filing.
• Issue an action within four months of an applicant's response.
• Issue the patent within four months of payment of the issue fee.
• Issue a patent within three years of the actual filing date (with some exceptions).

Applicant delays can reduce any awarded PTA.

To determine the specific PTA for US8271315, one would typically consult the patent's issue certificate or its file wrapper in USPTO's Patent Center. Without direct access to these specific documents for US8271315, I cannot provide the exact PTA amount. However, since the patent was filed on November 5, 2002, and issued on September 18, 2012, it was subject to PTA provisions.

Patent Term Extensions (PTE)

Patent Term Extensions (PTE) are distinct from PTAs and are primarily available for patents covering certain human drug products, medical devices, food or color additives, animal drugs, and veterinary biological products. PTE compensates for time lost during mandatory pre-market regulatory review by agencies like the FDA.

Based on the title and subject matter of US8271315, "Personal information utilization system and personal information utilization program for commodity based identification," it is highly unlikely to be eligible for a Patent Term Extension under 35 U.S.C. § 156, as it does not appear to cover a product subject to regulatory approval in the fields mentioned. Therefore, I can confidently state that there are no Patent Term Extensions for US8271315.

Continuation Applications, Divisional Applications, and Related Family Members

• Continuation Applications: A continuation application is a new application for an invention disclosed in a prior, co-pending non-provisional application, where the disclosure does not introduce new subject matter. It allows the applicant to pursue additional claims to the same invention.
• Divisional Applications: A divisional application arises from a restriction requirement by the USPTO, where the examiner determines that an application contains more than one distinct invention. The applicant can then pursue the non-elected invention(s) in a divisional application, benefiting from the filing date of the original application.

The patent document itself lists "Other versions" and "Applications Claiming Priority" which can indicate related family members:

• US20060155646A1: This is listed as "Other versions" and is the publication of the application for US8271315, published on July 13, 2006. It is not a separate continuation or divisional application, but an earlier publication stage of the same patent.
• PCT/JP2002/011502 (WO2004042610A1): This is listed as an "Applications Claiming Priority" with a priority date of 2001-05-07. This is an international (PCT) application that serves as the basis for the US patent and is a related family member. The US application (US10/533,859) claims priority from this PCT application.
• JP2002329058A: This Japanese patent application is also listed in the "Citations" and has the same priority date (2001-05-07) and inventor. This indicates it is a parallel foreign filing or a closely related family member to US8271315.

Based on the provided information, there are no explicit continuation or divisional applications listed directly under the US8271315 patent information. The primary related family members are the international PCT application PCT/JP2002/011502 (WO2004042610A1) and the Japanese application JP2002329058A.

Projected Expiration Date

The standard patent term for utility patents filed on or after June 8, 1995, is 20 years from the earliest claimed non-provisional filing date. The filing date for US8271315 (US10/533,859) is November 5, 2002. [cite: https://patents.google.com/patent/US8271315/en]

Therefore, the nominal expiration date (20 years from the filing date) would be November 5, 2022.

However, the legal status explicitly states "Expired - Fee Related , expires 2024-02-26" and also "2024-10-21 Lapse for failure to pay maintenance fees". [cite: https://patents.google.com/patent/US8271315/en] This indicates that despite the nominal term extending to 2022 (or later with PTA), the patent's enforceability ceased earlier due to failure to pay maintenance fees. The "Adjusted expiration" date listed as 2024-02-26 implies there may have been some PTA that extended the nominal 20-year term. The "Lapse for failure to pay maintenance fees" on 2024-10-21 confirms that the patent is no longer in force.

Therefore, the patent US8271315 is expired due to failure to pay maintenance fees, with the last recorded expiration related event being October 21, 2024.

Defensive Disclosure: Derivative Variations of US Patent 8271315

This document outlines various derivative concepts and implementations building upon the core principles of US Patent 8271315, specifically targeting Independent Claims 1 (Personal Information Utilization System) and 2 (Non-Transitory Computer-Readable Medium with Program). The objective is to proactively disclose variations that render future incremental improvements or alternative embodiments in this technological space obvious or non-novel, thereby strengthening the public domain as prior art.

