DETAILED ACTION
The following Non-Final office action is in response to application 18/425,787 filed on 1/9/2024. IDS filed 3/19/2025 has been considered.
Status of Claims
Claims 1-20 are currently pending and have been rejected as follows.
Claim Objections
Claim 6 is objected to because of the following informalities: Claim 6 recites “wherein the CERT data comprises information related to certifications, standards, accreditation, conformity assurance and validations of the item, wherein the CERT data further comprises social attributes, environmental attributes, governance attributes, origin attributes and quality attributes (SEQ attributes) of the item, wherein the CERT information is based at least on the SEQ data, wherein the SEQ data is identified via analysis of the CERT data via the AI model” while it is believed and interpreted, for purposes of compact prosecution, it should recite “wherein the CERT data comprises information related to certifications, standards, accreditation, conformity assurance and validations of the item, wherein the CERT data further comprises social attributes, environmental attributes, governance attributes, origin attributes and quality attributes (SEQ attributes) of the item, wherein the CERT information is based at least on the SEQ attributes , wherein the SEQ attributes is identified via analysis of the CERT data via the AI model.” Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are clearly drawn to at least one of the four categories of patent eligible subject matter recited in 35 U.S.C. 101 (method, device, and non-transitory computer readable storage medium). Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without integrating the abstract idea into a practical application or amounting to significantly more than the abstract idea.
Regarding Step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance (‘2019 PEG”), Claims 1-10 are directed toward the statutory category of a process (reciting a “method”). Claims 11-15 are directed toward the statutory category of a machine (reciting a “device”). Claims 16-20 are directed toward the statutory category of an article of manufacturer (reciting a “non-transitory computer readable storage medium”).
Regarding Step 2A, prong 1 of the 2019 PEG, Claims 1, 11 and 16 are directed to an abstract idea by reciting identifying, by …, electronic information related to an item, the information comprising certification (CERT) data and material data related to the item; analyzing, via … executing an artificial intelligence (AI) model, the electronic information; determining, by …, based on the AI analysis of the CERT data, CERT information for the item, CERT information indicating a status of at least one certification related to a manufacture of the item; determining, by …, based on the AI analysis of the material data, material information for the item, the material information indicating a status of a type of at least one material constituting the item; determining, by …, an item status for the item based on AI analysis of the CERT information and the material information; and […] (Example Claim 1).
The claims are considered abstract because these steps recite certain methods of organizing human activity like commercial interactions (including sales activities or behaviors, and business relations). The claims recite steps to analyze item information based on at least certifications and materials to determine an item status and curating a display of the item based on the item status, which are commercial interactions. It is understood that the claimed steps aim to ensure regulatory compliance and promote sustainable, quality, eco-friendly, and durable choices through the claimed assessment and display curation (Applicant’s Specification, [0002]-[0003]). By this evidence, the claims recite a type of “certain methods of organizing human activity like commercial interactions” common to judicial exception to patent-eligibility. By preponderance, the claims recite an abstract idea (e.g., a “unified network infrastructure” for assessing item information and dynamically curating and displaying items).
Regarding Step 2A, prong 2 of the 2019 PEG, the judicial exception is not integrated into a practical application because the claims (the judicial exception and the additional elements such as a device; dynamically curating, by the device over a network, display of the item on a network resource based on the item status, the curation of the display comprising execution of compiled instructions that automatically manipulate read and write access to the electronic information of the item) are not an improvement to a computer or a technology, the claims do not apply the judicial exception with a particular machine, the claims do not effect a transformation or reduction of a particular article to a different state or thing nor do the claims apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment such that the claims as a whole is more than a drafting effort designed to monopolize the exception (see MPEP §§ 2106.05(a-c, e)). The use of a device, network, and network resource are merely employed to link the use of the judicial exception to a technological environment.
Dependent claims 2-10, 12-15, and 17-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitations recite mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea ‐ see MPEP 2106.05(f).
