CTNF 18/779,945 CTNF 90577 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. DETAILED ACTION Continued Examination Under 37 CFR 1.114 07-42-04 AIA 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 April 27, 2026 has been entered. Information Disclosure Statement 06-52 The information disclosure statement (IDS) submitted on April 27, 2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. 12-151 AIA 26-51 12-51 Status of Claims Claims 1, 11, 19 and 20 have been amended. Claims 1-20 are currently pending and have been examined. Claim Objections 07-29-01 AIA Claim 1 is objected to because of the following informalities: Claim 11 appears to amend to remove “residential” from the claims from the claim set dated January 28, 2026. Examiner believes the same amendment should be made to the other independent and dependent claims . Appropriate correction is required. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1: Claims 11-18 are drawn to methods while claim(s) 1-10, 19 and 20 is/are drawn to an apparatus. As such, claims 1-20 are drawn to one of the statutory categories of invention (Step 1: YES). Step 2A - Prong One: Claim 11 (representative of independent claim(s) 1 and 19) recites the following steps: A method for generating a structured building inspection report for at least a portion of a building, the method comprising: receiving, building data for the building from one or more data sources, wherein the building data includes structural information about the at least a portion of the building; determining, a layout for the at least a portion of the building based upon the structural information; generating, a guided building assessment plan based upon the building data, wherein the guided building assessment plan provides inspection instructions for a user to gather unstructured user observations of the at least portion of the building; receiving the unstructured user observations; and automatically generating, the structured building inspection report in a predetermined format for delivery to one or more users associated with the building based upon the building data and the unstructured user observations. analyzing, the building data and the unstructured user observations, detecting, one or more conditions in an image included in the unstructured user observations indicative of a state of the building or a component of the building; and synthesizing, the analyzed building data, the analyzed unstructured user observations, and the detected one or more conditions to generate the structured building inspection report, the structured building inspection report comprising a plurality of data modalities. determining, by the one or more AI models using the one or more unstructured user observations and the one or more additional data items, a building fault associated with the at least one of the component or the space of the residential building, a severity of the building fault, and whether a type of repair to resolve the building fault requires repair by a certified professional by classifying the one or more unstructured user observations and the one or more additional data items, t to recognize and categorize building faults; (Claim 19) initiating, , an automatic action to resolve the building fault based upon one or more of: the determined building fault, the severity of the building fault, or the determined type of repair (Claim 19) Alternatively, these steps, under its broadest reasonable interpretation, encompass a human manually (e.g., in their mind, or using paper and pen) generating a structured building inspection report for at least a portion of a building (i.e., one or more concepts performed in the human mind, such as one or more observations, evaluations, judgments, opinions), but for the recitation of generic computer components. If one or more claim limitations, under their broadest reasonable interpretation, covers performance of the limitation(s) in the mind but for the recitation of generic computer components, then it falls within the " mental processes " subject matter grouping of abstract ideas. As such, the Examiner concludes that claim 11 recites an abstract idea (Step 2A - Prong One: YES). Independent claim(s) 1 and 19 are determined to recite an abstract idea under the same analysis. Step 2A - Prong Two: This judicial exception is not integrated into a practical application. The claim(s) recite the additional elements/limitations of: by one or more processors, (Claim 1, 11 and 19) by the one or more processors and using a plurality of artificial intelligence models (Claim 1, 11) using at least one generative artificial intelligence model, using a computer vision model , (Claim 11) using the one or more AI models (Claim1, 19) the one or more AI models trained, using classification machine learning techniques, (Claim 19) building inspection system (Claim 1) one or more memory devices having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations comprising: (Claim 1) a user device (Claim 1) A non-transitory computer readable medium comprising instructions stored thereon for automatically resolving a determined building fault that, when executed by one or more processors, cause the one or more processors to perform operations comprising (Claim 19) The requirement to execute the claimed steps/functions listed above is equivalent to