---

Derivative Variations

1. Material & Component Substitution: Distributed Ledger Technology for Storage and Communication

Enabling Description:
This derivative implements the personal information storage means (12) and communication means (8) of US8271315 using a distributed ledger technology (DLT), such as a permissioned blockchain network. Each "personal information disclosing person" maintains a self-sovereign identity (SSI) on the DLT, where their personal information (ID number, name, contact, etc.) is stored as verifiable credentials (VCs) issued by trusted authorities. The "commodity provision information, etc." (CPI) is recorded as immutable transactions on the ledger, linking an anonymized or pseudonymized identifier of the disclosing person to the attribute information of the commodity/service and its provider. Smart contracts govern the receipt, checking, identification, and transmission steps. The "information search side terminal" (second commodity provider) initiates a query via a smart contract, presenting "second commodity provision information" as a parameter. The smart contract, upon execution and verification of appropriate consent tokens (managed by the disclosing person's SSI wallet), checks this against the on-chain "first commodity provision information." Identification occurs by resolving on-chain identifiers linked to matching CPI, and the transmission of (optionally revealed) personal information is facilitated by encrypted data exchange or selective disclosure proofs validated by the smart contract. Data is stored across a network of decentralized nodes, replacing a single hard disk (12) and router (8) with a distributed, redundant, and auditable infrastructure.

flowchart TD
    subgraph Information Disclosing Person (IDP) Network
        IDP1(IDP Wallet/SSI) -- Grants Consent --> SC(Smart Contract)
        IDP2(IDP Wallet/SSI) -- Grants Consent --> SC
    end

    subgraph DLT Network
        SC -- Query First CPI --> DLT_Storage(Distributed Ledger Storage: Personal Info VCs + CPI Transactions)
        DLT_Storage -- Immutable Record --> NodeA
        DLT_Storage -- Immutable Record --> NodeB
        DLT_Storage -- Immutable Record --> NodeC
    end

    subgraph Information Search Side Terminal (ISST) Network
        ISST(Second Commodity Provider) -- Sends Second CPI --> SC
    end

    SC -- Checks Second CPI vs First CPI --> DLT_Storage
    SC -- Identifies Matching IDPs --> DLT_Storage
    SC -- Requests Personal Info (VCs) --> DLT_Storage
    SC -- Transmits Personal Info (Encrypted/SD) --> ISST

    style IDP1 fill:#f9f,stroke:#333,stroke-width:2px
    style IDP2 fill:#f9f,stroke:#333,stroke-width:2px
    style SC fill:#ccf,stroke:#333,stroke-width:2px
    style DLT_Storage fill:#cfc,stroke:#333,stroke-width:2px
    style NodeA fill:#eee,stroke:#333,stroke-width:1px
    style NodeB fill:#eee,stroke:#333,stroke-width:1px
    style NodeC fill:#eee,stroke:#333,stroke-width:1px
    style ISST fill:#f9f,stroke:#333,stroke-width:2px

2. Material & Component Substitution: Quantum-Resistant Cryptography and Homomorphic Encryption for Privacy

Enabling Description:
This derivative enhances the privacy aspects of US8271315 by employing post-quantum cryptographic algorithms and homomorphic encryption (HE). The personal information storage means (12) encrypts all "personal information" and "commodity provision information, etc." using a hybrid encryption scheme where the symmetric keys are themselves encrypted with quantum-resistant public-key cryptography (e.g., Lattice-based cryptography such as CRYSTALS-Kyber for key encapsulation and CRYSTALS-Dilithium for digital signatures). Furthermore, critical attributes of "personal information" (e.g., age ranges, location hashes) and "commodity provision information" (e.g., commodity types, provider categories) are homomorphically encrypted. The processing means (14) is augmented with a specialized homomorphic computation unit, allowing it to perform the "checking" and "identifying" steps directly on the encrypted data without decryption. This means the server never sees the plaintext personal information or search queries. The "read out personal information" transmitted to the "information search side terminal" is still in an encrypted state, with decryption keys only released upon verified consent from the "information disclosing person" via an out-of-band secure channel (e.g., multi-party computation protocol or secure enclave interaction).

