DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on December 17, 2025 has been entered.
Status of the Application
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The amendment filed on December 17, 2025 has been entered. The following has occurred: Claims 1, 10, and 18 have been amended.
Claims 1, 2, 7, 8, 10, 15, 17, 18, and 20-31 are pending.
Response to Amendment
35 U.S.C. 101 rejection has been maintained in light of the amendment.
Priority
The present application claims priority to Provisional Application No. 63/292,113, filed Dec. 21, 2021.
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, 2, 7, 8, 10, 15, 17, 18, and 20-31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Is the claim to a process, machine, manufacture or composition of matter? (MPEP 2106.03)
In the present application, claims 1, 2, 7, 8, and 22-25 are directed to a method (i.e., a process), claims 10, 15, 17, and 26-29 are directed to a system (i.e., a machine), and claims 18, 20, 21, 30, and 31 are directed to a computer product (i.e., an article of manufacture). Thus, the eligibility analysis proceeds to Step 2A. prong one.
Step 2A. prong one: Does the claim recite an abstract idea, law of nature, or natural phenomenon? (MPEP 2106.04)
While claims 1, 10, and 18, are directed to different categories, the language and scope are substantially the same and have been addressed together below.
The abstract idea recited in claims 1, 10, and 18, is
transforming textual provisions and guidelines of land development codes and regulations, by translating a sematic structure of each code and regulation into object rules or parametric models using a formal language, classifying and encoding object data specified in the land development codes and regulations, and classifying and encoding subjective data specified in the object rules;
acquiring from a land development design document in a building information model (BIM) digital format, a plurality of objects and a plurality of attributes describing the plurality of objects, wherein the plurality of attributes include at least a spatial relationship of a land development design and one or more details on zoning, landscaping, drainage, sanitation, and wetland controls with respect to the land development design; and
performing real time code checking and/or compliance of individual building elements of the land development design document in the BIM digital format as the land development design document is being developed by:
initiating a plurality of actions of code conformance checking of the land development design document;
upon receiving a selection, performing design model validation, wherein the design model validation comprises approving a format of the land development design document;
performing, via one or more design checking modules and an artificial neural network, code conformance checking of the land development design document using the computable digital representation of the land development codes and regulations, wherein code conformance checking comprises checking land use details of the land development design document for conformance with at least zoning codes and regulations, landscaping codes and regulations, drainage codes and regulations, sanitation codes and regulations, and wetland control codes and regulations, as defined by the computable digital representation of the land development codes and regulations;
upon receiving a selection, compliance reporting based on input provided from the design checking modules, wherein the compliance reporting includes a prediction confidence data for the code conformance checking performing by the one or more design checking modules;
receiving inaccurate prediction of code conformance data; and
retraining, the one or more design checking modules and the artificial neural network using the inaccurate prediction of code conformance data to improve prediction accuracy.
The claims are directed to an abstract idea of determining and checking land development code.
The bolded portions of limitations above recite concepts performable in the human mind including observation, evaluation, and judgement, which falls under “Mental Processes,” one of the abstract idea categories. Under the broadest reasonable interpretation, other than the additional elements of computer components, the claims 1, 10, and 18 recite processes that are all acts that could be performed by a human, e.g., mentally or manually, using a pen and paper, without the use of a computer or any other machine. For example, a person can translate development codes and regulations into rules and guidance to perform design model validation (i.e., evaluation) for land development permit application file information against relevant codes, ordinances, and regulations, using taxonomy; perform exchange model code checking (i.e., evaluation); perform code, ordinance, and regulation conformance checking (i.e., evaluation) to requirements; and perform compliance reporting based on input provided from the design checking procedures. As described in the application specification paragraph [0002], government office (i.e., human) has been known to manually review applications and compare with regulations. The reviewing application process and rejecting/approving application from zoning regulations for government officials have existed before computers were available to support these tasks. The instant receives compliance information in the form of business information model, the system processing the received file information related to land development permits, analyzes the conformance of those applications to stored provisions, and presenting the result of the conformance/compliance analysis to the user. Because the limitations above closely follow the steps of collecting information and analyzing the collected information, and the steps involved human judgements, observations, and evaluations that can be practically or reasonably performed in the human mind, the claims recite an abstract idea consistent with the “mental processes” grouping of the abstract ideas, set forth in MPEP 2106.04(a)(2)(III).
