Prosecution Insights
Last updated: April 19, 2026
Application No. 18/042,536

SENSOR TO SENSOR EDGE TRAFFIC INFERENCE, SYSTEM AND METHOD

Non-Final OA §101§102§103§112
Filed
Feb 22, 2023
Examiner
KUHFUSS, ZACHARY L
Art Unit
3615
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Konux GmbH
OA Round
1 (Non-Final)
78%
Grant Probability
Favorable
1-2
OA Rounds
2y 10m
To Grant
96%
With Interview

Examiner Intelligence

Grants 78% — above average
78%
Career Allow Rate
829 granted / 1065 resolved
+25.8% vs TC avg
Strong +18% interview lift
Without
With
+18.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
37 currently pending
Career history
1102
Total Applications
across all art units

Statute-Specific Performance

§101
0.9%
-39.1% vs TC avg
§103
48.6%
+8.6% vs TC avg
§102
28.5%
-11.5% vs TC avg
§112
15.0%
-25.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1065 resolved cases

Office Action

§101 §102 §103 §112
DETAILED ACTION Claim Objections Claims 2, 10, 12, and 13 are objected to because of the following informalities: Regarding claim 2, there is no period at the end of the claim. Regarding claim 10, in line 4, the term “used data” should be changed to “user data”. Regarding claim 12, in lines 10-11, the term “senor node” should be changed to “sensor node”. Regarding claim 13, in line 4, the phrase “infrastructure the at a first position” should be changed to “infrastructure . Appropriate correction is required. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 11, 12 and 14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. In claim 11, the last line, the phrase "preferably" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d). In claim 12, line 2, the phrase “the at least one sensor installing data” lacks proper antecedent basis. Please amend claim 12 to depend from claim 10 in order to provide proper antecedent basis. In claim 14, lines 2-3, the phrase “the at least one unmonitored railway infrastructure ” lacks proper antecedent basis. Please amend claim 14 to depend from claim 8 in order to provide proper antecedent basis. 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. Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The determination of whether a claim recites patent ineligible subject matter is a 2 step inquiry. STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), see MPEP 2106.03, or STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis: see MPEP 2106.04 STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon? see MPEP 2106.04(II)(A)(1) STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? see MPEP 2106.04(II)(A)(2) STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? see MPEP 2106.05 Regarding the system for monitoring a railway network infrastructure, as recited in claims 1-5, the following 101 analysis applies. 101 Analysis – Step 1 Claim 1 is directed to a system for monitoring a railway network infrastructure (i.e., a machine). Therefore, claim 1 is within at least one of the four statutory categories. 101 Analysis – Step 2A, Prong I Regarding Prong I of the Step 2A analysis, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. see MPEP 2106(A)(II)(1) and MPEP 2106.04(a)-(c) Independent claim 1 includes limitations that recite an abstract idea (emphasized below [with the category of abstract idea in brackets]) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites: A system for monitoring a railway network infrastructure, the system comprising at least one sensor node configured to obtain at least one sensor data; at least one processing component configured to process the at least one sensor data, and generate at least one processed sensor data; at least one analyzing component configured to generate at least one railway network infrastructure hypothesis [mental process/step] based on at least one of the at least one sensor data, and the at least one processed sensor data. The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, the ability to generate a hypothesis in the context of this claim encompasses a person (driver) looking at data collected and forming a simple testable inference. Accordingly, the claim recites at least one abstract idea. 101 Analysis – Step 2A, Prong II Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. see MPEP 2106.04(II)(A)(2) and MPEP 2106.04(d)(2). It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” [with a description of the additional limitations in brackets], while the bolded portions continue to represent the “abstract idea”.): A system for monitoring a railway network infrastructure, the system comprising at least one sensor node configured to obtain at least one sensor data [pre-solution activity (data gathering) using generic sensors]; at least one processing component configured to [pre-solution activity (data gathering) using a generic computing module] process the at least one sensor data [pre-solution activity (data gathering)], and generate at least one processed sensor data [pre-solution activity (data gathering)]; at least one analyzing component configured to [applying the abstract idea using generic computing module] generate at least one railway network infrastructure hypothesis [mental process/step] based on at least one of the at least one sensor data, and the at least one processed sensor data. For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application. Regarding the additional limitations of “at least one sensor node…,” “at least one processing component…,” “process…,” “generate…,”and “analyzing component…,” the examiner submits that these limitations are insignificant extra-solution activities that merely use generic computer components such as sensors and