Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED CORRESPONDENCE
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 March 16, 2026 has been entered.
Status of Claims
Claim 1 has been amended.
No claims have been cancelled.
No claims have been added.
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 – 7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite:
acquire and hold data including map data, sensing data acquired by sensing a state of an infrastructure, and repair actual result data of the infrastructure;
display a map image of an area specified by a user based on the map data with information regarding the state of the infrastructure determined on the basis of the sensing data in a superimposed manner on the map image, wherein the information regarding the state of the infrastructure is mapped on the map image by color coding or a mark;
predict a future degree of deterioration of each infrastructure at a future time specified by the user on the basis of data including the sensing data, extract the infrastructure having the predicted future degree of deterioration exceeding a predetermined repair reference value, and display the extracted infrastructure on the map image as a candidate for an infrastructure to be repaired by combining related information including at least one of weather information or traffic volume specified by the user; and
display a result of aggregation of the sensing data and indexes related to the infrastructure maintenance management on a dashboard in addition to the map image
The invention is directed towards the abstract idea of maintenance management based on the collection and comparison of information and, based on a rule(s), identify options, which corresponds to “Mental Processes” and “Certain Methods of Organizing Human Activities” as it is directed towards steps that can be performed by a human(s) and/or with the aid of pen and paper, e.g., having a user collect information regarding the state of an infrastructure by sensing the condition using the sense of sight or sense of touch, looking at a map, writing on the map, and presenting the map to convey the location of where there is an issue, as well as comparing the information collected against expected information, i.e. expected condition or reference value of the infrastructure, determine the degradation/deterioration of the infrastructure based on the comparison and any applicable rules, and presenting the results of the analysis.
The limitations of:
acquire and hold data including map data, sensing data acquired by sensing a state of an infrastructure, and repair actual result data of the infrastructure;
display a map image of an area specified by a user based on the map data with information regarding the state of the infrastructure determined on the basis of the sensing data in a superimposed manner on the map image, wherein the information regarding the state of the infrastructure is mapped on the map image by color coding or a mark;
predict a future degree of deterioration of each infrastructure at a future time specified by the user on the basis of data including the sensing data, extract the infrastructure having the predicted future degree of deterioration exceeding a predetermined repair reference value, and display the extracted infrastructure on the map image as a candidate for an infrastructure to be repaired by combining related information including at least one of weather information or traffic volume specified by the user; and
display a result of aggregation of the sensing data and indexes related to the infrastructure maintenance management on a dashboard in addition to the map image
are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of a generic units (as discussed above, this technology is not directed towards hardware, but software, therefore, the claims are reciting generic computer instructions to perform functions that can be performed by a human, as was discussed above). That is, other than reciting generic units nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the generic units in the context of this claim encompasses a user can observe, using their senses, the condition of an infrastructure and analyze the information by comparing it against known/expected information, referring to a map, marking the location of where they have determined, based on the comparison and any applicable rules, the location where there will be future deterioration, and presenting the results of the analysis. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of a generic units, then it falls within the “Mental Processes” and “Certain Methods of Organizing Human Activities” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – generic units communicate, store (hold), and display information, as well as performing operations that a human can perform in their mind and/or pen and paper, i.e. analyzing the information, as was discussed above, to determine the future deterioration of an infrastructure and marking it on a map. The generic units in the steps are recited at a high-level of generality (i.e., as a generic units can perform the insignificant extra solution steps of communicating, storing (holding), and displaying information (See MPEP 2106.05(g) while also reciting that the a generic units are merely being applied to perform the steps that can be performed in the human mind and/or pen and paper; "[use] of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” Therefore, according to the MPEP, this is not solely limited to computers but includes other technology that, recited in an equivalent to “apply it,” is a mere instruction to perform the abstract idea on that technology (See MPEP 2106.05(f)) such that it amounts no more than mere instructions to apply the exception using generic units.
Accordingly, 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 claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using generic units to perform the steps of:
acquire and hold data including map data, sensing data acquired by sensing a state of an infrastructure, and repair actual result data of the infrastructure;
display a map image of an area specified by a user based on the map data with information regarding the state of the infrastructure determined on the basis of the sensing data in a superimposed manner on the map image, wherein the information regarding the state of the infrastructure is mapped on the map image by color coding or a mark;
predict a future degree of deterioration of each infrastructure at a future time specified by the user on the basis of data including the sensing data, extract the infrastructure having the predicted future degree of deterioration exceeding a predetermined repair reference value, and display the extracted infrastructure on the map image as a candidate for an infrastructure to be repaired by combining related information including at least one of weather information or traffic volume specified by the user; and
display a result of aggregation of the sensing data and indexes related to the infrastructure maintenance management on a dashboard in addition to the map image
amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Additionally:
Claim 2 is directed towards human activities directed towards describing a rule and providing a suggestion of when to perform inspections.