Additionally, the claim recites a fundamental economic practice long prevalent in our system of commerce in the form of managing personal behavior or relationship or interaction between people for following rules or instructions. Under the broadest reasonable interpretation, other than the additional elements of computer components, the steps of performing design model validation from land development permit application file information with/against relevant codes and regulation, which are set of rules and instructions; performing exchange model code checking using a plurality of exchanges models which are set of rules and instructions; perform conformance checking, wherein the conformance checking comprises receiving a request from the exchange models and passing the land development permit application file information to design checking modules configured to check land development code, ordinance, and regulatory provisions and any regulations per local, state, national or international requirements; and perform compliance reporting based on input provided from the design checking modules, which design checking modules are a set of rules and instructions. The limitations, substantially comprising the body of the claim, recite standard processes found in standard practice within most industries to apply compliance standard in a plurality of processes to monitor compliance to a variety set rules and procedures and this has been done long before the invention of computers. If a claim limitation, under its broadest reasonable interpretation, covers following rules or instruction for an objective, then it falls within the “Certain Methods of Organizing Human Activity” category of the abstract ideas.
Additionally, under the broadest reasonable interpretation in view of the specification, the limitations using design checking modules and artificial neural network for performing conformance check and retraining in steps [F], [G], and [I] amounts to forms of performing mathematical calculations, which falls under “mathematical concepts” grouping of the abstract ideas, set forth in MPEP 2106.04(a)(2)(I).
Accordingly, the claims 1, 10, and 18 recite an abstract idea and the analysis proceeds to Step 2A. prong two.
Step 2A. prong two: Does the claim recite additional elements that integrate the judicial exception into a practical application? (MPEP 2106.04)
This judicial exception is not integrated into a practical application because the additional elements merely add instructions to apply the abstract idea to a computer.
The additional elements considered include:
Claim 1: “by at least one hardware processor, textual provisions and guidelines of land development codes and regulations into a computable digital representation of the land development codes and regulations, … using feature extraction in the object rules or parametric models and … using fuzzy logic and natural language processing in the object rules or parametric models;” “by the at least one hardware processor,” “graphically displaying, by at least one hardware processor, graphical user interface of a site design model platform, wherein the graphical user interface is embedded with a plurality of graphic buttons for initiating a plurality of actions of code conformance checking;” “upon receiving a selection of a first one of the plurality of graphic buttons embedded in the graphical user interface of the site design model platform, performing, using the at least one hardware processor,” and “upon receiving a selection of a second one of the plurality of graphic buttons embedded in the graphical user interface of the site design model platform,”
Claim 10: “at least one hardware processor; and one or more software modules that are configured to, when executed by the at least one hardware processor:” “computable digital representation of the land development codes and regulations, wherein a semantic structure of each code and regulation is translated into object rules or parametric models using a formal language, wherein objective data specified in the land development codes and regulations is encoded using feature extraction in the object rules or parametric models and subjective data specified in the object rules is encoded using fuzzy logic and neural Natural Language Processing (NLP) in the object rules or parametric models,” “graphically display a graphical user interface of a site design model platform, wherein the graphical user interface is embedded with a plurality of graphic buttons for initiating a plurality of actions of code conformance checking;” “upon receiving a selection of a first one of the plurality of graphic buttons,” “via with an artificial neural network,” and “upon receiving a selection of a second one of the plurality of graphic buttons embedded in the graphical user interface of the site design model platform,”
Claim 18: “a non-transitory computer-readable medium having instructions stored therein, wherein the instructions, when executed by a processor, cause the processor to:” “computable digital representation of the land development codes and regulations, wherein a semantic structure of each code and regulation is translated into object rules or parametric models using a formal language, wherein objective data specified in the land development codes and regulations is encoded using feature extraction in the object rules or parametric models and subjective data specified in the object rules is encoded using fuzzy logic and neural Natural Language Processing (NLP) in the object rules or parametric models,” “graphically display a graphical user interface of a site design model platform, wherein the graphical user interface is embedded with a plurality of graphic buttons for initiating a plurality of actions of code conformance checking;” “upon receiving a selection of a first one of the plurality of graphic buttons,” and “upon receiving a selection of a second one of the plurality of graphic buttons embedded in the graphical user interface of the site design model platform,”
The above-mentioned additional elements of a system comprising generic computer elements are found to recite mere instructions to apply a generic computer and technology to execute the method in the recited claim limitations, as merely using a computer to transmit, manipulate, and display information is not an improvement to a technology or technical field. The additional elements merely recite computer elements to transform, receive, check, display and retrain information.
