Prosecution Insights
Last updated: April 19, 2026
Application No. 18/215,861

INTELLIGENT BRIDGE CONDITION MONITORING

Final Rejection §101§103
Filed
Jun 29, 2023
Examiner
LEE, SANGKYUNG
Art Unit
2858
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
International Business Machines Corporation
OA Round
2 (Final)
61%
Grant Probability
Moderate
3-4
OA Rounds
2y 8m
To Grant
66%
With Interview

Examiner Intelligence

Grants 61% of resolved cases
61%
Career Allow Rate
86 granted / 141 resolved
-7.0% vs TC avg
Minimal +5% lift
Without
With
+4.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
46 currently pending
Career history
187
Total Applications
across all art units

Statute-Specific Performance

§101
24.1%
-15.9% vs TC avg
§103
54.6%
+14.6% vs TC avg
§102
11.8%
-28.2% vs TC avg
§112
8.3%
-31.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 141 resolved cases

Office Action

§101 §103
DETAILED ACTION 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 . Status of the claims The amendment received on March 12, 2026 has been acknowledged and entered. Claims 1, 4, 8, 11,15, and 18 are amended. Claims 2, 5, 9, 12, 16, and 19 are cancelled. Claims 26-27 are newly added. Thus, claims 1, 3-4, 6-8, 10-11, 13-15, 17-18, 20-27 are currently pending. Claims 22-25 were previously withdrawn. Response to Arguments Applicant’s arguments filed March 12, 2026 with respect to the claim rejection of claims 4 and 11 under 35 U.S.C. 112(b) have been fully considered and are persuasive. Thus, the claim interpretation under 35 U.S.C. 112(b) has been withdrawn. Applicant’s arguments filed March 12, 2026 with respect to the claim rejection of claims 8-14 under 35 U.S.C. 101 step 1 have been fully considered and are persuasive. Thus, the claim rejection of claim 8 under 35 U.S.C. 101 step 1 has been withdrawn. Applicant’s arguments filed on March 12, 2026 with respect to claims 1, 3-4, 6-8, 10-11, 13-15, 17-18, 20-27 under 35 U.S.C. 101 have been considered but are moot because the new ground of rejection. However, since the Applicant’s argument is related to current rejection, Applicant’s arguments are addressed as follows: On the page of 11, Applicant alleges that “[U]nder MPEP §2106.04(a)(2), a claim recites a mental process only when it can be practically performed in the human mind or with pen and paper. The operations recited in amended claim 1 cannot be performed mentally because they require collecting real-time vibration measurements from physical sensors embedded in vehicles, transmitting the collected sensor data through telematics and network communication infrastructure, and executing computer- implemented filtering and processing operations to detect anomalies. Such operations necessarily require computer processing and sensor infrastructure and therefore fall outside the mental process category.” Examiner respectfully disagrees. If a determining step is mental process, it does not matter if it is performed by a person, or computer or a person w/the aid of pen and paper. It is still a mental processes (see MEPE 2106.04.a.2.III state that Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer"). Mental processes recited in claims that require computers are explained further below with respect to point C.). On the page of 11, Applicant further alleges that “[F]urther, the claimed filtering of vibration data based on contextual information improves the functioning of the monitoring system by eliminating noisy data (such as variations in sensor readings caused by factors like weather or traffic) prior to baseline comparison, thereby increasing the accuracy and reliability of anomaly detection (see, e.g., paragraphs [0063], [0071], [0077]), which is indicative of a technological improvement to bridge monitoring and safety operations. Improvements in the accuracy and efficiency of sensor-based monitoring systems constitute technological improvements recognized under MPEP §2106.05(a). Examiner respectfully disagrees. Applicant has argued that the abstract idea itself is significant. However, an abstract idea itself is just that, abstract, and whether such feature is or is not significant does not preclude it from being considered abstract. An abstract idea by itself, whether it or not it has a benefit, does not reasonably overcome a 101 rejection because it is still an abstract idea. Applicant has not, respectfully, demonstrated with evidence why the abstract idea itself would amount to more than an abstract idea. Therefore, the above advantages relate to abstract idea limitations which are not considered. The Improvements (or inventive steps) in the abstract idea are not qualified as improvements indicating a practical application. Therefore, the pending claims are not patent eligible since a claim for a new abstract idea is still an abstract idea (see MPEP 2106.05(a).I) and an improvement in the abstract idea itself is not an improvement in technology (see MPEP 2106.05(a).II: Examples that the courts have indicated may not be sufficient to show an improvement to technology include: iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48)). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Further, the additional elements such as a processor, computer-implemented method, a computer program product comprising one or more computer readable storage media having program instructions collectively stored on the one or more computer readable storage media processor are recited at a high-level of generality (MPEP 2106.05(d)). Further, note that step of obtaining vibration data from a vehicle crossing the bridge is insignificant (gathering data) extra-solution activity (MPEP 2106.05(g)). The step of performing, by the processor set, a predefined remediation action is insignificant (post-solution) extra-solution activity. Merely “notifying” a result (i.e., performing a predefined remediation action) is nothing more than outputting a signal or displaying result. There is established case law (electric power group for example) to prove that such a feature is insufficient extra solution activity (see MPEP 2106.05(g)). Furthermore, the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception because these additional elements/steps are well-understood, routine, and conventional in the relevant based on the prior art of record (Dingli, Du (US 2023/0049919 A1)). Therefore, independent claims 1, 8, and 15 are not patent eligible. Claim Rejections - 35 USC § 101 Claims 1, 3-4, 6-8, 10-11, 13-15, 17-18, 20-21, and 26-27 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Specifically, representative Claim 1 recites: A computer-implemented method, comprising: determining, by a processor set, different baseline vibration patterns of a bridge for different vehicle categories based on vibration data collected from one or more vehicle-embedded vibration sensors of plural vehicles in the respective vehicle categories; obtaining, by the processor set, vibration data from at least one vehicle-embedded vibration sensor of a vehicle crossing the bridge; filtering, by the processor set, the vibration data obtained from the vehicle to eliminate vibration data according to a context including a predetermined factor of disinterest; classifying, by the processor set, the vehicle into a respective one of the vehicle categories; selecting, by the processor set, a respective one of the different baseline vibration patterns based on the respective one of the vehicle categories; determining, by the processor set, a difference between the filtered vibration data and the respective one of the different baseline vibration patterns; and in response to the difference exceeding a predefined threshold, performing, by the processor set, a predefined remediation action associated with the bridge. The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements.” Step 1: under the Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (Process). Step 2A, Prong One: under the Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the groupings of subject matter when recited as such in a claim limitation that falls into the grouping of subject matter when recited as such in a claim limitation, that covers mathematical concepts - mathematical relationships, mathematical formulas or equations, mathematical calculations and mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion. For example, the limitations of “determining, by a processor set, different baseline vibration patterns of a bridge for different vehicle categories based on vibration data collected from one or more vehicle-embedded vibration sensors of plural vehicles in the respective vehicle categories (paras. [0077]: step 420, [0082]: step 710 of instant application),” “filtering, by the processor set, the vibration data obtained from the vehicle to eliminate vibration data according to a context including a predetermined factor of disinterest (para. [0063]: including only data from vehicles in that vehicle category of instant application),” “classifying, by the processor set, the vehicle into a respective one of the vehicle categories (para. [0084]: step 730 of instant application),” and “selecting, by the processor set, a respective one of the different baseline vibration patterns based on the respective one of the vehicle categories (para. [0085]: step 740 of instant application)” are mental processes (i.e., evaluation or judgement). Further, the limitation of “determining, by the processor set, a difference between the filtered vibration data collected from the vehicle and the respective one of the different baseline vibration patterns (para. [0086]: step 750 of instant application) and in response to the difference exceeding a predefined threshold (para. [0087]: step 760 of instant application)” is mathematical calculations because determining a difference between the vibration data collected from the vehicle and the respective one of the baseline vibration patterns is indicative of mathematical calculation. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mathematical concepts and/or human mind, then it falls within the “Mental Processes” and/or “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Similar limitations comprise the abstract ideas of Claims 8 and 15. Step 2A, Prong Two: under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application. In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception. This judicial exception is not integrated into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B. Step 2B: The above claims comprise the following additional elements: In Claim 1: a computer-implemented method (preamble); processor; steps of obtain vibration data from at least one vehicle-embedded vibration sensor of a vehicle crossing the bridge and perform a predefined remediation action associated with the bridge; In Claim 8: a computer program product comprising one or more computer readable storage media having program instructions collectively stored on the one or more computer readable storage media (preamble); steps of obtain vibration data from at least one vehicle-embedded vibration sensor of a vehicle crossing the bridge and perform a predefined remediation action associated with the bridge; and In Claim 15: a system (preamble); and a computerized simulation validating system for a full-scale distribution network single phase-to-ground fault test (preamble); steps of obtain vibration data from at least one vehicle-embedded vibration sensor of a vehicle crossing the bridge and perform a predefined remediation action associated with the bridge. The additional elements such as a processor, computer-implemented method, a computer program product comprising one or more computer readable storage media having program instructions collectively stored on the one or more computer readable storage media processor, bridge are recited at a high-level of generality (MPEP 2106.05(d)). Further, note that the step of “obtain vibration data from at least one vehicle-embedded vibration sensor of a vehicle crossing the bridge” is insignificant (gathering data) extra-solution activity (MPEP 2106.05(g)). The limitation of “at least one vehicle-embedded vibration sensor of a vehicle crossing the bridge” is merely a description (or definition) about obtained data. The step of “performing, by the processor set, a predefined remediation action is insignificant (post-solution) extra-solution activity (MPEP 2106.05(g)). Merely “notifying” a result (i.e., performing a predefined remediation action) is nothing more than outputting a signal or displaying result. There is established case law (electric power group for example) to prove that such a feature is insufficient extra solution activity (see MPEP 2106.05(g)). Therefore, none of the additional elements indicate a practical application. Further, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because these additional elements/steps are well-understood, routine, and conventional in the relevant based on the prior art of record (Dingli, Du (US 2023/0049919 A1)). For example, Dingli and Du teach at least one vehicle-embedded vibration sensor of a vehicle (paras. [0029], [0065] of Dingli; paras. [0007], [0024], [0027], [0029], [0032]-[0034], [0040] of Du). Therefore, independent claims 1, 8, and 15 are not patent eligible. Claims 3, 10, and 17, The additional elements of “the vehicle is classified based on type, make, and model of the vehicle” is well-understood, routine, and conventional in the relevant based on the prior art of record (para. [0026] of Dingli; page 3, line 20 of Fu (CN 115221327A)). Therefore, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because these additional elements/steps are well-understood, routine, and conventional in the relevant based on the prior art of record. Regarding claims 4, 6-8, 11, 13-15, 18, 20-21, and 26-27, All features recited in these claims are abstract ideas, as all features found in these claims are directed towards mathematical calculations or mathematical calculation/mental process steps. The explanation for the rejection of Claims 4, 6-8, 11, 13-15, 18, 20-21, and 26-27 therefore are incorporated herein and applied to Claims 1, 8, and 15. These claims therefore stand rejected for similar reasons as explained in above Claims 1, 8, and 15. Claim Rejections - 35 USC § 103 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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 1, 3-4, 6-8, 10-11, 13-15, 17-18, 20-21, and 26 are rejected under 35 U.S.C. 103 as being unpatentable over Dingli et al. (US 2021/0134088 A1, hereinafter referred to as “Dingli”) in view of Bohannan et al. (US 4,956,999, hereinafter referred to as “Bohannan”) and Codevilla et al. (US 2020/0159231 A1, hereinafter referred to as “Codevilla”). Regarding claim 1, Dingli teaches a computer-implemented method (para. [0006]: non-transitory computer readable media; para. [0008]: a computer program product), comprising: determining, by a processor set (para. [0065]: one or more hardware processors), different baseline vibration patterns of a road segment (para. [0023]: a vehicle (e.g., an autonomous vehicle, a driverless vehicle, etc); Fig. 1 and para. [0029]: a vibrational signature for a vehicle and a baseline vibrational signature for a road segment along which the vehicle is travelling may be compared to determine if the vehicle is exhibiting anomalous vibrational characteristics that are outside of the range of expected vibrational behavior of the vehicle on that particular road segment, note that the above feature of “a vehicle (e.g., an autonomous vehicle, a driverless vehicle, etc.)” in para. [0023] and “a vibrational signature for a vehicle and a baseline vibrational signature for a road segment” and “particular road segment” in para. [0029] reads on “different baseline vibration patterns of a road segment) for vehicle categories (para. [0023]: a vehicle (e.g., an autonomous vehicle, a driverless vehicle, etc); para. [0029] the real-time sensor data is indicative of vibrational characteristics of the vehicle as it travels along a particular road segment, note that the above feature of “a vehicle (e.g., an autonomous vehicle, a driverless vehicle),” in para. [0023] and “vibrational characteristics