sequenceDiagram
    participant IDP as Information Disclosing Person
    participant ISST as Information Search Side Terminal
    participant PP as Processing Means (Server)
    participant PS as Personal Information Storage Means

    IDP->>PS: Stores HE-encrypted Personal Info (PI_HE) + CPI_HE
    ISST->>PP: Sends HE-encrypted Search Query (SQ_HE)
    PP->>PS: Requests CPI_HE relevant to SQ_HE
    PS-->>PP: Returns CPI_HE
    PP->>PP: Performs Homomorphic Checking (SQ_HE vs CPI_HE)
    PP->>PP: Identifies IDP_HE
    PP->>PS: Requests PI_HE for IDP_HE
    PS-->>PP: Returns PI_HE
    PP->>ISST: Transmits PI_HE (Encrypted, awaiting IDP consent)
    IDP->>ISST: Grants Decryption Consent (Out-of-band, secure channel)
    ISST->>ISST: Decrypts PI_HE to PI (plaintext)

3. Operational Parameter Expansion: Hyper-Scale Industrial Data Lake for B2B Information Exchange

Enabling Description:
This derivative scales the system of US8271315 to operate on a hyper-scale industrial data lake infrastructure, specifically designed for business-to-business (B2B) information exchange across a global consortium of enterprises. The personal information storage means (12) is realized as a distributed object storage layer (e.g., Apache Hadoop HDFS or AWS S3), capable of storing petabytes of structured and unstructured "personal information" and "commodity provision information, etc." from millions of "information disclosing persons" and thousands of "first commodity providers." The processing means (14) leverages a big data processing framework (e.g., Apache Spark on Kubernetes) for highly parallelized ingestion, indexing, and querying. The "checking" and "identifying" operations are performed using advanced data warehousing techniques and federated query engines, optimized for high-throughput batch analysis (e.g., daily customer segment identification) and low-latency ad-hoc searches (e.g., real-time lead generation). Communication means (8) are industrial-grade secure APIs and data pipelines, ensuring reliable and high-volume data transfer between the central system and geographically dispersed "information search side terminals." Data governance and anonymization pipelines (e.g., differential privacy techniques) are integrated to manage privacy at scale.

graph TD
    subgraph Data Ingestion Layer
        FP1(First Provider 1) --> DLI
        FP2(First Provider 2) --> DLI
        FPn(First Provider n) --> DLI
        DLI[Data Lake Ingest Service] --> DataLake(Hyper-Scale Data Lake: Raw PI + CPI)
    end

    subgraph Data Processing & Analytics Layer
        DataLake -- ETL/Processing --> DWS(Data Warehouse & Indexing Service)
        DWS -- Batch Processing --> BPE(Big Data Processing Engine - Spark/Kubernetes)
        DWS -- Real-time Query --> FQE(Federated Query Engine)
    end

    subgraph API & Communication Layer
        ISST(Information Search Side Terminal) -- API Request (Second CPI) --> API(Secure API Gateway)
        API --> FQE
        FQE --> BPE -- Results --> API
        API -- Transmits PI --> ISST
    end

    style FP1 fill:#f9f,stroke:#333,stroke-width:2px
    style FP2 fill:#f9f,stroke:#333,stroke-width:2px
    style FPn fill:#f9f,stroke:#333,stroke-width:2px
    style ISST fill:#f9f,stroke:#333,stroke-width:2px
    style DataLake fill:#cfc,stroke:#333,stroke-width:2px
    style BPE fill:#ccf,stroke:#333,stroke-width:2px
    style FQE fill:#ccf,stroke:#333,stroke-width:2px