The computer in the steps is recited at a high-level of generality (i.e., as generic computer components performing a generic computer function; See Applicant’s Specification at least at para. [0026]-[0029] and [0043]-[0045], regarding generic hardware processor executing software modules and functions; para. [0060] and [0080] regarding the generic use of neural Natural Language Processing (NLP) techniques, deep neural network-style machine learning/Artificial Intelligence; and para. [0024] describing generic graphical user interface) such that it amounts to no more than mere instructions to apply the exception using a generic computer component.
That is, the functions of limitations [A]-[I] are steps of adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea as discussed in MPEP 2106.05(f).
Accordingly, even in combination, these additional element(s) do not integrate the abstract idea into a practical application because they do not improve a computer or other technology, do not transform a particular article, do not recite more than a general link to a computer, and do not invoke the computer in any meaningful way; the general computer is effectively part of the preamble instruction to “apply” the exception by the computer. Therefore, the claims are directed to an abstract idea and the analysis proceeds to Step 2B.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? (MPEP 2106.05)
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the bold portions of the limitations recited above, were all considered to be an abstract idea in Step2A-Prong Two. The additional elements and analysis of Step2A-Prong two is carried over. For the same reason, these elements are not sufficient to provide an inventive concept. Applicant has merely recited elements that instruct the user to apply the abstract idea to a computer or other machinery. When considered individually and in combination the conclusion, as discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer to perform the above-mentioned limitations [A]-[I] amount to no more than mere instructions to apply the function of the limitations to the exception using generic computer component, as discussed in MPEP 2106.05(f). The claim as a whole merely describes how to generally “apply” the concept for checking land development code. For these reasons there is no inventive concept in the claims and thus are ineligible.
As for dependent claim 2, the claim further defines the abstract idea of the independent claim. The claim further provides additional information regarding the design checking modules. The claim further recites additional abstract step, at a high level of generality, (i.e., as a generic computer system performing generic computer functions of checking information) such that it amounts no more than mere instructions to apply the exception using a generic computer component, as discussed in MPEP 2106.05(f). Even in combination, the additional element does not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. The claim is ineligible.
