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 .
Claim Objections
Claim 16-17 are objected to because of the following informalities: these claims currently depend on Claim 9, however, based on the context, they seem to depend on Claim 15. Claims 16-17 should recite: “The system of Claim [[9]] 15…” Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-8 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-8 of U.S. Patent No. 11,861,509. Although the claims at issue are not identical, they are not patentably distinct from each other because the instant application is a broader version of Patent 11,861,509’s inventive concept, which is directed to automatic analysis of railroad enforcement events, especially positive train control (PTC) brake events by gathering logs and messages from train systems and related servers, then filters out the information that matters most. Therefore, it is not patentably distinct from the Patent.
Claims 9-14 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 7-12 of U.S. Application No. 19,206,777. Although the claims at issue are not identical, they are not patentably distinct from each other because the instant application is a similar version of the application’s inventive concept, which is directed to a watchdog system configured to transmit and receive messages related to status monitoring or other suitable activity, to and from a client or server, and generate one or more elements for display on the client, wherein the elements provide additional information related to workflow automation in train events. Therefore, it is not patentably distinct from the Patent.
Claims 15-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-8 of U.S. Patent No. 11,541,919, claims 1-8 of U.S. Patent No. 11,897,527, and claims 1-10 of U.S. Patent No. 12,296,868. Although the claims at issue are not identical, they are not patentably distinct from each other because the instant application is a broader version of Patent 11,541,919’s inventive concept, and a similar version of Patents 11,897,527’s and12,296,868’s inventive concept, which is directed to analysis of train logs and extraction of the most relevant log details in order to determine the root cause of an event or, if no root cause is found, a higher-level classification. The system uses rules, regular expressions, data manipulation, and machine-learning models such as decision trees or clustering to create a synopsis of what happened, including speed, location, warnings, configuration, and PTC component data. Therefore, it is not patentably distinct from the Patent.
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 1-20 stand rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1 analysis:
In the instant case, the claims are directed to a systems. Thus, each of the claims falls within one of the four statutory categories (i.e., process, machine, manufacture, or composition of matter).
Step 2A analysis:
Based on the claims being determined to be within of the four categories (Step 1), it must be determined if the claims are directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), in this case the claims fall within the judicial exception of an abstract idea. Specifically the abstract ideas of Mental Processes- “Concepts performed in the human mind (including an observation, evaluation, judgment, opinion)”.
Step 2A: Prong 1 analysis:
Independent Claim 1 recites:
“a message identification module configured to classify the messages and the railroad enforcement event notifications via the processor”- this limitation corresponds to classifying messages, which under broadest reasonable amounts to observation and evaluation steps; being a mental process/abstract idea;
“an information parsing module configured to parse the messages and the railroad enforcement event notifications, via the processor, for information including at least one of a user ID, employee information on the train, an employee requesting the information, and a location of the train”- this limitation corresponds to parsing messages for information, which under broadest reasonable amounts to observing and evaluating steps; being a mental process/abstract idea.
Step 2A: Prong 2 analysis:
This judicial exception is not integrated into a practical application because it only recites these additional elements:
a memory storing files and logs related to one or more enforcement events– this memory is considered a generic computer component, as it is recited at a high level of generality such that it amounts no more than mere instructions to apply the judicial exception using a computer. The use of a computer or other machinery in its ordinary capacity amounts to invoking computers merely as a tool to perform an existing process (see MPEP 2106.05(f));
a processor operably coupled to the memory and capable of executing one or more modules or machine-readable instructions – this processor is considered a generic computer component, as it is recited at a high level of generality such that it amounts no more than mere instructions to apply the judicial exception using a computer. The use of a computer or other machinery in its ordinary capacity amounts to invoking computers merely as a tool to perform an existing process (see MPEP 2106.05(f));
a file collection module configured to send and receive messages regarding railroad enforcement event notifications - this limitation amounts to necessary data gathering and outputting, and this is considered a pre-solution activity (data gathering) and post-solution activity (data outputting), being an insignificant extra solution activity (see MPEP 2106.05(g));
a log collection module configured to receive system component logs from memory- this limitation amounts to necessary data gathering, and this is considered a pre-solution activity (data gathering), being an insignificant extra solution activity (see MPEP 2106.05(g)).