adding the words ''apply it'' on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. This/these limitation(s) do/does not impose any meaningful limits on producing the abstract idea and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(f)). Additionally, “Step 2A - Prong 2”, the recited additional element(s) of “using one or more artificial intelligence (AI) models (Claim 19)” and “ the at least one generative artificial intelligence model trained on historical building data and unstructured user observations” serve merely to generally link the use of the judicial exception to a particular technological environment or field of use. These limitations therefore do not integrate the abstract idea into a practical application (see MPEP 2106.05(h)). The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (Step 2A -Prong Two: NO). Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above in "Step 2A - Prong 2", the requirement to execute the claimed steps/functions listed abov e is equivalent to adding the words "apply it" on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations therefore do not qualify as "significantly more" (see MPEP 2106.05 (f)). As discussed above in “Step 2A - Prong 2”, the recited additional element(s) of “ using one or more artificial intelligence (AI) models (Claim 19) ” serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. These limitations therefore do not qualify as “significantly more 5 ' (see MPEP 2106.05(g, h)). The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claim(s) amount to significantly more than the abstract idea identified above (Step 2B: NO). Regarding Dependent Claims: Dependent claims 4, 5, 10, 14-15, and 20 fail to include any additional elements and are further part of the abstract idea as identified by the Examiner. Dependent claims 2, 3, 6-9, 12, 13 and 16-18 include additional limitations that are part of the abstract idea except for: a connected devices data source configured to provide data regarding one or more connected devices, a user device data source configured to provide data regarding a user device (Claim 2) an integrated software data source configured to provide data regarding integrated software associated with the residential building (Claim 2) wherein the user device is at least one of a smart mobile device, a virtual reality device, or an augmented reality device (Claim 3 and 13) via a conversational chat bot associated with a large language model; (Claim 6, 16) by one or more artificial intelligence (AI) models (Claim 6) wherein the one or more AI models include a generative AI model. (Claim 7) wherein the one or more AI models include a computer vision model (Claim 8) one or more processors (Claim 9, 16, 17, 18) wherein the one or more data sources include at least one of a connected devices data source configured to provide data regarding one or more data source, a user device data source configured to provide data regarding a user device… or an integrated software data source configured to provide data regarding integrated software associated with the building (Claim 12) by the one or more processors and using one or more artificial intelligence (AI) models (Claim 16) The additional elements of the dependent claims are equivalent to adding the words ''apply it'' on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. Even in combination, these additional elements do 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. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim (s) 1-18 are rejected under 35 U.S.C. 103 as being unpatentable over Graham et al. (2022/0407598) in view of Brown (2024/0346036) . Claims 1 Graham et al. discloses a building inspection system for generating a structured building inspection report for at least a portion of a residential building, the building inspection system comprising: one or more memory devices having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations comprising (Graham [0105]): receiving building data for the residential building from one or more data sources, wherein the building data includes structural information about the at least a portion of the residential building (Graham [0660]); See at least “Step 1404 may include parsing or analyzing the unstructured service data using one or more models (e.g., the models 104, 116, 268, or any other model described herein) or other systems or devices to extract any identifiers of building equipment ( e.g., particular systems or devices of building equipment, equipment IDs, equipment models, equipment type, equipment manufacturer, etc.), identifiers of one or more buildings (e.g., street address, building name, etc.), building spaces ( e.g., floors, rooms, zones, parking lots, rooftops, outdoor areas, etc.), determining a layout for the at least a portion of the residential building based upon the structural information (Graham [0015]); See “The system of the present invention is further configured to automatically map a floor plan or layout of a location based on collected crowdsourced data collected as part of the geolocation service.” generating a guided building assessment plan on a user device based upon the building data, wherein the guided building assessment plan provides inspection instructions for a user to gather unstructured user observations of the at least a portion of the building; receiving