As for dependent claims 7, 15, and 21, these claims further define the abstract idea of the independent claim. The claims further recite additional abstract information regarding the land development code, ordinance, and regulation using a Transformation Logic Algorithm (TLA), neural Natural Language Processing (NLP) techniques, or artificial intelligence, which do not change the abstract idea of the independent claim. Examiner notes that the use of Transformation Logic Algorithm (TLA), neural Natural Language Processing (NLP) techniques, or artificial intelligence, under the broadest reasonable interpretation the system requires specific mathematical calculations (transformation Logic Algorithm is based partially on first-order logic calculus (see at least Specification [0058]) and therefore encompasses mathematical concepts. “For example, in a claim that includes a series of steps that recite mental steps as well as a mathematical calculation, an examiner should identify the claim as reciting both a mental process and a mathematical concept for Step 2A, Prong One to make the analysis clear on the record.” MPEP 2106.04, subsection II.B. Under such circumstances, however, the Supreme Court has treated such claims in the same manner as claims reciting a single judicial exception. Id. (discussing Bilski v. Kappos, 561 U.S. 593 (2010)). Here, the claimed invention falls within the mental process/certain method of organizing human activity grouping of abstract ideas, and the step falls within the mathematical concepts grouping of abstract ideas. The limitations are considered together as a single abstract idea for further analysis. (Step 2A, Prong One: YES). The additional element of using a Transformation Logic Algorithm (TLA), neural Natural Language Processing (NLP) techniques, or artificial intelligence, is recited at a high level of generality (in view of the application specification para. [0056], [0066], and [0081] that the various neural NLP techniques and/or deep neural network-style machine learning/Artificial Intelligence are used/applied for predictive result function of “automatically check land development code conformance and other regulations”], as a generic function performed by generic computer system) such that it amounts no more than mere instructions to apply the exception using a generic computer component, as discussed in MPEP 2106.05(f). Even in combination, the additional element does not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. The claims are ineligible.
As for dependent claims 8, 17, and 20, these claims further define the abstract idea of the independent claim. The claims further recite additional abstract information regarding the compliance reporting, which do not change the abstract idea of the independent claim. The claim does not integrate the abstract idea into a practical application and is not significantly more. The claims are ineligible.
As for dependent claims 22, 23, 26, 27, and 30, these claims further provide additional descriptive information regarding the land development design document, which does not change the abstract idea of the independent claims. No new additional element was added. The claims are ineligible.
As for dependent claims 24, 25, 28, 29, and 31, these claims further include additional abstract steps of verifying land development design by acquiring imaging data using unmanned aerial vehicle. The additional element of unmanned aerial vehicle with LIDAR images is recited at a high level of generality (described in specification para. [0088]) such that it amounts no more than mere instructions to apply the exception using a generic computer component or other machinery, as discussed in MPEP 2106.05(f). Even in combination, the additional element does not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. The claim is ineligible.
In summary, the dependent claims considered both individually and as ordered combination do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. The claims do not recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment. Therefore, claims are rejected under 35 U.S.C. 101.
Allowable Subject Matter over Prior Art
Examiner has withdrawn the previous rejection under 35 U.S.C. 103 of Claims 1, 2, 7, 8, 10, 15, 17, 18, and 20-31.
The closest prior art found are:
Nawari (“A Generalized Adaptive Framework for Automating Design Review Process: Technical Principles” provided in the IDS filed on May 2, 2023) is directed to a system and method for evaluating a design against its requirements to verify the performance of the design and identify issues before construction takes place. Nawari teaches transforming, by at least one hardware processor, textual provisions and guidelines of land development codes and regulations into a computable digital representation of the land development codes and regulations, wherein a semantic structure of each code and regulation is translated into object rules or parametric models using a formal language, wherein objective data specified in the land development codes and regulations is encoded using feature extraction in the object rules or parametric models and subjective data specified in the object rules is encoded using fuzzy logic and natural language processing in the object rules or parametric models; (Sections 6 and 9); acquiring, by the at least one hardware processor, from a land development design document in a building information model (BIM) digital format, a plurality of objects and a plurality of attributes describing the plurality of objects, wherein the plurality of attributes include at least a spatial relationship of a land development design and one or more details on zoning, landscaping, drainage, sanitation, and wetland controls with respect to the land development design (pages 16-17 and Section 9);
performing, using the at least one hardware processor, design model validation, wherein the design model validation comprises approving a format of the land development design document (Section 2: “An example of this platform would be Solibri Model Checker (SMC), which has its rule engine that can work on multiple models;” and page 6);
performing, via one or more design checking modules and an artificial neural network, code conformance checking of the land development design document using the computable digital representation of the land development codes and regulations, wherein code conformance checking comprises checking land use details of the land development design document for conformance with at least zoning codes and regulations, landscaping codes and regulations, drainage codes and regulations, sanitation codes and regulations, and wetland control codes and regulations, as defined by the computable digital representation of the land development codes and regulations (page 2, Fig. 1 and Section 5, in particular steps (A) to (E)).