of the vehicle as it travels along a particular road segment” in para. [0029] reads on “vehicle categories”) based on vibration data collected from one or more vehicle-embedded vibration sensors of plural vehicles (Fig. 2, 206A-C ) in the respective vehicle categories (para. [0023]: see above; para. [0029]: see above); obtaining, by the processor set (para. [0065]: one or more hardware processors), vibration data from at least one vehicle-embedded vibration sensor of a vehicle (Fig. 2, 206A-C) crossing the road segment (para. [0029]: a vibrational signature for a vehicle and a baseline vibrational signature for a road segment along which the vehicle is travelling may be compared to determine if the vehicle is exhibiting anomalous vibrational characteristics that are outside of the range of expected vibrational behavior of the vehicle on that particular road segment, note that the above feature of “a vibrational signature for a vehicle and a baseline vibrational signature for a road segment along which the vehicle is travelling” and “particular road segment” reads on “vibration data from a vehicle crossing the bridge” and “bridge,” respectively); classifying, by the processor set (para. [0065]: one or more hardware processors), the vehicle into a respective one of the vehicle categories (para. [0023]: a vehicle (e.g., an autonomous vehicle, a driverless vehicle, etc); para. [0029]: the real-time sensor data is indicative of vibrational characteristics of the vehicle as it travels along a particular road segment, note that since Dingli teaches vehicle categories in para. -0023) and the real-time sensor data is indicative of vibrational characteristics of the vehicle in para. [0029], classifying the vehicle into a respective one of the vehicle categories is inherent functional property of such result); selecting, by the processor set (para. [0065]: one or more hardware processors), a respective one of the different baseline vibration patterns (para. [0029]: a baseline vibrational signature for a road segment; para. [0038]: The vibrational data 114 may include multiple baseline vibrational signatures, each of which corresponds to a respective road segment represented in the map data 112, note that the above feature of “multiple baseline vibrational signatures, each of which corresponds to a respective road segment” reads on “a respective one of the baseline vibration patterns”) based on the respective one of the vehicle categories (para. [0029]: the real-time sensor data is indicative of vibrational characteristics of the vehicle as it travels along a particular road segment); determining, by the processor set (para. [0065]: one or more hardware processors), a difference between the vibration data collected from the vehicle and the respective one of the different baseline vibration patterns (para. [0029]: a vibrational signature for a vehicle and a baseline vibrational signature for a road segment along which the vehicle is travelling may be compared to determine if the vehicle is exhibiting anomalous vibrational characteristics that are outside of the range of expected vibrational behavior of the vehicle on that particular road segment, note that the above feature of “anomalous vibrational characteristics” reads on “a difference between the vibration data collected from the vehicle and the respective one of the baseline vibration patterns”); and in response to the difference exceeding a predefined threshold (para. [0029]: anomalous vibrational characteristics; para. [0030]: vibrational signature for the vehicle deviates from the baseline vibrational signature for the road segment by more than a threshold amount), performing, by the processor set (para. [0065]: one or more hardware processors), a predefined remediation action (para. [0030]: it is determined that the vibrational signature for the vehicle deviates from the baseline vibrational signature for the road segment by more than a threshold amount—and thus that the vehicle is exhibiting anomalous vibrational behavior in relation to the particular road segment it is traveling on—an automated vibrational anomaly alert may be generated) associated with the road segment (para. [0029]: a vibrational signature for a vehicle and a baseline vibrational signature for a road segment along which the vehicle is travelling may be compared to determine if the vehicle is exhibiting anomalous vibrational characteristics that are outside of the range of expected vibrational behavior of the vehicle on that particular road segment). Dingli does not specifically teach vibration patterns of a bridge for different vehicle and bridge. However, Bohannan teaches the vibration patterns (col. 9, lines 21-22; the vibrations associated with the motion of the structural member being monitored) of a bridge for different vehicle (col. 7, lines 41-47: in the context of structural members that are bridge span support beams, the transient loads may be vehicles traveling the longitudinal length of the span, for example, cars, trucks, and busses of different sizes and weights) and bridge (col. 7, lines 41-47: bridge). Dingli and Bohannan are both considered to be analogous to the claimed invention because they are in the same filed of monitoring the status of vehicle. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the vibration patterns of a bridge for different vehicle such as is described in Bohannan into Dingli, in order to monitor structural members subjected to transient loads over time to identify and/or measure changes in the structural integrity of the structural member (Bohannan, col. 5, lines 16-20). Dingli and Bohannan do not specifically teach filtering, by the processor set, the vibration data obtained from the vehicle to eliminate vibration data according to a context including a predetermined factor of disinterest. However, Codevilla teaches filtering, by the processor set, the vibration data obtained from the vehicle to eliminate vibration data according to a context including a predetermined factor of disinterest (para. [0018]: Sensors 108 may include, by way of non-limiting example: a vibration sensor; para. [0028]: Filtering component 116 may be configured to filter the contextual information spatially… contextual information may be filtered on a higher level such that some contextual information is ignored and some contextual information is acknowledged; para. [0030]: filtering component 116 may be configured to filter the contextual information spatially such that specific contextual information of the contextual information is determined, note that the above feature of “a vibration sensor” in para. [0018], “filter the contextual information spatially… contextual information may be filtered on a higher level such that some contextual information is ignored and some contextual information is acknowledged” in para. [0028], and “specific contextual information of the contextual information is determined” in para. [0030] reads on “filtering, by the processor set, the vibration data obtained from the vehicle to eliminate vibration data according to a context including a predetermined factor of disinterest”). Dingli and Codevilla are both considered to be analogous to the claimed invention because they are in the same filed of controlling a vehicle with context. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the filtering the vibration data such as is described in Codevilla into Dingli, in order to generate output signals conveying contextual information and vehicle information. The contextual information may characterize a contextual environment surrounding a vehicle. The vehicle information may characterize vehicle operations of the vehicle (Codevilla, para. [0004]). Regarding claim 2, Dingli in view of Bohannan and Codevilla teaches all the limitation of claim 1, in addition, Dingli teaches that the vibration data is collected by at least one sensor installed on the vehicle (para. [0026]: sensor data captured by various on-board vehicle sensors may be indicative of vibrational characteristics of a vehicle as it travels along a road surface). Regarding claim 3, Dingli in view of Bohannan and Codevilla teaches all the limitation of claim 1. Dingli does not specifically teach that the vehicle is classified based on type, make, and model of the vehicle. However, Bohannan teaches the vehicle is classified based on type, make, and model of the vehicle (col. 7, lines 41-47: in the context of structural members that are bridge span support beams, the transient loads may be vehicles traveling the longitudinal length of the span, for example, cars, trucks, and busses of different sizes and weights, note that the above feature of “cars, trucks, and busses of different sizes and weights” in col. 7, lines 41-47 reads on “ “the vehicle is classified based on type, make, and model of the vehicle”). Dingli and Bohannan are both considered to be analogous to the claimed invention because they are in the same filed of monitoring structural members. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the vehicle such as is described in Bohannan into Dingli, in order to monitor structural members subjected to transient loads over time to identify and/or measure changes in the structural integrity of the structural member (Bohannan, col. 5, lines 16-20). Regarding claim 4, Dingli in view of Bohannan and Codevilla teaches all the limitation of claim 1, in addition, Dingli teaches that the different baseline vibration patterns are determined using vibration data from plural vehicles passing over the road segment prior to obtaining the vibration data of the vehicle crossing the bridge (para. [0023]: a vehicle (e.g., an autonomous vehicle, a driverless vehicle, etc); para. [0028]: the baseline vibrational signature for a road segment may be indicative of a cumulative or an average level of vibration caused by defects, impediments, obstructions, and/or overall road surface quality of the road segment, as reflected by the vibrational characteristics of multiple vehicles traversing the road segment, note that the above feature of “a vehicle (e.g., an autonomous vehicle, a driverless vehicle, etc)” in para. [0023] and “the baseline vibrational signature for a road segment” in para. [0028] reads on “different baseline vibration patterns are determined using vibration data from plural vehicles passing over the road segment prior to obtaining the vibration data of the vehicle crossing the bridge”). Dingli and Codevilla do not specifically teach the bridge. However, Bohannan teaches the bridge (col. 7, lines 41-47: in the context of structural members that are bridge span support beams, the transient loads may be vehicles traveling the longitudinal length of the span, for example, cars, trucks, and busses of different sizes and weights). Dingli and Bohannan are both considered to be analogous to the claimed invention because they are in the same filed of monitoring structural members. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the bridge such as is described in Bohannan into Dingli, in order to monitor structural members subjected to transient loads over time to identify and/or measure changes in the structural integrity of the structural member (Bohannan, col. 5, lines 16-20). Regarding claim 5, Dingli in view of Bohannan and Codevilla teaches all the limitation of claim 4, in addition, Dingli teaches further comprising filtering the vibration data from the plural vehicles based on context (para. [0041]: the context module 214 may receive the respective vibrational data 208A, 208B, 208C from each of the plurality of vehicles 206A, 206B, 206C via the network(s) 210, which may include any combination of public and/or private networks; para. [0042] aggregating the vibrational data 208A, 208B, 208C may include, without limitation, sensor data fusion, data interpolation, data redundancy elimination, or any other form of data aggregation or manipulation, note that the above feature of “data redundancy elimination, or any other form of data aggregation or manipulation” reads on “filtering the vibration data from the plural vehicles based on context”). Regarding claim 6, Dingli in view of Bohannan and Codevilla teaches all the limitation of claim 1, in addition, Dingli teaches that the predefined remediation action is selected from a set of plural different predefined remediation actions using a decision tree and based on an amount of the difference (para. [0030]: it is determined that the vibrational signature for the vehicle deviates from the baseline vibrational signature for the road segment by more than a threshold amount—and thus that the vehicle is exhibiting anomalous vibrational behavior in relation to the particular road segment it is traveling on—an automated vibrational anomaly alert may be generated, various responses may then be initiated in response to the vibrational anomaly alert, note that the above feature of “an automated vibrational anomaly alert may be generated, various responses may then be initiated in response to the vibrational anomaly alert” reads on “the predefined remediation action is selected from a set of plural different predefined remediation actions using a decision tree and based on an amount of the difference”). Regarding claim 7, Dingli in view of Bohannan and Codevilla teaches all the limitation of claim 1, in addition, Dingli teaches that the predefined threshold is based on environmental impacts or location impacts associated with the road segment (para. [0030]: it is determined that the vibrational signature for the vehicle deviates from the baseline vibrational signature for the road segment by more than a threshold amount—and thus that the vehicle is exhibiting anomalous vibrational behavior in relation to the particular road segment it is traveling on, note that the above feature of “exhibiting anomalous vibrational behavior in relation to the particular road segment it is traveling on” reads on “environmental impacts or location impacts associated with the road segment”). Dingli and Codevilla do not specifically teach the bridge. However, Bohannan teaches the bridge (col. 7, lines 41-47: in the context of structural members that are bridge span support beams, the transient loads may be vehicles traveling the longitudinal length of the span, for example, cars, trucks, and busses of different sizes and weights). Dingli and Bohannan are both considered to be analogous to the claimed invention because they are in the same filed of monitoring structural members. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the bridge such as is described in Bohannan into Dingli, in order to monitor structural members subjected to transient loads over time to identify and/or measure changes in the structural integrity of the structural member (Bohannan, col. 5, lines 16-20). Regarding claim 26, Dingli in view of Bohannan and Codevilla teaches all the limitation of claim 1, Dingli does not specifically teach that the predetermined factor of disinterest is selected from the group consisting of weather information and presence of another vehicle on the roadway. However, Codevilla teaches the predetermined factor of disinterest (para. [0028]: some contextual information is ignored and some contextual information is acknowledged; para. [0030]: filtering component 116 may be configured to filter the contextual information spatially such that specific contextual information of the contextual information is determined) is selected from the group consisting of weather information (para. [0017]: Ambient conditions may include rain, hail, snow, fog, and/or other naturally occurring conditions) and presence of another vehicle (Fig. 5, 502 ) on the roadway (Fig. 5, 522). Dingli and Codevilla are both considered to be analogous to the claimed invention because they are in the same filed of controlling a vehicle with context. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the predetermined factor of disinterest such as is described in Codevilla into Dingli, in order to generate output signals conveying contextual information and vehicle information. The contextual information may characterize a contextual environment surrounding a vehicle. The vehicle information may characterize vehicle operations of the vehicle (Codevilla, para. [0004]). Dingli and Codevilla do not specifically teach that the roadway is bridge. However, Bohannan teaches that the roadway is bridge (col. 7, lines 41-47: in the context of structural members that are bridge span support beams, the transient loads may be vehicles traveling the longitudinal length of the span, for example, cars, trucks, and busses of different sizes and weights). Dingli and Bohannan are both considered to be analogous to the claimed invention because they are in the same filed of monitoring structural members. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the bridge such as is described in Bohannan into Dingli, in order to monitor structural members subjected to transient loads over time to identify and/or measure changes in the structural integrity of the structural member (Bohannan, col. 5, lines 16-20). Regarding claim 27, Dingli in view of Bohannan and Codevilla teaches all the limitation of claim 1, in addition, Codevilla teaches that filtering the vibration data comprises filtering noisy data (para. [0018]: Sensors 108 may include, by way of non-limiting example: a vibration sensor; para. [0028]: Filtering component 116 may be configured to filter the contextual information spatially… contextual information may be filtered on a higher level such that some contextual information is ignored and some contextual information is acknowledged; para. [0030]: filtering component 116 may be configured to filter the contextual information spatially such that specific contextual information of the contextual information is determined, note that the above feature of “a vibration sensor” in para. [0018], “filter the contextual information spatially… contextual information may be filtered on a higher level such that some contextual information is ignored and some contextual information is acknowledged” in para. [0028], and “specific contextual information of the contextual information is determined” in para. [0030] reads on “filtering the vibration data comprises filtering noisy data” because other information except specific information (or ignored information) is noise data). Dingli and Codevilla are both considered to be analogous to the claimed invention because they are in the same filed of controlling a vehicle with context. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the filtering the vibration data such as is described in Codevilla into Dingli, in order to generate output signals conveying contextual information and vehicle information. The contextual information may characterize a contextual environment surrounding a vehicle. The vehicle information may characterize vehicle operations of the vehicle (Codevilla, para. [0004]). Regarding claim 8, it is a computer program product or computer readable storage media type claim having similar limitations as for claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above. Regarding claim 10, it is dependent claim on claim 8 and has similar limitations as of claim 3 above. Therefore, it is rejected under the same rationale as of claim 3 above. Regarding claim 11, it is dependent claim on claim 8 and has similar limitations as of claim 4 above. Therefore, it is rejected under the same rationale as of claim 4 above. Regarding claim 13, it is dependent claim on claim 8 and has similar limitations as of claim 6 above. Therefore, it is rejected under the same rationale as of claim 6 above. Regarding claim 14, it is dependent claim on claim 8 and has similar limitations as of claim 7 above. Therefore, it is rejected under the same rationale as of claim 7 above. Regarding claim 15, it is a system type claim having similar limitations as for claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above. Regarding claim 17, it is dependent claim on claim 15 and has similar limitations as of claim 3 above. Therefore, it is rejected under the same rationale as of claim 3 above. Regarding claim 18, it is dependent claim on claim 15 and has similar limitations as of claim 4 above. Therefore, it is rejected under the same rationale as of claim 4 above. Regarding claim 20, it is dependent claim on claim 15 and has similar limitations as of claim 6 above. Therefore, it is rejected under the same rationale as of claim 6 above. Regarding claim 21, it is dependent claim on claim 15 and has similar limitations as of claim 7 above. Therefore, it is rejected under the same rationale as of claim 7 above. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to SANGKYUNG LEE whose telephone number is (571)272-3669. The examiner can normally be reached Monday-Friday 8:30am-5:00pm. 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, LEE RODAK can be reached at 571-270-5618. 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. /SANGKYUNG LEE/Examiner, Art Unit 2858 /LEE E RODAK/Supervisory Patent Examiner, Art Unit 2858
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Prosecution Timeline

Jun 29, 2023
Application Filed
Dec 11, 2025
Non-Final Rejection — §101, §103
Feb 03, 2026
Applicant Interview (Telephonic)
Feb 03, 2026
Examiner Interview Summary
Mar 12, 2026
Response Filed
Mar 25, 2026
Final Rejection — §101, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
61%
Grant Probability
66%
With Interview (+4.6%)
2y 8m
Median Time to Grant
Moderate
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