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. The claims are directed to an abstract idea.
Step 2B analysis:
The claim does 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 elements recited at Claim 1 above amount to generic computer components, and no more than insignificant extra solution activities.
Moreover, re-evaluation of the additional elements or combination of elements that were considered to be insignificant extra-solution activity at Claim 1 are needed to determine if they are considered well-understood, routine and conventional limitations:
“a file collection module configured to send and receive messages regarding railroad enforcement event notifications” - this limitation further amounts to receiving or transmitting dataset over a network, further considered well-understood, routine and conventional under MPEP 2106.05(d) II (i);
“a log collection module configured to receive system component logs from memory” - this limitation further amounts to receiving or transmitting dataset over a network, further considered well-understood, routine and conventional under MPEP 2106.05(d) II (i).
Dependent claims 2-7, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea. The claims are reciting further embellishment of the judicial exception.
Claim 2: this claim recites displaying information on a user device, and displaying data is one of the examples that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception (see 2106.05(h) (vi)- displaying the results of collection and analysis of data.
Claim 3: this claim recites notifications related to a railroad event, and this amounts to applying the judicial exception to the field of use of railroad operations (see MPEP 2106.05(h)).
Claim 4: this claim recites an event being a PTC brake event, and this amounts to applying the judicial exception to the field of use of railroad operations (see MPEP 2106.05(h)).
Claim 5: this claim recites further embellishment about the classification of messages and notifications, being evaluation steps, mental processes.
Claim 6: this claim recites further embellishment about the identification of a system log, being evaluation steps, mental processes.
Claim 7: this claim recites system logs from a CPU on board of a train, and this amounts to applying the judicial exception to the field of use of railroad operations (see MPEP 2106.05(h)).
Claim 8: this claim recites verifying if an event actually occurred based on characteristics, which recite further embellishment about the mental processes, being abstract ideas.
Independent Claim 9 recites:
“a log download module configured to query a service queue at a specified frequency and determine whether the service queue includes a new enforcement message related to an enforcement event”- this limitation corresponds to observing a service queue and evaluating if it includes a new message, which under broadest reasonable amounts to observation and evaluation steps; being a mental process/abstract idea;
“an automation initializing module configured to determine whether an automation service is executing on a designated server, and whether the automation service is executing based on network traffic on a designated IP address or network traffic on the designated server, and if the automation service is currently executing, execute an automation process”- this limitation corresponds to evaluating and judging is a service is executing on a server, which under broadest reasonable amounts to judging and evaluating steps; being a mental process/abstract idea.
Step 2A: Prong 2 analysis:
This judicial exception is not integrated into a practical application because it only recites these additional elements:
a memory storing files and logs related to one or more enforcement events – this memory is considered a generic computer component, as it is recited at a high level of generality such that it amounts no more than mere instructions to apply the judicial exception using a computer. The use of a computer or other machinery in its ordinary capacity amounts to invoking computers merely as a tool to perform an existing process (see MPEP 2106.05(f));
a processor operably coupled to the memory and capable of executing one or more modules or machine-readable instructions – this processor is considered a generic computer component, as it is recited at a high level of generality such that it amounts no more than mere instructions to apply the judicial exception using a computer. The use of a computer or other machinery in its ordinary capacity amounts to invoking computers merely as a tool to perform an existing process (see MPEP 2106.05(f));
an automation workflow module configured to receive processed events, including results from the automation process and a root cause of the enforcement event - this limitation amounts to necessary data gathering and outputting, and this is considered a pre-solution activity (data gathering) and post-solution activity (data outputting), being an insignificant extra solution activity (see MPEP 2106.05(g)).