However, Nawari does not expressly teach a graphical user interface buttons to initiate actions which includes performing compliance reporting based on input provided from the design checking modules, wherein the compliance reporting includes a prediction confidence data for the code conformance checking performing by the one or more design checking modules; receiving, by the at least one hardware processor, feedback on an accuracy of the prediction confidence data provided in the compliance reporting; and retraining, the one or more design checking modules and the artificial neural network using the feedback on the accuracy of the prediction confidence data.
Roth et al. (US 20080059220 A1, hereinafter “Roth”) is directed to a system for performing a computerized building code compliance check with an appropriate jurisdiction which teaches graphically displaying, by at least one hardware processor (para. [0025] and [0050]), a graphical user interface of a site design model platform, wherein the graphical user interface is embedded with a plurality of graphic buttons for initiating a plurality of actions of code conformance checking; upon receiving a selection of a first one of the plurality of graphic buttons, upon receiving a selection of a second one of the plurality of graphic buttons embedded in the graphical user interface of the site design model platform.
However, Roth does not expressly teach the interface buttons to initiate actions which includes performing compliance reporting based on input provided from the design checking modules, wherein the compliance reporting includes a prediction confidence data for the code conformance checking performing by the one or more design checking modules; receiving, by the at least one hardware processor, feedback on an accuracy of the prediction confidence data provided in the compliance reporting; and retraining, the one or more design checking modules and the artificial neural network using the feedback on the accuracy of the prediction confidence data.
Gupat (US 20190347751 A1) is directed to a system and method for automated approval of building proposal, which teaches wherein the compliance reporting comprises superimposing a CAD drawing or BIM model or PDF file of a proposed development of a piece of property on a GIS map of a geographic area having applicable zoning conditions illustrated.
However, Gupat does not expressly teach the interface buttons to initiate actions which includes performing compliance reporting based on input provided from the design checking modules, wherein the compliance reporting includes a prediction confidence data for the code conformance checking performing by the one or more design checking modules; receiving, by the at least one hardware processor, feedback on an accuracy of the prediction confidence data provided in the compliance reporting; and retraining, the one or more design checking modules and the artificial neural network using the feedback on the accuracy of the prediction confidence data.
In sum, the combination of the above references does not explicitly teach the specific configuration of the limitations upon receiving a selection of a second one of the plurality of graphic buttons embedded in the graphical user interface of the site design model platform, performing, using at least one hardware processor, compliance reporting based on input provided from the design checking modules, wherein the compliance reporting includes a prediction confidence data for the code conformance checking performed by the one or more design checking modules; receiving, by the at least one hardware processor, inaccurate prediction of code conformance data; and retraining, the one or more design checking modules and the artificial neural network using the inaccurate prediction of code conformance data to improve prediction accuracy (i.e. in the particular manner it is claimed in the context of the whole claim is not disclosed, taught or suggested in the prior art(s)).
Examiner notes that the underlined limitations above, in combination with the other limitations found within the independent claims are found to be allowable over the prior art of record.
The prior art of record neither anticipates nor fairly and reasonably teach the independent claims 1, 10, and 18.
Examiner notes that while applicant has overcome the art of record, the application is not in condition for allowance, given the outstanding rejection under 35 U.S.C. 101.
Response to Remarks
35 U.S.C. 101 Rejections:
The Applicant’s remarks are fully considered, however, are found to be unpersuasive.
On pages 14-16, the Applicant asserts the incompatibility of land development codes with open data standards in automated determination of land development code performance is a problem rooted in and arising in the computer technology then recites the entire claim as a whole solves the problem rooted in and arising in computer technology, and provides an improvement to computer functionality.