Regarding Step 2B of the 2019 PEG, the additional elements have been considered above in Step 2A Prong 2. The claim limitations do not amount to significantly more than the judicial exception because they are directed to limitations referenced in MPEP 2106.05I.A. that are not enough to qualify as significantly more when recited in a claim with an abstract idea because the limitations recite mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea ‐ see MPEP
2106.05(f).
Applicant's claims mimic conventional, routine, and generic computing by their similarity to other concepts already deemed routine, generic, and conventional [Berkheimer Memorandum, Page 4, item 2] by the following [MPEP § 2106.05(d) Part (II)]. The claims recite steps like: “Receiving or transmitting data over a network, e.g., using the Internet to gather data,” Symantec, “Performing repetitive calculations,” Flook, and “storing and retrieving information in memory,” Versata Dev. Group, Inc. v. SAP Am., Inc. (citations omitted), by performing steps of “identifying” item information, “analyzing” the item information, “determining” CERT information, “determining” material information, “determining” an item status, and “dynamically curating” display of the item (Example Claim 1).
By the above, the claimed computing “call[s] for performance of the claimed information collection, analysis, and display functions ‘on a set of generic computer components' and display devices” [Elec. Power Group, 830 F.3d at 1355] operating in a “normal, expected manner” [DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d at 1245, 1258 (Fed. Cir. 2014)].
Conclusively, Applicant's invention is patent-ineligible. When viewed both individually and as a whole, Claims 1-20 are directed toward an abstract idea without integration into a practical application and lacking an inventive concept.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 USC 103 as being unpatentable over the teachings of
Tabaddor et al., US 20210334699 A1, cite no. 1 from IDS filed 3/19/2025, hereinafter Tabaddor, in view of
Zhu et al., US 20230089850 A1, cite no. 3 from IDS filed 3/19/2025, hereinafter Zhu. As per,
Claims 1, 11, 16
Tabaddor teaches
A method comprising: /
A device comprising: a processor configured to: /
A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions that when executed by a device, perform a method comprising: (Tabaddor [0036])
identifying, by a device, electronic information related to an item, the information comprising certification (CERT) data and material data related to the item; (Tabaddor [0021] “the data source(s) 106 may compile, store, or otherwise access information associated with product tests, standards, certifications, requirements, and/or the like;” [0023] “the training dataset 116 may indicate characteristics, dimensions, materials, compositions, and/or qualities of the tested products” note the collection of certification data and material data related to a product)
analyzing, via the device executing an artificial intelligence (AI) model, the electronic information; (Tabaddor [0040] “the product test predictor application 160 may analyze or process the data 151 using the machine learning model to generate a set of output values” note the use of the ML model to analyze the product data)
determining, by the device, based on the AI analysis of the CERT data, CERT information for the item, CERT information indicating a status of at least one certification related to a manufacture of the item; (Tabaddor [0015] “he systems and methods may use a machine learning model to predict whether a sample of a product would “pass” a given product test (or otherwise be certified according to the product test).” Note the ML analysis to determine a certification status; [0016] “the term “product test” may refer to any standard, certification, test, or the like that is created or specified by an entity, agency, governing body, or the like, where each product test may be applicable to a certain type, kind, size, or portion of physical product that may be used in various applications (e.g., construction, consumer goods, manufacturing, maintenance, etc.).” note the certification related to a manufacture of the product)
determining, by the device, based on the AI analysis of the material data, material information for the item, the material information indicating a status of a type of at least one material constituting the item; (Tabaddor [0023] “For example, the portion of the training dataset 116 for NFPA 262 may include dimensions and compositions of the tested product specimens;” Note the compositions of the product; [0026] “The set of input data may include at least a portion of the parameters or characteristics that are included in the training dataset 116 (e.g., product characteristics, dimensions, materials, compositions, and/or qualities, and any output(s) of the product test on a given product)” note the input data containing the product materials and compositions; [0027] “After receipt of the set of input data, the server computer 115 may input the set of input data into the applicable machine learning model, and generate a set of outputs that may predict an output of a given product tested according to the product test used to certify the given product” note the outputs of the ML model corresponding to the status of a type of at least one material)
determining, by the device, an item status for the item based on AI analysis of the CERT information and the material information; and (Tabaddor [0027] “For example, a set of outputs generated using a machine learning model associated with NFPA 262 may include, for a small-scale plenum cable used to generate the set of inputs, the maximum peak optical density, the average optical density, and the maximum flame spread distance for the small-scale plenum cable. Thus, the server computer 115 (or another component) may examine the set of outputs to predict whether the product used to generate the set of inputs would pass the applicable product test;” [0028] “For example, the server computer 115 may compare the maximum peak optical density, the average optical density, and the maximum flame spread distance for the small-scale plenum cable as output by the machine learning model may be compared to the maximum peak optical density of 0.5 or less, the average optical density of 0.15 or less, and the maximum flame spread distance of 1.52 m (5 ft) or less, as specified by NFPA 262” note the determination of the product status based on the ML model analysis of the certification information (NFPA 262 in this example) and material information)
[…].