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. The claims are directed to an abstract idea.
Step 2B analysis:
The claim does 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 elements recited at Claim 9 above amount to generic computer components, and no more than insignificant extra solution activities.
Moreover, re-evaluation of the additional elements or combination of elements that were considered to be insignificant extra-solution activity at Claim 9 are needed to determine if they are considered well-understood, routine and conventional limitations:
“an automation workflow module configured to receive processed events, including results from the automation process and a root cause of the enforcement event” - this limitation further amounts to receiving or transmitting dataset over a network, further considered well-understood, routine and conventional under MPEP 2106.05(d) II (i).
Dependent claims 10-14, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea. The claims are reciting further embellishment of the judicial exception.
Claim 10: this claim recites displaying information on a user device, and displaying data is one of the examples that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception (see 2106.05(h) (vi)- displaying the results of collection and analysis of data.
Claim 11: this claim recites notifications related to a railroad event, and this amounts to applying the judicial exception to the field of use of railroad operations (see MPEP 2106.05(h)).
Claim 12: this claim recites generating a record, which amounts to mere data manipulation, being insignificant extra solution activity under Prong 2; and electronic record keeping, being well understood routine and conventional under Step 2B.
Claim 13: this claim recites a collection of events included in a record, which amounts to mere data manipulation, being insignificant extra solution activity under Prong 2; and electronic record keeping, being well understood routine and conventional under Step 2B.
Claim 14: this claim recites parsing a file retrieval, which amounts to mere data gathering, insignificant extra solution activity under prong 2; and retrieving information in memory, being well understood routine and conventional under step 2B.
Independent Claim 15 recites:
“an extraction module configured to receive data corresponding to system component logs including characteristics of an enforcement event, extract the data, and determine whether the data is structured or unstructured”- this limitation corresponds to observing data including characteristics of it and determining its class, which under broadest reasonable amounts to observation and evaluation steps; being a mental process/abstract idea;
“an analysis module configured to analyze the extracted data via one or more models to determine a root cause and generate an analysis result, wherein one or more analysis thresholds determine whether a single analysis model or multiple analysis models are required”- this limitation corresponds to evaluating data to determine a root cause, which under broadest reasonable amounts to observing and evaluating steps; being a mental process/abstract idea;
“an event watch module configured to receive the analysis result from the analysis module and generate a high-level classification for the enforcement event and assign a unique ID to the analysis result, when the analysis result does not include the root cause”- this limitation corresponds to further evaluating data to determine a classification and assign IDs, which under broadest reasonable amounts to judging and evaluating steps; being a mental process/abstract idea.
Step 2A: Prong 2 analysis:
This judicial exception is not integrated into a practical application because it only recites these additional elements:
a memory storing files and logs related to one or more enforcement events– this memory is considered a generic computer component, as it is recited at a high level of generality such that it amounts no more than mere instructions to apply the judicial exception using a computer. The use of a computer or other machinery in its ordinary capacity amounts to invoking computers merely as a tool to perform an existing process (see MPEP 2106.05(f));
a processor operably coupled to the memory and capable of executing one or more modules or machine-readable instructions – this processor is considered a generic computer component, as it is recited at a high level of generality such that it amounts no more than mere instructions to apply the judicial exception using a computer. The use of a computer or other machinery in its ordinary capacity amounts to invoking computers merely as a tool to perform an existing process (see MPEP 2106.05(f));
an automation production module configured to transmit a detailed synopsis to a user - this limitation amounts to data outputting, and this is considered a post-solution activity (data outputting), being an insignificant extra solution activity (see MPEP 2106.05(g)).
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. The claims are directed to an abstract idea.
Step 2B analysis:
The claim does 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 elements recited at Claim 15 above amount to generic computer components, and no more than insignificant extra solution activities.