processors to perform the hypothesis generating step. In particular, the obtain, process, generate and analyzing steps from the sensors and from the processing/analyzing component are recited at a high level of generality (i.e. as a general means of gathering railway network infrastructure data for use in the hypothesis generating step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Lastly, the “processing component” and “analyzing component” are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of processing and analyzing data in no particular manner) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use 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 not more than a drafting effort designed to monopolize the exception. See MPEP § 2106.05. The claims are recited in such a generic manner that there is no indication of what is being sensed relative to the railway infrastructure or how that data is being processed or analyzed. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. 101 Analysis – Step 2B Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor/analyzer to perform the hypothesis generating step amounts to nothing 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. And as discussed above, the additional limitations of “at least one sensor node…,” “at least one processing component…,” “process…,” “generate…,”and “analyzing component…,” the examiner submits that these limitations are insignificant extra-solution activities. In addition, these additional limitations (and the combination, thereof) amount to no more than what is well-understood, routine and conventional activity. Hence, claim 1 is not patent eligible. Dependent claim(s) 2-5 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. For example, claim 2 recites retrieving user data [pre-solution activity (data gathering)], claim 3 recites a server with storage and a base station with machine learning architecture [applying the abstract idea using a generic computing module and using well-understood components of the technical field], claim 4 recites an analyzer retrieving data from a processor [pre-solution activity (data gathering)], claim 5 recites retrieving, exchanging, and aggregating data at a very high level of generality [pre-solution activity (data gathering)] using a sensor, base station, processor and a user device [generic computing modules and well-understood components of the technical field]. Therefore, dependent claims 2-5 are not patent eligible under the same rationale as provided for in the rejection of claim 1. Therefore, claim(s) 1-5 is/are ineligible under 35 USC §101. Regarding the method for monitoring a railway network infrastructure, as recited in claims 6-16, the following 101 analysis applies. 101 Analysis – Step 1 Claim 6 is directed to a method for monitoring a railway network infrastructure (i.e., a process). Therefore, claim 6 is within at least one of the four statutory categories. 101 Analysis – Step 2A, Prong I Regarding Prong I of the Step 2A analysis, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. see MPEP 2106(A)(II)(1) and MPEP 2106.04(a)-(c) Independent claim 1 includes limitations that recite an abstract idea (emphasized below [with the category of abstract idea in brackets]) and will be used as a representative claim for the remainder of the 101 rejection. Claim 6 recites: A method for monitoring a railway network infrastructure, the method comprising obtaining at least one sensor data from at least one sensor node; processing the at least sensor data to generate at least one processed sensor data; and generating at least one railway infrastructure hypothesis [mental process/step] comprising at least one data related to the railway network infrastructure, wherein the at least one railway infrastructure hypothesis is based on at least one of the at least one sensor data, and the at least one processed sensor data. The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, the ability to generate a hypothesis in the context of this claim encompasses a person (driver) looking at data collected and forming a simple testable inference. Accordingly, the claim recites at least one abstract idea. 101 Analysis – Step 2A, Prong II Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. see MPEP 2106.04(II)(A)(2) and MPEP 2106.04(d)(2). It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” [with a description of the additional limitations in brackets], while the bolded portions continue to represent the “abstract idea”.): A method for monitoring a railway network infrastructure, the method comprising obtaining at least one sensor data from at least one sensor node [pre-solution activity (data gathering) using generic sensors]; processing the at least sensor data to generate at least one processed sensor data [pre-solution activity (data gathering) using a generic computing module] ; and generating at least one railway infrastructure hypothesis [mental process/step] comprising at least one data related to the railway network infrastructure, wherein the at least one railway infrastructure hypothesis is based on at least one of the at least one sensor data, and the at least one processed sensor data. For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application. Regarding the additional limitations of “obtaining…,” and “processing…,” the examiner submits that these limitations are insignificant extra-solution activities that merely use generic computer components such as sensors and processors to perform the hypothesis generating step. In particular, the obtaining and processing steps are recited at a high level of generality (i.e. as a general means of gathering railway network infrastructure data for use in the hypothesis generating step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Further, the “obtaining” and “processing” is recited at a high-level of generality (i.e., as a generic sensor obtaining data and processing said data in no particular manner) such that it amounts no more than mere instructions to apply the exception using generic computer and sensor components. Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use 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 not more than a drafting effort designed to monopolize the exception. See MPEP § 2106.05. The claims are recited in such a generic manner that there is no indication of what is being sensed relative to the railway infrastructure or how that data is being processed or analyzed. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. 101 Analysis – Step 2B Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of processing data before performing the hypothesis generating step amounts to nothing more than mere instructions to apply the exception using a generic computer component, i.e., processor. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “obtaining…,” and “processing…,” the examiner submits that these limitations are insignificant extra-solution activities. In addition, these additional limitations (and the combination, thereof) amount to no more than what is well-understood, routine and conventional activity. Hence, claim 6 is not patent eligible. Dependent claim(s) 7-11 and 13-16 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. For example, claim 7 recites obtaining sensor data using first and second sensors at first and second positions [pre-solution activity (data gathering)], claim 8 recites predicting a finding based on the hypothesis that comprises tonnage data, train count data or axel count data [generally linking the use of the abstract idea to a particular technological field], claim 9 recites a switch and a track segment and automatically retrieving data to be aggregated to generate a dataset [pre-solution activity (data gathering) and generally linking the use of the abstract idea to a particular technological field], claim 10 recites bidirectionally communicating between infrastructure components [pre-solution activity (data gathering)] using a sensor, base station, and a user device [generic computing modules and well-understood components of the technical field], claim 11 recites teaching a neural network according to the gathered data [mere instructions to implement an abstract idea using a neural network] and labelling the data [post-solution activity (data gathering)], claim 13 recites outputting a difference finding between first and n-th sensor data [pre-solution activity (data gathering) and generally linking the use of the abstract idea to a particular technological field], claim 14 recites predicting a finding based on the difference of claim 13 [generally linking the use of the abstract idea to a particular technological field], claims 15 and 16 recite aggregating data and inferring a finding based on that data [pre-solution activity (data gathering) and generally linking the use of the abstract idea to a particular technological field]. Therefore, dependent claims 7-11 and 13-16 are not patent eligible under the same rationale as provided for in the rejection of claim 6. Therefore, claim(s) 6-11 and 13-16 is/are ineligible under 35 USC §101. 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 . 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 (i.e., changing from AIA to pre-AIA ) 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. Claim Rejections - 35 USC § 102 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. Claim(s) 1, 2, 4, 6-8, 10 and 13-16 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Mian (US 2009/0326746 A1). Referring to Claim 1: Mian discloses a system for monitoring a railway network infrastructure, the system comprising at least one sensor node (10A-10E) configured to obtain at least one sensor data (Para. [0018]) (Fig. 1B); at least one processing component (20 or 64) (Fig. 1B or Fig. 4B) configured to process the at least one sensor data (Para. [0022] or [0042]), and generate at least one processed sensor data (Para. [0022] or [0042]); at least one analyzing component (62A-62E or 72) configured to generate at least one railway network infrastructure hypothesis based on at least one of the at least one sensor data, and the at least one processed sensor data (Para. [0037-0038] or [0046]). Referring to Claim 2: Mian discloses the system according to claim 1, wherein the at least one processing component (72) is configured to retrieve at least one user data from at least one user device (76) configured to be in a proximity of the at least one sensor node (10A-10F) (Para. [0046]) (Fig. 4B). Referring to Claim 4: Mian discloses the system according to claim 1, wherein the at least one analyzing component (62A-62E or 72) is configured to retrieve sensor data from the at least one processing component (20) (Para. [0037] or [0046]). Referring to Claim 6: Mian discloses a method for monitoring a railway network infrastructure, the method comprising obtaining at least one sensor data from at least one sensor node (10A-10E) (Para. [0018] or [0042]) (Fig. 1B, 4A or 4B); processing the at least sensor data to generate at least one processed sensor data (Para. [0022] or [0042]); and generating at least one railway infrastructure hypothesis comprising at least one data related to the railway network infrastructure (Para. [0043]), wherein the at least one railway infrastructure hypothesis is based on at least one of