the unstructured user observations (Graham [0032]); See at least “receiving crowdsourced data associated with one or more of an indoor location and user confirmation of determined location for the user; and providing one or more of augmented reality (AR) and virtual reality (VR) routing guidance in a display interface of a user device.” and wherein the guided building assessment plan comprises one or more questions provided to the user regarding one or more pieces of the structural information (Graham [0130]); See “Response module 120 may also include an inspection module 122 configured to generate and populate a checklist display [questions] such as shown in FIG. 18. The checklist interface enables a user to identify, e.g., with a checkmark, the particular asset being inspected.” See also [0197] for user polling [questions]. Graham et al. does not explicitly disclose generating a report on structural building data. Brown et al. teaches: automatically generating, using an artificial intelligence model, the structured building inspection report in a predetermined format for delivery to one or more users associated with the building based upon the building data the unstructured user observations, and one or more responses from the user to the one or more questions. (Brown [0647]). See at least “The process 1200 is shown to include automatically generating a structured service report in a predetermined format using the AI model (step 1206). In some embodiments, the structured report is generated for delivery to a customer associated with the building equipment.” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included in the method of collecting and managing crowdsourced data in a building, as taught by Graham, the method of processing structural data of the building system, as taught by Brown, to better identify proper response actions or sequences of response actions, regarding equipment to be serviced, technical issues with the items of equipment, and the availability of timely, precise data to use for supporting the service operations (Graham [0003]). Claims 2 and 12 Modified Graham et al. and Brown et al. disclose the limitations above. Modified Brown et al. further teaches: wherein the one or more data sources include at least one of a connected devices data source configured to provide data regarding one or more connected devices, a user device data source configured to provide data regarding a user device, a provider data source configured to provide data regarding a provider, a third party data source configured to provide data from one or more third parties, or an integrated software data source configured to provide data regarding integrated software associated with the residential building (Brown [0610]). See at least “The client device 304 can communicate with the system 200 via the building data platform, and can feedback, reports, and other data to the building data platform. In some implementations, the data repository 204 maintains building data platform specific databases, such as to enable the system 200 to configure the machine learning models 268 on a building data platform-specific basis…” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included in the method of collecting and managing crowdsourced data in a building, as taught by Graham, the method of processing structural data of the building system, as taught by Brown, to better identify proper response actions or sequences of response actions, regarding equipment to be serviced, technical issues with the items of equipment, and the availability of timely, precise data to use for supporting the service operations (Graham [0003]). Claims 3 and 13 Modified Graham et al. and Brown et al. disclose the limitations above. Modified Brown et al. further teaches: wherein the user device is at least one of a smart mobile device, a virtual reality device, or an augmented reality device (Brown [0609]). See at least “This can allow the expert system 700 to provide a platform for a user receiving the data (e.g., customer or field technician) to receive expert feedback from a user of the client device 704 (e.g., expert technician).” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included in the method of collecting and managing crowdsourced data in a building, as taught by Graham, the method of processing structural data of the building system, as taught by Brown, to better identify proper response actions or sequences of response actions, regarding equipment to be serviced, technical issues with the items of equipment, and the availability of timely, precise data to use for supporting the service operations (Graham [0003]). Claims 4 and 14 Modified Graham et al. and Brown et al. disclose the limitations above. Modified Graham et al. further teaches: wherein the guided building assessment plan is at least one of a room-by-room guided building assessment plan or a component-by-component guided building assessment plan (Graham [0018]). See “The system is further configured to providing routing guidance to the team member, including providing the optimal path to the given location requiring attention (i.e., determine the quickest route to reach to intended destination).” Claims 5 and 15 Modified Graham et al. and Brown et al. disclose the limitations above. Modified Graham et al. further teaches: wherein the inspection instructions include requesting at least one of images, natural language written observations, or natural language speech observations (Graham [0021]). See at least “In some embodiments, the system is configured to utilize contextual data analysis to improve the understanding of user requests and user location associated with such requests. Such analytics may include, for example, Natural Language Processing (NLP) analysis and/or computer vision techniques.” Claims 6 and 16 The building inspection system of claim 1, wherein automatically generating the structured building inspection report comprises: receiving a first unstructured user observation from the user via a conversational chat bot associated with a large language model; generating, by the large language model, a follow-up prompt requesting additional information about the first unstructured user observation; (Brown [0446][0475]); See at least “In some embodiments, the user interface includes a chat interface configured to facilitate conversational interaction with the user ( e.g., a chat bot or generative AI interface). The system 100 can be configured to prompt the user for additional information about the building equipment or problem associated with the building equipment and provide dynamic responses to the user based on structured or unstructured data provided by the user via the user interface. in response to receiving the follow-up prompt, receiving a second unstructured user observation providing the additional information (Brown [0743]); See at least “The user can provide additional information such as "It looks like the sensor is reading a short" and the AI model can diagnose the issue and respond with "That's likely the issue, you should replace the sensor with part number 02552740000." The interaction between the user and the AI model may be in the form of a natural language conversation or other interaction in one or more modalities (e.g., text, images, audio, video, etc.) as described in detail throughout the present disclosure.” processing, by one or more artificial intelligence (AI) models, the first unstructured user observation and the second unstructured user observation to generate the structured building inspection report (Brown [0447]). See at least “For example, the interface can include user interface and/or user experience features configured to provide a question/answer-based input/output format, such as a conversational interface, that directs users through providing targeted information for accurately generating predictions of root cause, presenting solutions, or presenting instructions for repairing or inspecting the equipment to identify information that the system can use to detect root causes or other issues. The system can use the interface to present information regarding parts and/or tools to service the equipment…[inspection report]. Claim 7 Modified Graham et al. and Brown et al. disclose the limitations above. Modified Brown et al. further teaches: wherein the one or more AI models include a generative AI model (Brown [0009]). See at least “The method may include training, by the one or more processors, a generative AI model using the plurality of first unstructured service reports.” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included in the method of collecting and managing crowdsourced data in a building, as taught by Graham, the method of processing structural data of the building system, as taught by Brown, to better identify proper response actions or sequences of response actions, regarding equipment to be serviced, technical issues with the items of equipment, and the availability of timely, precise data to use for supporting the service operations (Graham [0003]). Claim 8 Modified Graham et al. and Brown et al. disclose the limitations above. Modified Graham et al. further teaches: wherein the one or more AI models include a computer vision model (Graham [0016]). See at least “the additional data may be collected by utilizing a handheld or integrated light detection and ranging (LIDAR) device for scanning and mapping indoor environments and the system is configured to associate scan data with known features/landmarks based, at least in part, on prior and/or subsequent user location determinations, pre- determined features such as two-dimensional (2-D) floor plans, specific locations of objects (QR code locations, locations of fixed objects identifiable with image-based analysis or computer vision, and the like).” Claim 9 Modified Graham et al. and Brown et al. disclose the limitations above. Modified Graham et al. further teaches: wherein the structured building inspection report comprises a plurality of building faults, and wherein the instructions cause the one or more processors to automatically generate the structured building inspection report by determining priorities for the plurality of building faults and order the plurality of building faults within the structured building inspection report using the determined priorities (Graham [0237]). See at least “the platform may utilize a form of AI or machine learning to determine a status of a building platform (e.g., component of HVAC system) and predict whether the platform is going to fail and/or requires preventative maintenance, thereby assisting building managers in understanding and prioritizing systems and building features in terms of repair, maintenance, and replacement.” Claims 10 and 18 Modified Graham et al. and Brown et al. disclose the limitations above. Modified Brown et al. further teaches: wherein the operations further comprise generating a maintenance plan for the building based upon the structured building inspection report (Brown [0379]). See at least “automatically initiating the one or more actions includes scheduling maintenance to be performed on the building equipment at or before the future time to prevent the building equipment or the part of the building equipment from failing.” Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included in the method of collecting and managing crowdsourced data in a building, as taught by Graham, the method of processing structural data of the building system, as taught by Brown, to better identify proper response actions or sequences of response actions, regarding equipment to be serviced, technical issues with the items of equipment, and the availability of timely, precise data to use for supporting the service operations (Graham [0003]). Claim 11 A computer-implemented method for generating a structured building inspection report for at least a portion of a building, the computer-implemented method comprising: receiving, by one or more processors, building data for the building from one or more data sources, wherein the building data includes structural information about the at least a portion of the building (Graham [0660]); See at least “Step 1404 may include parsing or analyzing the unstructured service data using one or more models (e.g., the models 104, 116, 268, or any other model described herein) or other systems or devices to extract any identifiers of building equipment ( e.g., particular systems or devices of building equipment, equipment IDs, equipment models, equipment type, equipment manufacturer, etc.), identifiers of one or more buildings (e.g., street address, building name, etc.), building spaces ( e.g., floors, rooms, zones, parking lots, rooftops, outdoor areas, etc.), determining, by the one or more processors, a layout for the at least a portion of the building based upon the structural information (Graham [0015]); See “The system of the present invention is further configured to automatically map a floor plan or layout of a location based on collected crowdsourced data collected as part of the geolocation service.” generating, by the one or more processors, a guided building assessment plan on a user device based upon the building data, wherein the guided building assessment plan provides inspection instructions for a user to gather unstructured user observations of the at least a portion of the building; receiving the unstructured user observations; (Graham [0032]); See at least “receiving crowdsourced data associated with one or more of an indoor location and user confirmation of determined location for the user; and providing one or more of augmented reality (AR) and virtual reality (VR) routing guidance in a display interface of a user device.” automatically generating, by the one or more processors and using a plurality of artificial intelligence models, the structured building inspection report in a predetermined format for delivery to one or more users associated with the building based upon the building data and the unstructured user observations (Brown [0647]). See at least “The process 1200 is shown to include automatically generating a structured service report in a predetermined format using the AI model (step 1206). In some embodiments, the structured report is generated for delivery to a customer associated with the building equipment.” detecting, using a computer vision model, one or more conditions in an image included in the unstructured user observations indicative of a state of the building or a component of the building (Graham [0016][0021][0025]); See at least [0025] “Certain aspects of the present invention include a method, including the steps of: receiving, from a plurality of user devices, user feedback data related to one or more spaces of a building; processing the user feedback data using an algorithm applying one or more of Natural Language Processing (NLP), computer vision, and machine learning; and determining, based on the processing, one or more of a type of user feedback or a space of the one or more spaces associated with the feedback.” Graham et al. does not explicitly disclose generating a report on structural building data. Brown et al. teaches: analyzing, using at least one generative artificial intelligence model, the building data and the unstructured user observations, the at least one generative artificial intelligence model trained on historical building data and unstructured user observations (Brown [0678]); synthesizing, using the at least one generative artificial intelligence model, the analyzed building data, the analyzed unstructured user observations, and the detected one or more conditions to generate the structured building inspection report, the structured building inspection report comprising a plurality of data modalities (Brown [0037]). See at least “The engineering data may include one or more user manuals, operating guides, engineering drawings, process flow diagrams, or equipment specifications describing the building equipment or operation thereof. Training the generative AI model may include using the engineering data in combination with the plurality of first unstructured service reports to configure the trained generative AI model.” Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-15 AIA Claim s 19 and 20 are rejected under 35 U.S.C. 102( a)(1 ) as being anticipated by Brown et al. (2024/0346036) . Claim 19 Brown et al. discloses the limitations below: A non-transitory computer readable medium comprising instructions stored thereon for automatically resolving a determined building fault that, when executed by one or more processors, cause the one or more processors to perform operations comprising: (Brown [0745]): receiving one or more unstructured user observations from a user regarding at least one of a component or a space of a residential building (Brown [0660]); See at least “Step 1404 may include parsing or analyzing the unstructured service data using one or more models (e.g., the models 104, 116, 268, or any other model described herein) or other systems or devices to extract any identifiers of building equipment ( e.g., particular systems or devices of building equipment, equipment IDs, equipment models, equipment type, equipment manufacturer, etc.), identifiers of one or more buildings (e.g., street address, building name, etc.), building spaces ( e.g., floors, rooms, zones, parking lots, rooftops, outdoor areas, etc.), processing, using one or more artificial intelligence (AI) models, the one or more unstructured user observations to identify one or more additional data items regarding the at least one of the component or the space; obtaining the one or more additional data items (Brown [0021]); determining, by the one or more AI models using the one or more unstructured user observations and the one or more additional data items, a building fault associated with the at least one of the component or the space of the residential building, a severity of the building fault, and whether a type of repair to resolve the building fault requires repair by a certified professional by classifying the one or more unstructured user observations and the one or more additional data items, the one or more AI models trained, using classification machine learning techniques, to recognize and categorize building faults; (Brown [0617][0447][0480]); See at least [0617] “The prescription can indicate one or more actions for a service technician to perform to verify, service, and/or repair the fault condition, such as instructions for tools and/or parts to use for the item of equipment.” See also “the expert system 700 requests at least one of an identifier or a credential of a user of the client device 704 prior to providing the data to the client device 704 and/or requesting feedback regarding the data from the expert session 708. For example, the expert system 700 can request the feedback responsive to determining that the at least one of the identifier or the credential satisfies a target value for the data.” initiating, using the one or more AI models, an automatic action to resolve the building fault based upon one or more of: the determined building fault, the severity of the building fault, or the determined type of repair (Brown [0289]). See at least “The method may include automatically initiating, by the one or more processors, one or more actions to address the problem based on the information provided via the user interface.” Claim 20 Brown et al. discloses the limitations below: in response to determining the type of repair does not require repair by a certified professional , automatically generating step-by-step instructions for a non-professional user to resolve the building fault; and in response to determining the type of repair requires repair by a certified professional, automatically scheduling a service appointment for professional maintenance personnel to resolve the building fault. (Brown [0607]). See at least “For example, via the expert session 708, the expert session 700 can enable functions such as receiving inputs for a human expert to provide feedback to a user of the client device 304; a human expert to guide the user through the data (e.g., completions) provided to the client device 304, such as reports, insights, and action items;” Response to Arguments 07-37 AIA Applicant's arguments filed with respect to the rejection under 35 USC 101 have been fully considered but they are not persuasive. Applicant Argues: Applicant respectfully submits that the claims are not directed to a mental process, but rather recite the use of "an artificial intelligence model" to generate a "building inspection report in a predetermined format for delivery to one or more users associated with the residential building based upon the building data, the unstructured user observations, and one or more responses from the user to the one or more questions [regarding one or more pieces of the structural information]." Examiner respectfully disagrees and maintains the previous response. Examiner notes that “[c]laims can recite a mental process even if they are claimed as being performed on a computer,” and that “courts have found requiring a generic computer or nominally reciting a generic computer may still recite a mental process even though the claim limitations are not