Moreover, re-evaluation of the additional elements or combination of elements that were considered to be insignificant extra-solution activity at Claim 15 are needed to determine if they are considered well-understood, routine and conventional limitations:
“an automation production module configured to transmit a detailed synopsis to a user” - this limitation further amounts to receiving or transmitting dataset over a network, further considered well-understood, routine and conventional under MPEP 2106.05(d) II (i).
Dependent claims 16-20, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea. The claims are reciting further embellishment of the judicial exception.
Claim 16: this claim recites displaying information on a user device, and displaying data is one of the examples that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception (see 2106.05(h) (vi)- displaying the results of collection and analysis of data.
Claim 17: this claim recites notifications related to a railroad event, and this amounts to applying the judicial exception to the field of use of railroad operations (see MPEP 2106.05(h)).
Claim 18: this claim recites collecting data points, which amounts to mere data gathering, insignificant extra solution activity under prong 2; receiving or transmitting dataset over a network, further considered well-understood, routine and conventional under Step 2B.
Claim 19: this claim recites collecting data points regarding time windows, which amounts to mere data gathering, insignificant extra solution activity under prong 2; receiving or transmitting dataset over a network, further considered well-understood, routine and conventional under Step 2B.
Claim 20: this claim recites evaluation and judgment steps for comparing and verifying an event occurred, being mental processes.
Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 (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.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-7 are rejected under 35 U.S.C. 103 as being unpatentable over Akif et al (US PG Pub. 2022/0194446- hereinafter Akif).
Referring to Claim 1, Akif teaches a file retrieval management system configured to retrieve and modify files and logs related to one or more enforcement events, comprising:
a memory storing files and logs related to one or more enforcement events (see Akif at [0050]: “These means may include components such as, for example, a memory, one or more data storage devices, a central processing unit, or any other components that may be used to run an application. Furthermore, although aspects of the present disclosure may be described generally as being stored in memory, one skilled in the art will appreciate that these aspects can be stored on or read from different types of computer program products”); and
a processor operably coupled to the memory and capable of executing one or more modules or machine-readable instructions (see Akif at [0050]: “These means may include components such as, for example, a memory, one or more data storage devices, a central processing unit, or any other components that may be used to run an application”), including:
a file collection module configured to send and receive messages regarding railroad enforcement event notifications (see Akif at [0016]: “The control system 100 may be used to convey a variety of network data and command and control signals in the form of messages communicated to the train 102, such as packetized data or information that is communicated in data packets, from the off-board remote controller interface 104”. Further, see [0017]: “Control system 100 may include a centralized or cloud-based computer processing system located in one or more of a back-office server or a plurality of servers remote from train 102, one or more distributed, edge-based computer processing systems located on-board one or more locomotives of the train, wherein each of the distributed computer processing systems is communicatively connected to the centralized computer processing system, and a data acquisition hub 312 (see FIG. 3) communicatively connected to one or more of databases and a plurality of sensors associated with the one or more locomotives or other components of the train and configured to acquire real-time and historical configuration, structural, and operational data in association with inputs derived from real time and historical contextual data relating to a plurality of trains operating under a variety of different conditions for use as training data”. Therefore, these messages/and or communication using a data acquisition hub is interpreted as the file collection module sending/receiving messages);
a message identification module configured to classify the messages and the railroad enforcement event notifications via the processor (see Akif at [0061]: “The data acquisition hub 312 may be configured to communicate “real-time” data from the monitored system 302 to the analytics server 316 using a network connection 314”. Further at [0062]: “Analytics engine 318 can be configured to generate predicted data for the monitored systems and analyze differences between the predicted data and the real-time data received from data acquisition hub 312”. Further, at [0068]: “The alarm can be indicative of a need for a repair event or maintenance, such as synchronization of any computer control systems that are no longer communicating within allowable latency parameters”. Therefore, this analytics server that generates prediction based on the received data is interpreted as the message identification module classifying the messages and notifications);