4. Operational Parameter Expansion: Edge Computing for Localized Micro-Commodity Matching

Enabling Description:
This derivative deploys the system of US8271315 onto localized edge computing devices for highly granular, real-time matching within a constrained geographical or personal environment. Each "information disclosing person" possesses a personal edge device (e.g., a smart home hub, a local server, or a powerful wearable). This edge device acts as the personal information storage means (12) for that individual, holding their "personal information" and "first commodity provision information" locally. The processing means (14) is implemented as a lightweight, optimized microservice running on the edge device itself. "Second commodity provision information" (e.g., availability of a local delivery service, a nearby event, or a personalized offer from a specific local vendor) is received from "information search side terminals" (local businesses, service providers) via short-range wireless communication means (e.g., Bluetooth Low Energy, local Wi-Fi, NFC, or secure mesh networks). The checking, identification, and reading out of (optionally anonymized) personal information occur directly on the edge device, minimizing latency and enhancing privacy by reducing cloud data transfers. Only highly aggregated or strictly consented-to information, or a direct notification to the user, is transmitted back to the external "information search side terminal."

graph TD
    subgraph Edge Device (Information Disclosing Person)
        Local_Storage(Local PI & CPI Storage)
        Local_Processor(Local Matching Engine)
        Local_Comm(Local Wireless Comm. Module)
        Local_Storage -- Stores/Retrieves --> Local_Processor
        Local_Comm -- Receives Second CPI --> Local_Processor
        Local_Processor -- Identifies/Reads --> Local_Comm
    end

    subgraph Local Environment (Information Search Side Terminal)
        LBP(Local Business Provider) -- Sends Second CPI --> Local_Comm
        LSS(Local Service Supplier) -- Sends Second CPI --> Local_Comm
        Local_Comm -- Transmits Matched Info/Notification --> LBP
        Local_Comm -- Transmits Matched Info/Notification --> LSS
    end

    style Local_Storage fill:#cfc,stroke:#333,stroke-width:2px
    style Local_Processor fill:#ccf,stroke:#333,stroke-width:2px
    style Local_Comm fill:#f9f,stroke:#333,stroke-width:2px
    style LBP fill:#f9f,stroke:#333,stroke-width:2px
    style LSS fill:#f9f,stroke:#333,stroke-width:2px

5. Cross-Domain Application: Precision Agriculture (AgTech)

Enabling Description:
In a precision agriculture context, the system is used to optimize resource allocation and procurement for farms. The "personal information storage means" (12) stores farm profiles ("personal information" of the "information disclosing person" - the farm owner/manager), including attributes like soil composition, crop types, historical yields, and environmental conditions. The "first commodity provision information" stored pertains to past purchases of seeds, fertilizers, pesticides, machinery, or received agronomical services from "first commodity providers" (e.g., seed distributors, chemical companies, equipment dealers). An "information search side terminal" (e.g., a new fertilizer supplier, a farm machinery leasing company - the "second commodity provider") submits "second commodity provision information" (e.g., a query for farms that grow corn and used a specific type of nitrogen fertilizer last season). The processing means (14) checks this query against the stored CPI and identifies farms (disclosing persons) that match these criteria. The system then reads out and transmits relevant farm profile information (e.g., contact details, farm size, location, current crop cycle) to the new supplier, enabling targeted offers for complementary products or services.

graph LR
    subgraph Farm Data Hub (Server Device 1)
        FarmDB(Farm Profiles & Historical CPI Storage)
        AgronomicProcessor(Matching & Retrieval Processor)
    end

    subgraph Farm Owner / Manager Network (Information Disclosing Persons)
        FO1(Farm Owner 1) -- Registers Farm Profile & CPI --> FarmDB
        FO2(Farm Owner 2) -- Registers Farm Profile & CPI --> FarmDB
    end

    subgraph AgTech Vendor Network (Information Search Side Terminals)
        FSup(Fertilizer Supplier - 2nd Provider) -- Queries (2nd CPI) --> AgronomicProcessor
        MfrLease(Machinery Lessor - 2nd Provider) -- Queries (2nd CPI) --> AgronomicProcessor
    end

    AgronomicProcessor -- Checks CPI --> FarmDB
    AgronomicProcessor -- Identifies Matching Farms --> FarmDB
    AgronomicProcessor -- Transmits Farm Profiles (PI) --> FSup
    AgronomicProcessor -- Transmits Farm Profiles (PI) --> MfrLease

    style FarmDB fill:#cfc,stroke:#333,stroke-width:2px
    style AgronomicProcessor fill:#ccf,stroke:#333,stroke-width:2px
    style FSup fill:#f9f,stroke:#333,stroke-width:2px
    style MfrLease fill:#f9f,stroke:#333,stroke-width:2px