Claim 3 is directed towards collecting and comparing/analyzing information to determine the condition of the infrastructure.
Claim 4 is directed to human activities (select), extra-solution activities (present/display), and reciting generic technology at a high level of generality and applying it to the abstract idea.
Although the claim recites “AI,” (which the Examiner presumes is the acronym for “artificial intelligence”) the claims and specification fail to provide sufficient disclosure regarding an improvement to how a machine learning algorithm can be trained, but simply recites a high-level generic recitation that a machine learning algorithm is being trained. There is insufficient evidence from the specification to indicate that the use of the machine learning algorithm involves anything other than the generic application of a known technique in its normal, routine, and ordinary capacity or that the claimed invention purports to improve the functioning of the computer itself or the machine learning algorithm. None of the limitations reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field, applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, effects a transformation or reduction of a particular article to a different state or thing, or applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Even training and applying AI is simply application of a computer model, itself an abstract idea manifestation. Further, such training and applying of a model is no more than putting data into a black box machine learning operation. The nomination as being AI is a functional label, devoid of technological implementation and application details. The specification does not contend it invented any of these activities, or the creation and use of such machine learning models. In short, each step does no more than require a generic computer to perform generic computer functions. As to the data operated upon, "even if a process of collecting and analyzing information is 'limited to particular content' or a particular 'source,' that limitation does not make the collection and analysis other than abstract." SAP America, Inc. v. InvestPic LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018).
The Examiner asserts that the scope of the disclosed invention, as presented in the originally filed specification, is not directed towards the improvement of machine learning, but directed towards managing the maintenance/repair of infrastructure based on collected information about the condition of the infrastructure. The specification’s disclosure on machine learning is nothing more than a high general explanation of generic technology and applying it to the abstract idea. Referring to MPEP § 2106.05(f), the selection and presentation by AI are merely being used to facilitate the tasks of the abstract idea, which provides nothing more than a results-oriented solution that lacks detail of the mechanism for accomplishing the result and is equivalent to the words “apply it,” per MPEP § 2106.05(f). The Examiner asserts that in light of the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence, the claimed invention is analogous to Example 47, Claim 2.
Further, the combination of these elements is nothing more than a generic computing system with AI. Because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP § 2106.05(f), they do not integrate the abstract idea into a practical application.
Accordingly, 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 an abstract idea.
Claim 5 is directed towards simulating or predicting the life cycle cost based on the collected information and comparison and/or reference to a rule in order to predict/simulate the cost and the extra-solution activity of presenting/displaying information.
Claim 6 is directed towards human activities for creating a repair plan and performing the repair work based on the repair plan.
Claim 7 is directed towards the extra-solution activity of displaying and receiving information and descriptive subject matter describing the displayed information. The filtering process is directed towards displaying and organizing desired information in response to what a user wants to have displayed.
In summary, the dependent claims are simply directed towards providing additional descriptive factors that are considered for managing the repair of an asset. Accordingly, the claims are not patent eligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 –
(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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1 – 7 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Sunde et al. (US PGPub 2022/0101272 A1).