a log collection module configured to receive system component logs from memory (see Akif at [0017]: “Control system 100 may include a centralized or cloud-based computer processing system located in one or more of a back-office server or a plurality of servers remote from train 102, one or more distributed, edge-based computer processing systems located on-board one or more locomotives of the train, wherein each of the distributed computer processing systems is communicatively connected to the centralized computer processing system, and a data acquisition hub 312 (see FIG. 3) communicatively connected to one or more of databases and a plurality of sensors associated with the one or more locomotives or other components of the train and configured to acquire real-time and historical configuration, structural, and operational data in association with inputs derived from real time and historical contextual data relating to a plurality of trains operating under a variety of different conditions for use as training data”. Therefore this historical data is interpreted as system component logs); and
an information parsing module configured to parse the messages and the railroad enforcement event notifications, via the processor, for information including at least one of a user ID, employee information on the train, an employee requesting the information, and a location of the train (see Akif at [0017]: “Control system 100 may include a centralized or cloud-based computer processing system located in one or more of a back-office server or a plurality of servers remote from train 102, one or more distributed, edge-based computer processing systems located on-board one or more locomotives of the train, wherein each of the distributed computer processing systems is communicatively connected to the centralized computer processing system, and a data acquisition hub 312 (see FIG. 3) communicatively connected to one or more of databases and a plurality of sensors associated with the one or more locomotives or other components of the train and configured to acquire real-time and historical configuration, structural, and operational data in association with inputs derived from real time and historical contextual data relating to a plurality of trains operating under a variety of different conditions for use as training data”. Further, at [0048]: “Additionally or alternatively, sensors may include brake temperature sensors, exhaust sensors, fuel level sensors, pressure sensors, structural stress sensors, knock sensors, reductant level or temperature sensors, speed sensors, motion detection sensors, location sensors, or any other sensor known in the art”. Further at [0084]: “For example, locomotive control system 237 may be configured to retain information on when each respective train engineer operating the locomotive has logged into the system through positive train control (PTC) messages or other indicators”. Therefore, acquiring operational data from sensors, such as a location sensor, is interpreted as parsing for information including location of the train, and tracking information about each train operator logged into the system as parsing information including user ID and employee information).
Referring to Claim 2, Akif teaches the system of Claim 1, the machine-readable instructions further comprising generate, via the processor, one or more elements for display on the user device to provide a user with information related to railroad event management (see Akif at [0066]: “If significant deviations are detected, the decision engine can also be configured to determine whether an alarm condition exists, activate the alarm and communicate the alarm to a Human-Machine Interface (HMI) for display in real-time via, e.g., client 328. The decision engine of analytics engine 318 can also be configured to perform root cause analysis for significant deviations in order to determine the interdependencies and identify any failure relationships that may be occurring. The decision engine can also be configured to determine health and performance levels and indicate these levels for the various processes and equipment via the HMI of client”).
Referring to Claim 3, Akif teaches the system of Claim 1, wherein the information related to railroad event management includes notifications indicating at least one of file collections, log parsing, automated workflow initialization, railroad event handling, and errors (see Akif at [0066]: “If significant deviations are detected, the decision engine can also be configured to determine whether an alarm condition exists, activate the alarm and communicate the alarm to a Human-Machine Interface (HMI) for display in real-time via, e.g., client 328. The decision engine of analytics engine 318 can also be configured to perform root cause analysis for significant deviations in order to determine the interdependencies and identify any failure relationships that may be occurring. The decision engine can also be configured to determine health and performance levels and indicate these levels for the various processes and equipment via the HMI of client”).
Referring to Claim 4, Akif teaches the system of Claim 1, wherein the enforcement event is a PTC brake event (see Akif at [0002]: “For example, the supplied tractive and/or braking efforts may be based on Positive Train Control (PTC) instructions or control information for an upcoming trip. The control information may be used by a software application to determine the speed of the rail vehicle for various segments of an upcoming trip of the rail vehicle”).