6. Cross-Domain Application: Disaster Response & Humanitarian Aid

Enabling Description:
In the context of disaster relief, this system facilitates efficient allocation of aid. The "personal information storage means" (12) stores profiles of affected individuals and families ("information disclosing persons"), including essential personal details, medical needs, family composition, and shelter/resource preferences. "First commodity provision information" records aid received from "first commodity providers" (e.g., food rations from NGO A, medical supplies from Agency B, temporary shelter from Government C). An "information search side terminal" (e.g., a new medical team arriving in the region, a water purification unit, a clothing distributor - the "second commodity provider") transmits "second commodity provision information" (e.g., "available medical capacity for trauma patients," "purified water for 500 people," "winter clothing for children"). The processing means (14) matches this against the stored CPI to identify individuals (disclosing persons) who have unmet needs corresponding to the available aid. The system then reads out and transmits relevant anonymized or aggregated personal information (or direct encrypted contact details with explicit prior consent) to the "second commodity provider," ensuring aid reaches those most in need without duplication of efforts.

flowchart TD
    subgraph Humanitarian Data Exchange (Server Device 1)
        AIDB(Aid Recipient Profiles & Aid Provision History Storage)
        ReliefCoordinator(Matching & Prioritization Processor)
    end

    subgraph Affected Persons Network (Information Disclosing Persons)
        AP1(Affected Person 1) -- Registers Needs & Received Aid --> AIDB
        AP2(Affected Person 2) -- Registers Needs & Received Aid --> AIDB
    end

    subgraph Aid Provider Network (Information Search Side Terminals)
        MedTeam(Medical Team - 2nd Provider) -- Queries (2nd CPI - e.g., Trauma Capacity) --> ReliefCoordinator
        WaterPurif(Water Purification - 2nd Provider) -- Queries (2nd CPI - e.g., Water for X ppl) --> ReliefCoordinator
    end

    ReliefCoordinator -- Checks CPI --> AIDB
    ReliefCoordinator -- Identifies Unmet Needs --> AIDB
    ReliefCoordinator -- Transmits Anonymized PI/Direct Contact --> MedTeam
    ReliefCoordinator -- Transmits Anonymized PI/Direct Contact --> WaterPurif

    style AIDB fill:#cfc,stroke:#333,stroke-width:2px
    style ReliefCoordinator fill:#ccf,stroke:#333,stroke-width:2px
    style MedTeam fill:#f9f,stroke:#333,stroke-width:2px
    style WaterPurif fill:#f9f,stroke:#333,stroke-width:2px

7. Cross-Domain Application: Scientific Research Collaboration

Enabling Description:
This derivative supports inter-institutional scientific research by facilitating the identification of collaborators. The "personal information storage means" (12) stores researcher profiles ("personal information" of "information disclosing persons"), including their areas of expertise, publications, current projects, and institutional affiliations. "First commodity provision information" records usage of specialized equipment, access to unique datasets, or participation in specific research grants ("commodities") provided by "first commodity providers" (e.g., core lab facilities, data repositories, funding agencies). An "information search side terminal" (e.g., a principal investigator seeking collaborators for a new grant, a research team with a novel assay technique - the "second commodity provider") transmits "second commodity provision information" (e.g., "seeking researchers who used Cryo-EM within the last year," "looking for labs with access to genomic data from specific patient cohorts"). The processing means (14) checks this query against stored CPI and identifies researchers (disclosing persons) with the relevant equipment usage or data access history. The system then reads out and transmits pertinent anonymized researcher profile information (e.g., institutional contact, high-level expertise) to the "second commodity provider," fostering new collaborative opportunities.