The Examiner respectfully disagrees. The claims are directed to the abstract idea of collecting data (land development code and design specifications), comparing the data with set of rules, and reporting the results. This is a fundamental mental process and long-standing commercial practice for organizing human activities, analogous to an architect or building planner manually reviewing blueprint against a city’s zoning regulations. The computer function and automating process on a generic computer does not confer patent eligibility.
Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer").
In evaluating whether a claim that requires a computer recites a mental process, examiners should carefully consider the broadest reasonable interpretation of the claim in light of the specification. For instance, examiners should review the specification to determine if the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept. In these situations, the claim is considered to recite a mental process.
An example of a case identifying a mental process performed on a generic computer as an abstract idea is Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 1385, 126 USPQ2d 1498, 1504 (Fed. Cir. 2018). In this case, the Federal Circuit relied upon the specification in explaining that the claimed steps of voting, verifying the vote, and submitting the vote for tabulation are "human cognitive actions" that humans have performed for hundreds of years. The claims therefore recited an abstract idea, despite the fact that the claimed voting steps were performed on a computer. 887 F.3d at 1385, 126 USPQ2d at 1504. Another example is FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 120 USPQ2d 1293 (Fed. Cir. 2016). The patentee in FairWarning claimed a system and method of detecting fraud and/or misuse in a computer environment, in which information regarding accesses of a patient’s personal health information was analyzed according to one of several rules (i.e., related to accesses in excess of a specific volume, accesses during a pre-determined time interval, or accesses by a specific user) to determine if the activity indicates improper access. 839 F.3d. at 1092, 120 USPQ2d at 1294. The court determined that these claims were directed to a mental process of detecting misuse, and that the claimed rules here were "the same questions (though perhaps phrased with different words) that humans in analogous situations detecting fraud have asked for decades, if not centuries." 839 F.3d. at 1094-95, 120 USPQ2d at 1296.
An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699. The patentee in Mortgage Grader claimed a computer-implemented system for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The interface prompts a borrower to enter personal information, which the grading module uses to calculate the borrower’s credit grading, and allows the borrower to identify and compare loan packages in the database using the credit grading. 811 F.3d. at 1318, 117 USPQ2d at 1695. The Federal Circuit determined that these claims were directed to the concept of "anonymous loan shopping", which was a concept that could be "performed by humans without a computer." 811 F.3d. at 1324, 117 USPQ2d at 1699. Another example is Berkheimer v. HP, Inc., 881 F.3d 1360, 125 USPQ2d 1649 (Fed. Cir. 2018), in which the patentee claimed methods for parsing and evaluating data using a computer processing system. The Federal Circuit determined that these claims were directed to mental processes of parsing and comparing data, because the steps were recited at a high level of generality and merely used computers as a tool to perform the processes. 881 F.3d at 1366, 125 USPQ2d at 1652-53.
Both product claims (e.g., computer system, computer-readable medium, etc.) and process claims may recite mental processes. For example, in Mortgage Grader, the patentee claimed a computer-implemented system and a method for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The Federal Circuit determined that both the computer-implemented system and method claims were directed to "anonymous loan shopping", which was an abstract idea because it could be "performed by humans without a computer." 811 F.3d. at 1318, 1324-25, 117 USPQ2d at 1695, 1699-1700. See also FairWarning IP, 839 F.3d at 1092, 120 USPQ2d at 1294 (identifying both system and process claims for detecting improper access of a patient's protected health information in a health-care system computer environment as directed to abstract idea of detecting fraud); Content Extraction & Transmission LLC v. Wells Fargo Bank, N.A., 776 F.3d 1343, 1345, 113 USPQ2d 1354, 1356 (Fed. Cir. 2014) (system and method claims of inputting information from a hard copy document into a computer program). Accordingly, the phrase "mental processes" should be understood as referring to the type of abstract idea, and not to the statutory category of the claim.