the at least one sensor data, and the at least one processed sensor data (Para. [0037-0038] or [0046]). Referring to Claim 7: Mian discloses the method according to claim 6, wherein obtaining the at least one sensor data from the at least one sensor node (10A-10E) comprises obtaining at least one first sensor data from at least one first sensor node (10A) arranged on the railway network infrastructure at a first position (Fig. 4A), and obtaining at least one second sensor data from at least one second sensor node (10B) on the railway network infrastructure at a second position (Fig. 4A); and processing the at least one sensor data comprises processing at least one of the at least one first sensor data, and the at least second sensor data (Para. [0034-0037]). Referring to Claim 8: Mian discloses the method according to claim 8, wherein the method comprises predicting at least one finding (e.g., “rail 2A, 2B is under sufficient stress or in sufficiently poor condition to be in imminent danger of breaking”) for at least one unmonitored railway network infrastructure (Para. [0038]), wherein the at least one finding is based on the at least one railway infrastructure hypothesis (Para. [0043]); and comprises at least one of tonnage data, train count data, and axel count data (“wheel 4 passage”, Para. [0021]). Referring to Claim 10: Mian discloses the system according to claim 6, wherein the method comprises generating at least one sensor installing data (Para. [0040]); retrieving at least one used data from at least one user device (76); establishing a bidirectionally communication with at least one server (62) comprising at least one storage component (74); establishing a bidirectional communication with at least one base station (70); exchanging data between the at least one base station (70) and the at least one sensor node (10); and exchanging data between the at least one user device (76) and the at least one base station (70) (Para. [0046]) (Fig. 4B). Referring to Claim 13: Mian discloses the method according to claim 6, wherein the method comprises obtaining the at least one first sensor data from the at least one first sensor node (10A) arranged on the railway network infrastructure the at a first position (Fig. 4A); processing the at least one first sensor data (Para. [0036]); obtaining at least one n-th sensor data from at least one n-th sensor node (10B-10F) arranged on the railway network infrastructure at n-th position (Fig. 4A); processing the at least one n-th sensor data (Para. [0036]); generating a railway network infrastructure data difference finding (e.g., poor rail condition), wherein the data difference finding is based on at least one parameter difference between the at least one first sensor data and the n-th sensor data; and outputting at least one interpreted railway network infrastructure data difference finding, wherein the interpreted railway network infrastructure data is based on the railway network infrastructure data difference finding (“Similarly, sensor nodes 10A-F can detect when a rail 2A, 2B is under sufficient stress or in sufficiently poor condition to be in imminent danger of breaking”) (Para. [0038]). Referring to Claim 14: Mian discloses the method according to claim 13, wherein the method comprises predicting the at least one finding for the at least one unmonitored railway infrastructure using the at least one railway infrastructure based on the at least one interpreted railway network infrastructure data difference finding (Para. [0038]). Referring to Claim 15: Mian discloses the method according to claim 6, wherein the method comprises automatically aggregating at least one sensor data between at least two sensor nodes (10A, 10B) (Para. [0042]); generating at least one aggregated sensor data based on the at least one sensor data between the at least two sensor nodes (Para. [0043]); and inferring the at least one finding based on the at least one aggregated sensor data (Para. [0046]). Referring to Claim 16: Mian discloses the method according to claim 13, wherein the method comprises automatically aggregating at least one sensor data between at least two sensor nodes (10A, 10B) (Para. [0042]); generating at least one aggregated sensor data based on the at least one sensor data between the at least two sensor nodes (Para. [0043]); and inferring the at least one finding based on the at least one aggregated sensor data (Para. [0046]). Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 3, 5 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mian in view of Samadani et al. (US 2019/0250069 A1). Referring to Claim 3: Mian teaches the system according to claim 1, wherein the system comprises at least one server (62) comprising at least one storage component (74) (Fig. 4B); and at least one base station (70) configured to exchange data with the at least one sensor node, wherein the at least one base station comprises software (Para. [0047-0048]) As indicated by strikethrough above, Mian does not specifically teach that the base station comprises a machine learning architecture. However, Samadani teaches a wheel health system (300) comprising a processor (310) connected to sensors (302, 304, 306), wherein “the vibration data, temperature data, speed data and weight data, or any combination thereof, may be processed by artificial intelligence (‘AI’) algorithms on board WHS 300 to identify problems in the early stages of the development. Such AI algorithms, in certain embodiments, can be implemented as machine learning models trained to recognize vibration patterns predictive of various failure modes.” (Para. [0064]) (see also Para. [0006-0007] and [0065-0069]) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, for Mian to use machine learning architecture at the base station, as taught by Samadani, in order to identify problems in the early stages of development using sensor data, and thereby prevent future failure of railway network infrastructure components with a reasonable expectation of success. Referring to Claim 5: Mian in view of Samadani, as applied to claim 3, further teaches the system wherein the at least one analyzing component (Mian, 72) is configured to retrieve raw user data from the at least one user device (76) (Para. [0046]) (Fig. 4B); retrieve the at least one processed sensor data from the at least one sensor node (10) (Para. [0042]); exchange data (via 78) with the at least one base station (70); and aggregate data (via 80) sourced by the at least two of: the at least one sensor node (10), the at least one base station (70), the at least one processing component (64), and the at least one user device (76) (Para. [0046]) (Fig. 4B). Referring to Claim 11: Mian does not specifically teach that the base station comprises a machine learning architecture and teaching and labelling the sensor data. However, Samadani teaches a wheel health system (300) comprising a processor (310) connected to sensors (302, 304, 306), wherein “the vibration data, temperature data, speed data and weight data, or any combination thereof, may be processed by artificial intelligence (‘AI’) algorithms on board WHS 300 to identify problems in the early stages of the development. Such AI algorithms, in certain embodiments, can be implemented as machine learning models trained to recognize vibration patterns predictive of various failure modes.” (Para. [0064]) (see also Para. [0006-0007] and [0065-0069]) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, for Mian to use machine learning architecture at the base station to teach and label data indicative of various failure modes, as taught by Samadani, in order to identify problems in the early stages of development using sensor data, and thereby prevent future failure of railway network infrastructure components with a reasonable expectation of success. Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mian in view of Hilleary (US 2017/0313331 A1). Referring to Claim 9: Mian further teaches the method according to claim 6, wherein at least one railway network infrastructure comprises at least one railway network infrastructure comprises at least one switch (Para. [0037] and [0039]); and at least one track segment (2A, 2B) (Fig. 4A), wherein the method comprises automatically retrieving at least one sensor data from at least one sensor processing component (64); aggregating data obtained by the at least two of the at least one sensor node with at least one data sourced from at least one of base station (70), processing component (64), and at least one input data (76) (Para. [0046]); and generating at least one aggregated dataset based on at least one of base station, processing component, and at least one input data (“railroad data 84, which can include and/or be generated from sensor data 21 (FIG. 1B) acquired by sensor node(s) 10”, Para. [0045]). Mian does not specifically teach using direction data. However, Hilleary teaches a railroad car location, speed, and heading detection system and method with self-powered wireless sensor nodes, wherein “detecting a railroad car location (i.e. physical presence), speed (i.e., velocity) and heading (i.e., direction of travel) is beneficial for safe, effective and productive railroad operations in a switchyard.” (Para. [0019]) (see also Para. [0054]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, for Mian to use direction data, as taught by Hilleary, in order to provide data beneficial for safe, effective and productive railroad operations in a switchyard with a reasonable expectation of success. Allowable Subject Matter Claim 12 is rejected in view of 35 USC § 112(b), but would be allowable if rewritten in independent form including all of the limitations of the base claims and if all claim objections and rejections in view of 35 USC § 112(b) are overcome. The following is a statement of reasons for the indication of allowable subject matter: Regarding claim 12, the prior art, including Mian, fails to teach the steps of generating at least one sensor activation data, as claimed. While Mian teaches, “The location of sensor node 10 can be selected based on the corresponding attribute(s) of the rail operation for which sensor node 10 is configured to acquire measurements” (Para. [0018]), Mian does not specifically teach generating the sensor activation data as claimed. Examiner finds that modifying Mian to meet the claimed limitations would require an improper degree of hindsight reasoning. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZACHARY L KUHFUSS whose telephone number is (571)270-7858. The examiner can normally be reached Monday - Friday 10:00am to 6:00 pm CDT. 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, Samuel (Joe) Morano can be reached on (571)272-6682. 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. /ZACHARY L KUHFUSS/Primary Examiner, Art Unit 3617
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Prosecution Timeline

Feb 22, 2023
Application Filed
Nov 13, 2025
Non-Final Rejection — §101, §102, §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

1-2
Expected OA Rounds
78%
Grant Probability
96%
With Interview (+18.0%)
2y 10m
Median Time to Grant
Low
PTA Risk
Based on 1065 resolved cases by this examiner. Grant probability derived from career allow rate.

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