Referring to Claim 5, Akif teaches the system of Claim 1, wherein the message identification module classifies the messages as an enforcement message or a status request and classifies the notification as a log status (see Akif at [0003]: “There are also benefits from a train tracking and monitoring system that determines and presents current, real-time position information for one or more trains in a railroad network, the configuration or arrangement of powered and non-powered units within each of the trains, and operational status of the various systems and subsystems of the trains that are being tracked”. Further, at [0024]: “The network data communicated to the off-board remote controller interface 104 from the train 102 may also provide alerts and other operational information that allows for remote monitoring, diagnostics, asset management, and tracking of the state of health of all of the primary power systems and auxiliary subsystems such as HVAC, air brakes, lights, event recorders, and the like”. Further at [0084]: “The system may be configured to automatically check the date of the last evaluation for that respective engineer and recommend or enforce a “check ride””. Further at [0095]: “Associative memory is built through “experiential” learning in which each newly observed state is accumulated in the associative memory as a basis for interpreting future events”).
Referring to Claim 6, Akif teaches the system of Claim 1, wherein the message identification module identifies the system component logs of the enforcement event (see Akif at [0017]: “Control system 100 may include a centralized or cloud-based computer processing system located in one or more of a back-office server or a plurality of servers remote from train 102, one or more distributed, edge-based computer processing systems located on-board one or more locomotives of the train, wherein each of the distributed computer processing systems is communicatively connected to the centralized computer processing system, and a data acquisition hub 312 (see FIG. 3) communicatively connected to one or more of databases and a plurality of sensors associated with the one or more locomotives or other components of the train and configured to acquire real-time and historical configuration, structural, and operational data in association with inputs derived from real time and historical contextual data relating to a plurality of trains operating under a variety of different conditions for use as training data”. Therefore this historical data is interpreted as system component logs).
Referring to Claim 7, Akif teaches the system of Claim 6, wherein the system component logs correspond to default set of onboard logs from at least one CPU on board the train (see Akif at [0017]: “Control system 100 may include a centralized or cloud-based computer processing system located in one or more of a back-office server or a plurality of servers remote from train 102, one or more distributed, edge-based computer processing systems located on-board one or more locomotives of the train, wherein each of the distributed computer processing systems is communicatively connected to the centralized computer processing system, and a data acquisition hub 312 (see FIG. 3) communicatively connected to one or more of databases and a plurality of sensors associated with the one or more locomotives or other components of the train and configured to acquire real-time and historical configuration, structural, and operational data in association with inputs derived from real time and historical contextual data relating to a plurality of trains operating under a variety of different conditions for use as training data”. Therefore this historical data from the computer processing systems located on-board one or more locomotives of the train is interpreted as the set of onboard logs from at least one CPU on board the train).
Claims 8-14 are rejected under 35 U.S.C. 103 as being unpatentable over Akif in view of Jain et al (US Pub. No. 2023/0123568 - hereinafter Jain) and further in view of Mehta et al (US Patent No. 10,931,686- hereinafter Mehta).
Referring to Claim 8, Akif teaches the system of Claim 1, wherein the message identification module verifies the message to identify whether the enforcement event actually occurred based on at least one of the characteristics (see Akif at [0098]: “The ranking system may include a tabular scoring of a plurality of train runs or segments of train runs for a plurality of trains, with each train run or segment of a train run being correlated to one or more rules that each indicate a Boolean true or false result of whether the train run or segment of a train run complied with the rule, and to one or more comparative key performance indicators that each indicate a score on a scale of 0-100% as compared to the comparative key performance indicator for a different but comparable train run or segment of a train run”).