Examples of product claims reciting mental processes include: An application program interface for extracting and processing information from a diversity of types of hard copy documents – Content Extraction, 776 F.3d at 1345, 113 USPQ2d at 1356; and A computer readable medium containing program instructions for detecting fraud – CyberSource, 654 F.3d at 1368 n. 1, 99 USPQ2d at 1692 n.1.
Further, the Examiner fails to see the technological improvement. As reflected in Enfish and Mentone Solutions, there is a fundamental difference between computer functionality improvements (improvement of the technology or technical field), on the one hand, and uses of existing computers as tools to perform a particular task (collecting, processing, analyzing, and displaying information), on the other. The alleged advantages that the applicant touts do not concern an improvement to computer capabilities or any machinery but instead relate to an alleged improvement in collecting and processing/checking information using models for a desirable result, which a computer is used as a mere tool in its ordinary capacity, see MPEP 2106.05(f). To further clarify, the applicant reflected a business need/reason of the abstract idea for the collecting and processing/checking land development codes, ordinances, and regulations information for land development need in the field of managing compliance requirement for business entity. The computer, itself is merely used “applied” for the expected result of convenience (e.g., more efficient, faster, and etc.) and time/cost saving, however, the claims do not reflect an improvement to the technology of the computer functionalities other than, by using the additional elements of the computer system, desired result can be produced without doubt to how it is done. That is, the computer system itself or specific technology is not improved in anyway other than being applied as a tool/instrument for the judicial exception (abstract idea). The claims do not recite or provide details to how the technology (e.g., NLP, fuzzy logic, real-time BIM integration, and self-training ANN) is improved or provide technological detail of the specifics of how it is accomplished, but rather with mere statement of applying additional elements of computer components function and result can be accomplished. A hypothetical example the Examiner can provide is “extracting, by processor, content from documents” which is an applied step of additional element of computer processor can accomplish the intend result of extracting information without the need of further detail, that is deemed to be not an improvement, however, if the claim recites, “extracting, by processor, content from documents by reducing noise with isolation of white and gray pixel”, which the claim limitation is directed to improvement and specific details to the technological application. The Examiner suggests providing additional technological details to the how improvement of the technology (e.g., fuzzy logic, NLP, BIM integration, retraining of ANN, etc.) is accomplished in the claims rather than just what it is used for.
At Alice step one, we determine whether the claims are directed to an abstract idea. Alice, 573 U.S. at 217. In cases involving software, step one often “turns on whether the claims focus on specific asserted improvements in computer capabilities or instead on a process or system that qualifies [as] an abstract idea for which computers are invoked merely as a tool.” Uniloc USA, Inc. v. LG Elecs. USA, Inc., 957 F.3d 1303, 1306–07 (Fed. Cir. 2020) (citing Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1364 (Fed. Cir. 2020)). “We have routinely held software claims patent eligible under Alice step one when they are directed to improvements to the functionality of a computer or network platform itself.” Id. at 1307 (collecting cases).
This case is nothing like the claims we held ineligible in Two-Way Media Ltd. v. Comcast Cable Communications, LLC, 874 F.3d 1329 (Fed. Cir. 2017). There, the claims recited a method of transmitting packets of information over a communications network comprising: converting information into streams of digital packets; routing the streams to users; controlling the routing; and monitoring the reception of packets by the users. Id. at 1334. We held the claims ineligible because they merely recited a series of abstract steps (“converting,” “routing,” “controlling,” “monitoring,” and “accumulating records”) using “result-based functional language” without the means for achieving any purported technological improvement. Id. at 1337. Here, there is no functional claiming, nor are there abstract steps.