performed entirely in the human mind” (see p. 8 of the October 2019 Update: Subject Matter Eligibility ). The Examiner also notes that “both product claims (e.g., computer system, computer-readable medium, etc.) and process claims may recite mental processes (see p. 8 of the October 2019 Update: Subject Matter Eligibility ). For example, the user can be guided by a printed manual with instructions to gather information for the building assessment. The inspection report could be generated by entering in the findings and being mapped to a database of information. The processor is recited at a high level of generality and the artificial intelligence model responsible for the generating step does not put any limits on how the model and is considered, when given their broadest reasonable interpretation in light of the background, a mathematical calculation. Applicant Argues: Applicant respectfully submits that claim 1 demonstrates that any allegedly abstract feature is integrated into a practical application. Examiner respectfully disagrees and maintains the previous response. The claim recites the following: receiving information; analyzing the information and providing results [generating] of the analyzed information. The receiving, analyzing and generating steps are recited at a high level of generality (i.e., as a general means of gathering data for use in the analyzing step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The processor and artificial intelligence model that performs the generating step is also recited at a high level of generality, and merely automates the generating step. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component (the processor and artificial intelligence model). The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer component (processor and high level recited artificial intelligence model). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea. Applicant Argues: C laim 1 provides a technical solution in that the elements of claim 1 result in an improvement to generation of building inspection reports… Claim 1 therefore provides a technical solution in that the AI model processes multiple types of data, as indicated in paragraph [0124], that a user may be unable to interpret and format into a structured building inspection report. Examiner maintains the previous response. The Examiner notes that this claim of providing a technical solution is not representative of an "actual" improvement to the technology itself, but at best is an improvement to the business method or abstract idea itself using the technology as mere instruction to implement the abstract idea on a generic computer. The Examiner respectfully notes that the features of the claimed invention (i.e. improvement to the generation of building inspection reports) does not represent an improvement to technology, it is merely implementing the abstract idea on a generic computer. Moreover, the Examiner respectfully notes that the needed "improvement" in terms of patent eligibility is not one resulting from programming a generic processor or model to perform a different (or even improved) function, but rather a specific and actual improvement to the machine itself is needed. Based on these findings of fact, the Examiner contends the claims are indeed directed towards an abstract idea and Applicant's arguments to the contrary are considered to be non-persuasive. Applicant Argues: Applicant respectfully submits that claim 1 recites subject matter similar to the eligible subject matter included in Claim 1 of Example 42 of the USPTO Subject Matter Eligibility Examples: Abstract Ideas ("Example 42"). Examiner respectfully disagrees. The claims of Examiner 42 are not at all like the instant claims. In Example 42 Claim 1 the claims are directed to converting nonstandard updated information into the standardized format. The combination of additional elements is what makes the claim patent eligible. The instant claims are more like Example 47 Claim 2 where the inventive steps generic use of machine learning models to execute the abstract idea. Similar to Example 42, Claim 2, the instant claims gather data, direct a user to gather more data and generate a report based on the user findings. Applicant Argues: Applicant respectfully submits that the claims cover a particular technical solution to a problem, including the use of an AI model trained to provide expertise that a user lacks and the use of an AI model to convert unstructured data into structured data, and are therefore also eligible under Step 2B. The Examiner maintains that this claim of providing a particular solution is not representative of an "actual" improvement to the technology itself, but at best is an improvement to the business method or abstract idea itself. Applicant Argues: Claims 11 and 19 Claim 11 does not present eligible subject matter for the same reasons listed above . 