In regards to claim 1, Sunde discloses an infrastructure maintenance management support system that supports infrastructure maintenance management, the system comprising a processor or processors configured to:
acquire and hold data including map data, sensing data acquired by sensing a state of an infrastructure, and repair actual result data of the infrastructure (Fig. 3A, 3B, 4A, 4B, 6; ¶ 70, 73 wherein the system collects and stores map information; ¶ 48, 53, 54, 55 wherein the system further collects and stores sensing data; ¶ 51, 58, 59 wherein historical repair information is stored);
display a map image of an area specified by a user based on the map data with information regarding the state of the infrastructure determined on the basis of the sensing data in a superimposed manner on the map image, wherein the information regarding the state of the infrastructure is mapped on the map image by color coding or a mark (Fig. 3A, 3B, 4A, 4B, 6; ¶ 48, 53, 54, 55, 67, 69, 70, 73; Claim 1 wherein, based on the collected and stored information, the system displays a map of the location that requires servicing, e.g., repair, maintenance plan, etc., and wherein the information is marked by superimposing the additional information regarding the condition of the infrastructure onto the map;
Fig. 4B, 6; Abstract; ¶ 25 and corresponding examples disclosed in ¶ 26 – 43, 53, 65 wherein the system is configured to capture, process, and display information for assisting a user with evaluating the condition of a plurality of different infrastructure types, e.g., roads, signs, power lines, and etc., and presents the user with a dashboard to allow them to filter through information and present information that the user is interested in. As a non-limiting example, the user selects the chevron of Fig. 6 to select roads and is presented with a plurality of additional filtering options to mark roads requiring a particular maintenance type, e.g., “Mill and overlay” and marking the roads (e.g., marking the roads or using a different color to mark the roads to differentiate the roads for the treatment against the roads that do not) in the center map image of roads satisfying this filter option. As stated above, Sunde discloses a plurality of infrastructure types and Fig. 6 provides an example for when the user selects “Roads” (see also: ¶ 58, 76). Sunde provides another example where the system displays of map identifying the presence and type of signage.);
predict a future degree of deterioration of each infrastructure at a future time specified by the user on the basis of data including the sensing data, extract the infrastructure having the predicted future degree of deterioration exceeding a predetermined repair reference value, and display the extracted infrastructure on the map image as a candidate for an infrastructure to be repaired by combining related information including at least one of weather information or traffic volume specified by the user (¶ 49, 51, 52, 58, 59, 61, 63 wherein the system provides predictions regarding deterioration of the infrastructure based on the collected and stored information and will provide a maintenance plan for the infrastructure based on the prediction and request by a user.;
¶ 44, 45, 50, 54, 65, 66 wherein machine learning is used to analyze the information and present its results to assist with the generation and implementation of the maintenance plan at the request of a user;
Fig. 4B, 6; Abstract; ¶ 25 and corresponding examples disclosed in ¶ 26 – 43, 53, 65 wherein the system is configured to capture, process, and display information for assisting a user with evaluating the condition of a plurality of different infrastructure types, e.g., roads, signs, power lines, and etc., and presents the user with a dashboard to allow them to filter through information and present information that the user is interested in. As a non-limiting example, the user selects the chevron of Fig. 6 to select roads and is presented with a plurality of additional filtering options to mark roads requiring a particular maintenance type, e.g., “Mill and overlay” and marking the roads (e.g., marking the roads or using a different color to mark the roads to differentiate the roads for the treatment against the roads that do not) in the center map image of roads satisfying this filter option. As stated above, Sunde discloses a plurality of infrastructure types and Fig. 6 provides an example for when the user selects “Roads”. Sunde provides another example where the system displays of map identifying the presence and type of signage.
¶ 48, 49, 50, 51, 52, 53, 58, 59 wherein the system is not only provided with data of expected degradation to monitor/determine the state of the infrastructure, but will dynamically modify expected degradation based on the data that is being collected and will monitor the location to determine if a trend exists, which further assists with the generation of the dynamically based maintenance plan. The system will also attach sensors to vehicles in order to more closely monitor the condition of the infrastructure, wherein the vehicles have assigned routes, e.g., garbage trucks, recycling trucks, and sweepers are vehicles that follow an assigned schedule and route and the system can utilize this information to attach a sensor and monitor the condition of the roads these vehicles are traveling on to predict degradation of the road and dynamically generate a maintenance plan. The system can also utilize traffic information to determine the current usage of the road, which, in turn, further allows the system to dynamically generate the maintenance plan. The system further blends stock aging curves and actual measured data to form a blended aging curve for the infrastructure to provide an optimized measurement for the agent of the infrastructure to determine when maintenance should be performed, i.e. when the condition of the road has exceeded an acceptable threshold value that triggers its maintenance/repair. Finally, the system can also deploy vehicles to drive onto certain streets to collect information regarding the state of the street and continue monitoring the infrastructure over time to determine the priority or decision to repair); and
display a result of aggregation of the sensing data and indexes related to the infrastructure maintenance management on a dashboard in addition to the map image (¶ 73 wherein a dashboard is displayed that includes information of the location for the maintenance plan, repair cost estimates, determined rating of the asset, and so forth;
Fig. 3A, 3B, 4A, 5A, 5B, 6 wherein the system also provides a dashboard/user interface that displays sensed data and indexes related to the infrastructure maintenance management in addition to the map image
Fig. 4B, 6; Abstract; ¶ 25 and corresponding examples disclosed in ¶ 26 – 43, 53, 65 wherein the system is configured to capture, process, and display information for assisting a user with evaluating the condition of a plurality of different infrastructure types, e.g., roads, signs, power lines, and etc., and presents the user with a dashboard to allow them to filter through information and present information that the user is interested in. As a non-limiting example, the user selects the chevron of Fig. 6 to select roads and is presented with a plurality of additional filtering options to mark roads requiring a particular maintenance type, e.g., “Mill and overlay” and marking the roads (e.g., marking the roads or using a different color to mark the roads to differentiate the roads for the treatment against the roads that do not) in the center map image of roads satisfying this filter option. As stated above, Sunde discloses a plurality of infrastructure types and Fig. 6 provides an example for when the user selects “Roads”. Sunde provides another example where the system displays of map identifying the presence and type of signage.).