Referring to Claim 9, Akif teaches a watchdog system configured to transmit and receive messages related to status monitoring to and from a client or server, comprising:
a memory storing files and logs related to one or more enforcement events (see Akif at [0050]: “These means may include components such as, for example, a memory, one or more data storage devices, a central processing unit, or any other components that may be used to run an application. Furthermore, although aspects of the present disclosure may be described generally as being stored in memory, one skilled in the art will appreciate that these aspects can be stored on or read from different types of computer program products”); and
a processor operably coupled to the memory and capable of executing one or more modules or machine-readable instructions (see Akif at [0050]: “These means may include components such as, for example, a memory, one or more data storage devices, a central processing unit, or any other components that may be used to run an application”), including:
a log download module configured to…determine whether the service queue includes a new enforcement message related to an enforcement event (see Akif at [0016]: “The control system 100 may be used to convey a variety of network data and command and control signals in the form of messages communicated to the train 102, such as packetized data or information that is communicated in data packets, from the off-board remote controller interface 104” and “The data communicated between the train 102 and the off-board remote controller interface 104 may include signals indicative of various operational parameters associated with components and subsystems of the train, signals indicative of fault conditions, signals indicative of maintenance activities or procedures, and command and control signals operative to change the state of various circuit breakers, throttles, brake controls, actuators, switches, handles, relays, and other electronically-controllable devices on-board any locomotive or other powered unit of the train 102”);
an automation initializing module configured to determine whether an automation service is executing on a designated server,…, and if the automation service is currently executing, execute an automation process (see Akif at [0016-0017]: “In various exemplary embodiments, a centralized or cloud-based computer processing system including remote controller interface 104 may be located in one or more of a back-office server or a plurality of servers remote from the train” and “Control system 100 may be configured to use artificial intelligence for maintaining synchronization between centralized (cloud-based) and distributed (edge-based) train control models. Control system 100 may include a centralized or cloud-based computer processing system located in one or more of a back-office server or a plurality of servers remote from train 102”. Therefore, this control system using artificial intelligence is interpreted as the automation process executing on a designated server); and
an automation workflow module configured to receive processed events, including results from the automation process and a root cause of the enforcement event (see Akif at [0066]: “The decision engine of analytics engine 318 can also be configured to perform root cause analysis for significant deviations in order to determine the interdependencies and identify any failure relationships that may be occurring. The decision engine can also be configured to determine health and performance levels and indicate these levels for the various processes and equipment via the HMI of client 328. All of which, when combined with the analytical and machine learning capabilities of analytics engine 318 allows the operator to minimize the risk of catastrophic equipment failure by predicting future failures and providing prompt, informative information concerning potential/predicted failures before they occur”).
However, Akif fails to teach:
a log download module configured to query a service queue at a specified frequency; and
whether the automation service is executing based on network traffic on a designated IP address or network traffic on the designated server.
Jain teaches, in an analogous system, a log download module configured to query a service queue at a specified frequency and determine whether the service queue includes a new enforcement message related to an enforcement event (see Jain at [0031]: “The virtualization container associated with a task may send to the work queue service a request to add one or more new tasks to the work queue. The request may identify the task type and include the required resources for each of the one or more new tasks”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Akif with the above teachings of Jain by having an automation workflow to determine services in a watchdog system, as taught by Akif, and having a queue with all the corresponding services as requested, as taught by Jain. The modification would have been obvious because one of ordinary skill in the art would be motivated to dynamically allocate resources that are assigned to execute the one or more tasks in the work queue (as suggested by Jain at Abstract).
Mehta teaches, in an analogous system, whether the automation service is executing based on network traffic on a designated IP address or network traffic on the designated server (see Mehta at Col. 6: lines 33-39: “In another example, the automation detection heuristics could be included in a reverse proxy or load balancer used in the provision of the web service, where an active inline security module of web server 130 receives and analyzes network traffic from a plurality of users, such as client computing systems 101 and 102, before delivering it to the web service”. Therefore, this security module to analyze network traffic before delivering the automation heuristics is interpreted as determining whether the automaton service is executing based on network traffic).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Akif and Jain with the above teachings of Mehta by having an automation workflow to determine services in a watchdog system and having a queue with all the corresponding services as requested, as taught by Akif and Jain, and executing the service required based on the network traffic, as taught by Mehta. The modification would have been obvious because one of ordinary skill in the art would be motivated to analyze network traffic in order to balance the load (as suggested by Mehta at Col. 6).