07-37 AIA Applicant's arguments filed with respect to the rejection under 35 USC 103 have been fully considered but they are not persuasive. Applicant Argues: Applicant respectfully submits that Brown is silent with respect to any indication of processes being performed with respect to a residential building. Examiner respectfully disagrees. Brown teaches a building system of a building, where a residential building is still a building. See [0004] “One or more aspects relate to building management systems and methods that implement building equipment servicing.” Furthermore, The “residential” description or label of the building is not positively recited as actually being used to change or affect the manner of building inspection systems. See ( Gulack , 703 F.2d at 1386, 217 USPQ at 404). Here, by contrast, the type of building (residential or commercial) does not a have a functional relationship to the claimed steps. See MPEP 2111.05 B II. Where a functional relationship must be established to be given patentable weight. Applicant Argues: Brown does not disclose at least "receiving one or more unstructured user observations from a user regarding at least one of a component or a space of a residential building." Examiner respectfully disagrees and maintains the previous response. See [0443] “ The system can enable real-time messaging and/or conversational interfaces for users to provide field data [unstructured observations] regarding equipment to the system (including presenting targeted queries to users that are expected to elicit relevant responses for efficiently receiving useful response information from users) and guide users, such as service technicians, through relevant service, diagnostic, troubleshooting, and/or repair processes.” Applicant Argues: For example, Graham fails to disclose, teach, or suggest at least "determining a layout for the at least a portion of the residential building based upon the structural information" or "generating a guided building assessment plan on a user device based upon the building data, wherein the guided building assessment plan provides inspection instructions for a user to gather unstructured user observations of the at least a portion of the residential building, and wherein the guided building assessment plan comprises one or more questions provided to the user regarding one or more pieces of the structural information." Examiner respectfully disagrees and maintains that Graham teaches both. First, Graham teaches updating an existing layout in paragraph [0193]. Graham also teaches a building model that is allows for user updates in paragraph [0030]. Graham teaches routing a user to gather building information in paragraph [0032]. See at least “receiving crowdsourced data associated with one or more of an indoor location and user confirmation of determined location for the user; and providing one or more of augmented reality (AR) and virtual reality (VR) routing guidance in a display interface of a user device.” However, it should be noted that Brown also teaches this in paragraph [0443] “The system can enable real-time messaging and/or conversational interfaces for users to provide field data [unstructured observations] regarding equipment to the system (including presenting targeted queries to users that are expected to elicit relevant responses for efficiently receiving useful response information from users) and guide users, such as service technicians, through relevant service, diagnostic, troubleshooting, and/or repair processes.” See also (Graham [0130]); See “Response module 120 may also include an inspection module 122 configured to generate and populate a checklist display [questions] such as shown in FIG. 18. The checklist interface enables a user to identify, e.g., with a checkmark, the particular asset being inspected.” See also [0197] for user polling [questions]. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to RASHIDA R SHORTER whose telephone number is (571)272-9345. The examiner can normally be reached Monday- Friday from 9am- 530pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jessica Lemieux can be reached at (571) 270-3445. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /RASHIDA R SHORTER/Primary Examiner, Art Unit 3626 Application/Control Number: 18/779,945 Page 2 Art Unit: 3626 Application/Control Number: 18/779,945 Page 3 Art Unit: 3626 Application/Control Number: 18/779,945 Page 4 Art Unit: 3626 Application/Control Number: 18/779,945 Page 5 Art Unit: 3626 Application/Control Number: 18/779,945 Page 6 Art Unit: 3626 Application/Control Number: 18/779,945 Page 7 Art Unit: 3626 Application/Control Number: 18/779,945 Page 8 Art Unit: 3626 Application/Control Number: 18/779,945 Page 9 Art Unit: 3626 Application/Control Number: 18/779,945 Page 10 Art Unit: 3626 Application/Control Number: 18/779,945 Page 11 Art Unit: 3626 Application/Control Number: 18/779,945 Page 12 Art Unit: 3626 Application/Control Number: 18/779,945 Page 13 Art Unit: 3626 Application/Control Number: 18/779,945 Page 14 Art Unit: 3626 Application/Control Number: 18/779,945 Page 15 Art Unit: 3626 Application/Control Number: 18/779,945 Page 16 Art Unit: 3626 Application/Control Number: 18/779,945 Page 17 Art Unit: 3626 Application/Control Number: 18/779,945 Page 18 Art Unit: 3626 Application/Control Number: 18/779,945 Page 19 Art Unit: 3626 Application/Control Number: 18/779,945 Page 20 Art Unit: 3626 Application/Control Number: 18/779,945 Page 21 Art Unit: 3626 Application/Control Number: 18/779,945 Page 22 Art Unit: 3626 Application/Control Number: 18/779,945 Page 23 Art Unit: 3626 Application/Control Number: 18/779,945 Page 24 Art Unit: 3626 Application/Control Number: 18/779,945 Page 25 Art Unit: 3626
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