In regards to claim 2, Sunde discloses the infrastructure maintenance management support system according to claim 1, wherein the processor or processors are further configured to:
determine a difference between the future degree of deterioration of each infrastructure at a certain point of time predicted on the basis of data including the sensing data and an inspection value acquired by sensing a state of the infrastructure at the certain point of time;
set a first inspection cycle for each infrastructure if the difference is equal to or smaller than a predetermined threshold;
set a second inspection cycle for each infrastructure if the difference is larger than the predetermined threshold, the second inspection cycle being shorter than the first inspection cycle; and
display the first inspection cycle or the second inspection cycle on the map image as the information regarding the state of the corresponding infrastructure (¶ 48, 49, 50, 51, 52, 53, 58, 59 wherein the system is not only provided with data of expected degradation to monitor/determine the state of the infrastructure, but will dynamically modify expected degradation based on the data that is being collected and will monitor the location to determine if a trend exists, which further assists with the generation of the dynamically based maintenance plan. The system will also attach sensors to vehicles in order to more closely monitor the condition of the infrastructure, wherein the vehicles have assigned routes, e.g., garbage trucks, recycling trucks, and sweepers are vehicles that follow an assigned schedule and route and the system can utilize this information to attach a sensor and monitor the condition of the roads these vehicles are traveling on to predict degradation of the road and dynamically generate a maintenance plan. The system can also utilize traffic information to determine the current usage of the road, which, in turn, further allows the system to dynamically generate the maintenance plan. The system further blends stock aging curves and actual measured data to form a blended aging curve for the infrastructure to provide an optimized measurement for the agent of the infrastructure to determine when maintenance should be performed, i.e. when the condition of the road has exceeded an acceptable threshold value that triggers its maintenance/repair. Finally, the system can also deploy vehicles to drive onto certain streets to collect information regarding the state of the street and continue monitoring the infrastructure over time to determine the priority or decision to repair.).
In regards to claim 3, Sunde discloses the infrastructure maintenance management support system according to claim 2, wherein the processor or processors are further configured to determine soundness of the infrastructure on the basis of the sensing data acquired by the inspection (¶ 48, 49, 51, 52, 53, 58, 59 wherein the data is collected to determine the condition of the infrastructure).
In regards to claim 4, Sunde discloses the infrastructure maintenance management support system according to claim 1, wherein the processor or processors are further configured to select a method to be adopted for repairing the candidate infrastructure by Artificial Intelligence (AI), and present the selected method (¶ 44, 45, 50, 54, 65, 66 wherein machine learning is used to analyze the information and present its results to assist with the generation and implementation of the maintenance plan).
In regards to claim 5, Sunde discloses the infrastructure maintenance management support system according to claim 1, wherein the processor or processors are further configured to perform simulation of a life cycle cost when repairing the candidate infrastructure, and present a result of the simulation (¶ 50, 51, 52, 58, 59, 60, 61, 73 wherein the system performs a simulation of the life cycle cost for the maintenance plan and presents the results to optimize the coordination effort to maintain and upgrade the infrastructure).
In regards to claim 6, Sunde discloses the infrastructure maintenance management support system according to claim 1, wherein the processor or processors are further configured to:
create a repair plan including a method, a work schedule, and a budget for an infrastructure selected from the candidate and record the repair plan as repair plan data; and
perform project management related to repair work performed on the basis of the repair plan
(¶ 50, 51, 52, 58, 59, 60, 61, 73 wherein the system generates and provides a maintenance plan that includes the repair plan, schedule, and budget for the maintenance project and stores the plan for viewing by a user, monitoring the progress of the entity implementing the plan, and the management of the plan).