Tabaddor does not explicitly teach, Zhu however in the analogous art of product analyses teaches
dynamically curating, by the device over a network, display of the item on a network resource based on the item status, the curation of the display comprising execution of compiled instructions that automatically manipulate read and write access to the electronic information of the item. (Zhu fig. 4; [0018] and [0035] noting the compilation of instructions; [0065] “FIG. 4 illustrates an online shopping GUI based on a real-time environmental impact scoring system. As shown, an online marketplace 400 (e.g., online store) may be displayed on an online shopper's computing device display (e.g., smartphone) as a listing of products and their calculated environmental impact score.” Note the dynamic display of items based on their status)
Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to modify Tabaddor’s AI-based item testing to include dynamically displaying an item’s status based on the analysis in view of Zhu in an effort to provide consumers with unbiased product assessments (see Zhu ¶ [0010] & MPEP 2143G).
Claims 2, 12, 17
Tabaddor does not explicitly teach, Zhu however in the analogous art of product analyses teaches
determining, based on the material data, a type of the materials of the item, the type of the materials corresponding to at least one of a preferred material (PM) and exclusionary material (EM), wherein the material information determination is based on the type of materials of the item. (Zhu [0059] “For example, sustainably farmed products may be highly ranked as positive environmental impact components, while petroleum-based products may be ranked low” note the positive components corresponding to preferred material and negative/low components corresponding to exclusionary material)
The rationale/motivation to combine Tabaddor with Zhu persists.
Claims 3, 13, 18
Tabaddor does not explicitly teach, Zhu however in the analogous art of product analyses teaches
determining a hierarchical score for the item, the hierarchical score being based on a determined base score for a type of PM material, wherein the hierarchical score increases based on the type of PM material as it relates to at least one of sustainability, ethical manufacturing and responsible consumption. (Zhu fig. 3 noting the product scoring, ranking, and display of ranked products; [0027] a product score, a packaging score and a shipping method score (FIG. 3) are individually generated to produce scores for each of these components. Subsequently, these individual scores are aggregated (e.g., averaged, added, mean, etc.) to create an overall product score;” [0059] “A correlation to positive environmental impact components may positively affect a score … sustainably farmed products may be highly ranked as positive environmental impact components, while petroleum-based products may be ranked low”)
The rationale/motivation to combine Tabaddor with Zhu persists.
Claims 4, 14, 19
Tabaddor does not explicitly teach, Zhu however in the analogous art of product analyses teaches
wherein the hierarchical score is further based on a type of the EM material. (Zhu [0059] “a correlation to negative environmental impact components may negatively affect a score … petroleum-based products may be ranked low;” [0060] “plastic packaging may be ranked low”)
The rationale/motivation to combine Tabaddor with Zhu persists.