The Applicant’s comparison to DDR Holdings is unpersuasive because the claimed invention is not analogous. The invention in DDR Holdings was found patent-eligible because it is addressed a problem that was specifically rooted in internet technology of the problem of a host website losing visitor traffic when a user clicks on an advertisement for a third-party merchant. The claimed solution for generating a hybrid webpage that retained the host’s “look and feel” was a specific technological solution that altered the conventional behavior of internet hyperlink protocols. In contrast, the present invention does not solve a problem unique to computer technology. The problem of checking a design plan for compliance with regulations existed long before computers. The claimed invention merely uses a computer as a tool to perform this long-standing, real world activity more efficiently. The claimed invention does not alter the functionality of the BIM platform or the computer itself in the manner the DDR Holdings invention altered the functionality of the internet via hyperlink protocols.
The Applicant cites Appeal 2018-007443 to support the argument that the classifying and retraining steps are computationally complex and constitute an improvement to technology. The Examiner would like to note the decisions by PTAB for 2018-007443 is not precedential and Examiners are instructed to follow the guidance of the MPEP 2106, which is based on binding precedent from the Supreme Court and Federal Circuit. The single finding of non-precedential case for a particular “classifying” step to be computationally complex to establish general rule that all “classifying” steps are patent-eligible.
The PTAB decision 2017-010866 is also not precedential and Examiners are instructed to follow the guidance of the MPEP 2106, which is based on binding precedent from the Supreme Court and Federal Circuit. The remarks fail to address the similarity between the decision 2017-010866 with the claimed invention.
Furthermore, the Applicant asserts “retraining” step is similar to the language recited in Ex Parte Desjardins rehearing decision. The Examiner respectfully disagrees. Desjardins recites a specific and unconventional multi-steps training method that is further elaborated in the specification with technological detail. The instant claims do not. The retraining step is recited at a high-level of generality: “retraining… using the inaccurate prediction… to improve prediction accuracy. The claim and the specification describe the basic goal and function of any supervised learning algorithm to learn from the errors. The specification does not provide description for how. Therefore, it is an abstract instruction to learn from inaccurate or mistakes, which is a mental process implemented with the generic tool of an ANN.
Thus, the claims do not improve the functionality of the computer itself or provide a solution to a problem that is unique to the realm of computer technology. Accordingly, the claims fail to recite significantly more than a judicial exception, therefore, the rejection under 35 U.S.C. 101 is maintained.
Relevant Prior Art Not Relied Upon
The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure. The additional cited art, including but not limited to the excerpts below, further establishes the state of the art at the time of Applicant’s invention and shows the following was known:
Khan et al. “Geotechnical Property Modeling and Construction Safety Zoning Based on GIS and BIM Integration” Appl. Sci. April 28, 2021, 11(9), 4004; https://doi.org/10.3390/app11094004; teaches the integration of BIM and GIS for the subsurface geotechnical property modeling and classification into zones in according to OSHA regulation for safe construction.
Hajji et al. “Development of an Integrated BIM-3D GIS Approach for 3D Cadastre in Morocco” ISPRS Int. J. Geo-Inf. 2021, 10(5), 351; https://doi.org/10.3390/ijgi10050351; teaches 3D cadastre based on the integration of BIM and 3D GIS.
Nawari, “A Generalized Adaptive Framework for Automating Design Review Process: Technical Principles” 2019, In: Mutis, I., Hartmann, T. (eds) Advances in Informatics and Computing in Civil and Construction Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-00220-6_48.
Rodriguez (US 20200258174 A1) is directed to systems and methods for determining land use development potential are provided, including a graphical user interface for real-time analysis. The systems and methods further implement search functions and real-time feedback and recommendations for real-time adjustment of a proposed land use development plan to ensure compliance with environmental and regulatory information.
Marthouse et al. (US 20220107977 A1) is directed to method and system for inspecting a structure are disclosed. Data is obtained from a dimensional sensor such as a LIDAR, RGBD, or other sensor capable of collecting data in three dimensions to define a structure element or object, describing physical dimensions of a structure and its elements. A verbal description is obtained with an audio sensor. Machine learning (ML) engines identify the elements of the structure and its physical features. Audio data is parsed using NLP techniques to identify additional attributes such as the material composition of identified elements.
Conclusion
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/WENREN CHEN/Examiner, Art Unit 3626