In regards to claim 7, Sunde discloses the infrastructure maintenance management support system according to claim 1, wherein the processor or processors are configured to:
digitally present a screen display including the image and a filter;
electrically receive an input through the filter digitally presented on the screen display to specify the information regarding the state of the infrastructure; and
digitally present the specified information regarding the state of the infrastructure on the map image in the superimposed manner by the color coding or the mark
(Fig. 4B, 6; Abstract; ¶ 25 and corresponding examples disclosed in ¶ 26 – 43, 53, 65 wherein the system is configured to capture, process, and display information for assisting a user with evaluating the condition of a plurality of different infrastructure types, e.g., roads, signs, power lines, and etc., and presents the user with a dashboard to allow them to filter through information and present information that the user is interested in. As a non-limiting example, the user selects the chevron of Fig. 6 to select roads and is presented with a plurality of additional filtering options to mark roads requiring a particular maintenance type, e.g., “Mill and overlay” and marking the roads (e.g., marking the roads or using a different color to mark the roads to differentiate the roads for the treatment against the roads that do not) in the center map image of roads satisfying this filter option. As stated above, Sunde discloses a plurality of infrastructure types and Fig. 6 provides an example for when the user selects “Roads”. Sunde provides another example where the system displays of map identifying the presence and type of signage.).
Response to Arguments
Applicant's arguments filed 3/16/2026 have been fully considered but they are not persuasive.
Rejection under 35 USC 101
The rejection under 35 USC 101 has been maintained.
The Examiner asserts that the claimed invention is not improving upon infrastructure maintenance or the infrastructure itself, but directed towards the collection and comparison of information and, based on a rule(s), identify options for the purpose of managing the maintenance of an infrastructure, e.g., notifying when maintenance is required. The claimed invention can be performed by a human(s) in their mind and/or through the aid of pen and paper. The claimed invention encompasses having a user collect information regarding the state of an infrastructure by sensing the condition using the sense of sight or sense of touch, looking at a map, writing on the map, and presenting the map to convey the location of where there is an issue, as well as comparing the information collected against expected information, i.e. expected condition or reference value of the infrastructure, determine the degradation/deterioration of the infrastructure based on the comparison and any applicable rules, and presenting the results of the analysis.
The applicant refers to a “digital twin” in the specification, however, this has not been claimed. Moreover, in light of the specification, even if this element were positively claimed, it would be insufficient to overcome the rejection. The “digital twin” is nothing more than a representation of an actual asset and, more specifically, encompasses a human drawing and writing down information about an asset based on historical and current information and extrapolating when sufficient deterioration has occurred to determine when maintenance should be performed. The claimed invention is not directed towards creating and maintaining a “digital twin” of a real-world object in order to simulate how it is operating, how it is being affected by its environment, and the like to determine the deterioration rate of the real-world asset so that a determination can be made on when it will require maintenance. The simulation discussed in the specification is directed toward a cost analysis not an analysis that is simulating how the asset is/will perform or operate.
With regards to “reduce a load of information collection”, the Examiner asserts that the claimed invention does not recite such a feature nor does it present elements directed towards such a technological improvement. The claimed invention does not rise to the level of Enfish, DDR Holdings, or CoreWireless wherein demonstrable technological improvements were discussed, identified, and provided to show a demonstrable difference in technological performance against the prior state of the art. The claimed invention recites generic technology at a high level of generality to perform extra-solution activities of communicating, storing/holding, and displaying/presenting information and performing operations that a human can perform in their mind and/or with the aid of pen and paper, i.e. analyzing the information, as was discussed above, to determine the future deterioration of an infrastructure and marking it on a map
Finally, with regards to the Berkheimer analysis, the Examiner asserts that the rejection never stated “well-understood, routine, and conventional” and, therefore, there is no requirement to provide any evidence because the Examiner’s analysis is not based on this analysis.
Rejection under 35 USC 102
The Examiner asserts that the applicant’s arguments are directed towards newly amended limitations and are, therefore, considered moot. However, the Examiner has responded to the newly submitted amendments, which the arguments are directed to, in the rejection above, thereby addressing the applicant’s arguments.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure can be found in the attached PTO-892 Notice of References Cited.
Peterson et al. (US Patent 9,863,928 B1); Riland et al. (US PGPub 2016/0343093 A1) – which disclose maintenance management systems for monitoring and determining the condition of infrastructure
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GERARDO ARAQUE JR whose telephone number is (571)272-3747. The examiner can normally be reached Monday - Friday 8-4:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sarah Monfeldt can be reached at 571-270-1833. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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GERARDO ARAQUE JR
Primary Examiner
Art Unit 3629
/GERARDO ARAQUE JR/Primary Examiner, Art Unit 3629 4/20/2026
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