Claims 5, 15, 20
Tabaddor does not explicitly teach, Zhu however in the analogous art of product analyses teaches
compiling the electronic instructions based on the item status, the electronic instructions comprising controls for how the display of the item is curated, the controls comprising modifications to the display of the item that impact how the electronic information is presented on the network resource. (Zhu fig. 4; [0065] “FIG. 4 illustrates an online shopping GUI based on a real-time environmental impact scoring system. As shown, an online marketplace 400 (e.g., online store) may be displayed on an online shopper's computing device display (e.g., smartphone) as a listing of products and their calculated environmental impact score. For example as shown, product 402 has an E-impact score (environmental impact score) of 87. This score may indicate a high or low environmental impact depending on a selected scoring system designation.” Note the select scoring system determination how the product is displayed (high or low impact); [0066] “this score may also be revealed to the consumer by its score components 408, such as a product score 410 of 91, a packaging score 112 of 84 and a shipping score 412 of 84. Additional products 404 and 406 may also be displayed with their calculated E-impact scores” note the control of the score components)
The rationale/motivation to combine Tabaddor with Zhu persists.
Claim 6
Tabaddor teaches
wherein the CERT data comprises information related to certifications, standards, accreditation, conformity assurance and validations of the item, […] (Tabaddor [0016] “the term “product test” may refer to any standard, certification, test, or the like that is created or specified by an entity, agency, governing body, or the like, where each product test may be applicable to a certain type, kind, size, or portion of physical product that may be used in various applications (e.g., construction, consumer goods, manufacturing, maintenance, etc.).”)
Tabaddor does not explicitly teach, Zhu however in the analogous art of product analyses teaches
[…] wherein the CERT data further comprises social attributes, environmental attributes, governance attributes, origin attributes and quality attributes (SEQ attributes) of the item, wherein the CERT information is based at least on the SEQ data, wherein the SEQ data is identified via analysis of the CERT data via the AI model. (Zhu [0015] “the technology disclosed herein computes real-time scoring on a number of metrics (e.g., product environmental impact, packaging environmental impact, shipping environmental impact, manufacturer reputation, carbon footprint calculation, etc.). These metrics may be derived from a number of data sources, such as SKU-level product detail discovery, social media on recent events reflecting a manufacturer's reputation, verification information based on industry organization recognition or government certification (e.g., fair trade, USDA, blockchain data on supply chain, etc.), environmental impact score databases capturing previous assessments for existing or known products, etc.”)
The rationale/motivation to combine Tabaddor with Zhu persists.
Claim 7
Tabaddor teaches
wherein the CERT information, material information and item status comprise scoring values. (Tabaddor [0044] “The set of raw data 205 may further identify a set of results or outputs of an applicable large-scale product test and a small-scale product test. In particular, the set of outputs may be numeric and/or Boolean values or outputs indicating how a product performed”)
Claim 8
Tabaddor teaches
wherein the electronic information further comprises item data related to at least one of characteristics of the item, item type, item size, item shape, item materials, item provider and item location. (Tabaddor [0044] “ the set of raw data 205 may identify products, characteristics of the products (e.g., physical dimensions), composition of the products (i.e., physical materials that make up the products), design of the products (i.e., information indicating how the products are structured), and/or similar information”)
Claim 9
Tabaddor does not explicitly teach, Zhu however in the analogous art of product analyses teaches
wherein the network resource is a webpage associated with a third party provider. (Zhu [0014] “locate and analyze customer review data on environmental impact from merchant sites, consumer sites or third party review sites;” [0016] “the technology disclosed herein provides consumers with several decision aid metrics, such as a consumer product environmental impact assessment” note the webpage associated with a third party provider)
The rationale/motivation to combine Tabaddor with Zhu persists.
Claim 10
Tabaddor teaches
wherein the item is a real-world or digital item provided by a third party entity. (Tabaddor [0045] note the example of the cable corresponding to a real-world item)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 20220245574 A1; US 11544275 B2; WO 2022087497 A1; Sutter, Generic compliance check tool in examining the conformity of company-specific standards to public standards, 2010.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMED EL-BATHY whose telephone number is (571)270-5847. The examiner can normally be reached on M-F 8AM-4:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, PATRICIA MUNSON can be reached on (571) 270-5396. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMED N EL-BATHY/Primary Examiner, Art Unit 3624