graph TD
    subgraph Research Data Exchange (Server Device 1)
        ResearcherDB(Researcher Profiles & Resource Usage History Storage)
        CollaborationMatcher(Matching & Discovery Processor)
    end

    subgraph Research Community (Information Disclosing Persons)
        R1(Researcher A) -- Registers Profile & Resource Usage --> ResearcherDB
        R2(Researcher B) -- Registers Profile & Resource Usage --> ResearcherDB
    end

    subgraph Collaborative Seeker Network (Information Search Side Terminals)
        PI_Seeking(PI seeking collaborators - 2nd Provider) -- Queries (2nd CPI - e.g., Cryo-EM users) --> CollaborationMatcher
        Team_Offering(Team with new assay - 2nd Provider) -- Queries (2nd CPI - e.g., Genomic data access) --> CollaborationMatcher
    end

    CollaborationMatcher -- Checks CPI --> ResearcherDB
    CollaborationMatcher -- Identifies Relevant Researchers --> ResearcherDB
    CollaborationMatcher -- Transmits Anonymized PI --> PI_Seeking
    CollaborationMatcher -- Transmits Anonymized PI --> Team_Offering

    style ResearcherDB fill:#cfc,stroke:#333,stroke-width:2px
    style CollaborationMatcher fill:#ccf,stroke:#333,stroke-width:2px
    style PI_Seeking fill:#f9f,stroke:#333,stroke-width:2px
    style Team_Offering fill:#f9f,stroke:#333,stroke-width:2px

8. Integration with Emerging Tech: AI-Driven Predictive Recommendation Engine

Enabling Description:
This derivative augments the processing means (14) of US8271315 with an advanced AI-driven predictive recommendation engine. Beyond simple matching, the engine analyzes "personal information" and historical "first commodity provision information" using machine learning models (e.g., collaborative filtering, deep learning-based recommender systems) to predict future needs or preferences of "information disclosing persons." When "second commodity provision information" is received, the AI engine not only performs the direct matching but also identifies information disclosing persons who are likely to be interested in the "second commodity" even if they haven't directly received a perfectly matching "first commodity." This involves:

1. Feature Engineering: Extracting latent features from personal and commodity data.
2. Model Training: Training a predictive model on historical data of successful cross-selling and service adoption.
3. Scoring & Ranking: The AI scores potential matches and ranks them by predicted relevance.
   The "read out personal information" transmitted to the "information search side terminal" includes not just the identified personal details but also a "propensity score" or predicted interest level generated by the AI, enabling the second commodity provider to prioritize their outreach.

graph TD
    subgraph Server Device 1 (Processing Means 14)
        PI_Storage(Personal Info & CPI Storage)
        DataIngest(Data Ingestion & Feature Eng.)
        AI_Model_Train(AI Model Training - Offline)
        AI_Rec_Engine(AI Recommendation Engine - Online)
    end

    subgraph External Inputs
        IDP_Input(IDP Personal Info & First CPI) --> DataIngest
        ISST_Query(Second CPI from Search Terminal) --> AI_Rec_Engine
    end

    DataIngest -- Feeds --> PI_Storage
    PI_Storage -- Training Data --> AI_Model_Train
    AI_Model_Train -- Deploys --> AI_Rec_Engine
    AI_Rec_Engine -- Matches & Predicts --> PI_Storage
    AI_Rec_Engine -- Transmits PI + Propensity Score --> ISST_Output(Information Search Side Terminal)

    style PI_Storage fill:#cfc,stroke:#333,stroke-width:2px
    style DataIngest fill:#eee,stroke:#333,stroke-width:1px
    style AI_Model_Train fill:#add8e6,stroke:#333,stroke-width:2px
    style AI_Rec_Engine fill:#add8e6,stroke:#333,stroke-width:2px
    style IDP_Input fill:#f9f,stroke:#333,stroke-width:2px
    style ISST_Query fill:#f9f,stroke:#333,stroke-width:2px
    style ISST_Output fill:#f9f,stroke:#333,stroke-width:2px

9. Integration with Emerging Tech: IoT-Enabled Real-time Contextual Matching

Enabling Description:
This derivative integrates real-time data streams from Internet of Things (IoT) sensors as a dynamic source of "commodity provision information, etc." The personal information storage means (12) stores static personal profiles and historical CPI. However, the processing means (14) continuously ingests and processes live sensor data (e.g., smart home appliance usage patterns, environmental conditions, vehicle diagnostics, biometric data from wearables – representing very granular "first commodity provision information" or implicit needs derived therefrom) via the communication means (8). An "information search side terminal" (e.g., a utility company, an appliance repair service, a health & wellness provider - "second commodity providers") submits "second commodity provision information" (e.g., "identified abnormal energy consumption," "predictive maintenance alert for specific appliance model," "wearable detected elevated stress levels"). The processing means (14) then performs real-time checking against the current and historical IoT-derived CPI. It identifies "information disclosing persons" whose real-time context matches the "second commodity provision information" and transmits a portion of their (consented) personal information or a direct contextual alert to the "information search side terminal." This enables highly timely and context-aware service provision.

graph TD
    subgraph Server Device 1 (Processing Means 14)
        PI_Storage(Personal Info & Historical CPI)
        IoT_DataStream(IoT Data Stream Ingest)
        RealtimeProcessor(Real-time Matching & Alerting Engine)
    end

    subgraph IoT Devices & Networks
        IoT_Sensor1(Smart Appliance 1) --> IoT_DataStream
        IoT_Sensor2(Wearable Device) --> IoT_DataStream
        IoT_Sensorn(Vehicle Diagnostic) --> IoT_DataStream
    end

    subgraph Information Search Side Terminal Network
        UtilityCo(Utility Company - 2nd Provider) -- Queries (2nd CPI - e.g., High Energy Usage) --> RealtimeProcessor
        RepairSvc(Repair Service - 2nd Provider) -- Queries (2nd CPI - e.g., Appliance Fault) --> RealtimeProcessor
    end

    IoT_DataStream -- Feeds Real-time CPI --> RealtimeProcessor
    RealtimeProcessor -- Checks Real-time + Historical CPI --> PI_Storage
    RealtimeProcessor -- Identifies IDP in Context --> PI_Storage
    RealtimeProcessor -- Transmits PI/Contextual Alert --> UtilityCo
    RealtimeProcessor -- Transmits PI/Contextual Alert --> RepairSvc

    style PI_Storage fill:#cfc,stroke:#333,stroke-width:2px
    style IoT_DataStream fill:#eee,stroke:#333,stroke-width:1px
    style RealtimeProcessor fill:#ccf,stroke:#333,stroke-width:2px
    style UtilityCo fill:#f9f,stroke:#333,stroke-width:2px
    style RepairSvc fill:#f9f,stroke:#333,stroke-width:2px

10. The "Inverse" or Failure Mode: Privacy-Preserving Anonymized Aggregation Mode

Enabling Description:
This derivative describes an operational mode where the system prioritizes privacy by default, functioning primarily as an anonymized aggregation and trend analysis platform, and only escalating to individual personal information disclosure under stringent, explicit, and audited consent. In this "Privacy-Preserving Anonymized Aggregation Mode," the personal information storage means (12) and processing means (14) are configured to:

1. Anonymize & Aggregate: When "first commodity provision information" is stored, it is immediately anonymized and aggregated with other similar data points. "Personal information" is stored in a segregated, highly secured, and encrypted vault, accessed only under exceptional circumstances.
2. Trend Analysis: The "information search side terminal" receives "second commodity provision information" as a query, but the processing means (14) defaults to returning only anonymized, aggregated demographic trends or commodity uptake statistics that coincide with the query (e.g., "50% of households in zip code XYZ that bought a baby blanket also bought furniture within 6 months"). No individual "personal information" is read out or transmitted.
3. Granular Consent for Individual Disclosure: If an "information search side terminal" explicitly requests individual "personal information," a multi-stage, auditable consent process is initiated directly with the "information disclosing person" via their "information disclosure side terminal." Only upon receiving explicit, time-limited, and purpose-bound consent for specific data fields, is that portion of the encrypted personal information read out from the vault and transmitted. This mode also acts as a safe-failure mechanism, preventing accidental or unauthorized individual data disclosure by default.

graph TD
    subgraph Server Device 1 (Privacy-Preserving Mode)
        Vault_PI(Encrypted Personal Info Vault)
        CPI_Aggregator(Anonymized CPI Aggregation & Trend Storage)
        PrivacyProcessor(Processing Means - Default Aggregation)
    end

    subgraph User Interaction
        IDP(Information Disclosing Person) -- Granular Consent Request --> PrivacyProcessor
        IDP -- Stores PI (Encrypted) & CPI --> Vault_PI
        IDP -- Consent Confirmation --> ISST_Receiver(Information Search Side Terminal)
    end

    subgraph Information Search Side Terminal
        ISST_Sender(Search Terminal - Sends Query for 2nd CPI) --> PrivacyProcessor
    end

    PrivacyProcessor -- Default: Returns Aggregated Trends --> ISST_Receiver
    PrivacyProcessor -- Explicit Request for PI --> Vault_PI
    Vault_PI -- Triggers Consent Request --> IDP
    PrivacyProcessor -- IF Consent GRANTED: Reads Specific PI --> Vault_PI
    PrivacyProcessor -- Transmits Specific PI (Encrypted) --> ISST_Receiver

    style Vault_PI fill:#cfc,stroke:#333,stroke-width:2px
    style CPI_Aggregator fill:#cfc,stroke:#333,stroke-width:2px
    style PrivacyProcessor fill:#ccf,stroke:#333,stroke-width:2px
    style IDP fill:#f9f,stroke:#333,stroke-width:2px
    style ISST_Sender fill:#f9f,stroke:#333,stroke-width:2px
    style ISST_Receiver fill:#f9f,stroke:#333,stroke-width:2px

---

Combination Prior Art Scenarios with Open-Source Standards

These scenarios illustrate how the system and method of US8271315, and its derivatives, can be combined with existing open-source standards, thereby contributing to the obviousness of further developments.

1. US8271315 System + OAuth 2.0 / OpenID Connect for Consent Management:

   • Description: The "information on disclosure limits" functionality described in dependent claims 5 and 8 of US8271315, which allows "information disclosing persons" to manage their privacy, can be readily implemented using the OAuth 2.0 authorization framework and OpenID Connect (OIDC) authentication layer. An "information disclosing person" would grant specific scopes (e.g., "read personal contact," "read commodity type") to a "second commodity provider" (acting as a client application) through the system (acting as an authorization server). OIDC would handle user authentication and identity verification. This standard integration makes the user consent mechanism robust, interoperable, and well-understood by a person having ordinary skill in the art.
   • Open-Source Standard: OAuth 2.0 (RFC 6749) and OpenID Connect. Many open-source implementations exist (e.g., Keycloak, Auth0, Dex).

2. US8271315 System + Apache Kafka for Real-time CPI Ingestion:

   • Description: For large-scale and real-time environments, the process of receiving "commodity provision information, etc." from "information register side terminals" (as per dependent claims 3 and 6) and from "first commodity providers" (implicitly in claims 1 and 2) can be implemented using Apache Kafka. Kafka, a distributed streaming platform, would act as the communication means (8) for high-throughput, fault-tolerant ingestion of CPI into the "personal information storage means" (12). "First commodity providers" would publish CPI events to Kafka topics, which the processing means (14) would then consume for real-time updating of personal information records and immediate availability for "information search side terminal" queries. This addresses the need for timely data updates mentioned in the patent's objectives (e.g., "in good timing").
   • Open-Source Standard: Apache Kafka.

3. US8271315 DLT Derivative (as described in Derivative 1) + Hyperledger Fabric for Permissioned Blockchain Implementation:

   • Description: The derivative concept of using distributed ledger technology for storage and communication (Derivative 1) can be concretely realized using Hyperledger Fabric. Fabric provides a permissioned blockchain framework where "first commodity providers" and the central system operator (Keysoft Inc. in the original patent) can operate as authenticated peers. Smart contracts (chaincode in Fabric) would implement the logic for receiving "second commodity provision information," checking it against on-chain "first commodity provision information," identifying "information disclosing persons," and conditionally releasing encrypted or selectively disclosed personal information. User identities and consent tokens could be managed via Fabric's identity services and private data collections, providing a robust, auditable, and secure environment for cross-industry data sharing.
   • Open-Source Standard: Hyperledger Fabric.