Referring to Claim 10, the combination of Akif, Jain and Mehta teaches the system of Claim 9, the machine-readable instructions further comprising generate, via the processor, one or more elements for display on a user device to provide a user with information related to workflow automation (see Akif at [0043]: “The remote controller interface 104 may include a GUI configured to display information and receive user inputs associated with the train. The GUI may be a graphic display tool including menus (e.g., drop-down menus), modules, buttons, soft keys, toolbars, text boxes, field boxes, windows, and other means to facilitate the conveyance and transfer of information between a user and remote controller interface”).
Referring to Claim 11, the combination of Akif, Jain and Mehta teaches the system of Claim 9, wherein the information related to workflow automation includes notifications indicating at least one of a status update, system component log status, and start of an automation service (see Akif at [0003]: “There are also benefits from a train tracking and monitoring system that determines and presents current, real-time position information for one or more trains in a railroad network, the configuration or arrangement of powered and non-powered units within each of the trains, and operational status of the various systems and subsystems of the trains that are being tracked”).
Referring to Claim 12, the combination of Akif, Jain and Mehta teaches the system of Claim 9, wherein if the service queue includes a new enforcement message, the log download module generates a record (see Jain at [0031]: “The virtualization container associated with a task may send to the work queue service a request to add one or more new tasks to the work queue. The request may identify the task type and include the required resources for each of the one or more new tasks”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Akif with the above teachings of Jain by having an automation workflow to determine services in a watchdog system, as taught by Akif, and having a queue with all the corresponding services as requested, as taught by Jain. The modification would have been obvious because one of ordinary skill in the art would be motivated to dynamically allocate resources that are assigned to execute the one or more tasks in the work queue (as suggested by Jain at Abstract).
Referring to Claim 13, the combination of Akif, Jain and Mehta teaches the system of Claim 12, wherein the record includes a collection of enforcement events based on enforcement messages from the internal service queue (see Jain at [0031]: “The virtualization container associated with a task may send to the work queue service a request to add one or more new tasks to the work queue. The request may identify the task type and include the required resources for each of the one or more new tasks”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Akif with the above teachings of Jain by having an automation workflow to determine services in a watchdog system, as taught by Akif, and having a queue with all the corresponding services as requested, as taught by Jain. The modification would have been obvious because one of ordinary skill in the art would be motivated to dynamically allocate resources that are assigned to execute the one or more tasks in the work queue (as suggested by Jain at Abstract).
Referring to Claim 14, the combination of Akif, Jain and Mehta teaches the system of Claim 9, wherein the log download module parses a file retrieval system for system component logs corresponding to the enforcement event (see Akif at [0017]: “Control system 100 may include a centralized or cloud-based computer processing system located in one or more of a back-office server or a plurality of servers remote from train 102, one or more distributed, edge-based computer processing systems located on-board one or more locomotives of the train, wherein each of the distributed computer processing systems is communicatively connected to the centralized computer processing system, and a data acquisition hub 312 (see FIG. 3) communicatively connected to one or more of databases and a plurality of sensors associated with the one or more locomotives or other components of the train and configured to acquire real-time and historical configuration, structural, and operational data in association with inputs derived from real time and historical contextual data relating to a plurality of trains operating under a variety of different conditions for use as training data”. This acquiring of information is interpreted as the parsing).
Allowable Subject Matter
For claims 15-20, no art rejection is made for these claims, they are only rejected under 35 USC 101 and Double Patenting, as explained above in this office action. None of the references of record either alone or in combination fairly disclose or suggest the combination of limitations specified in the independent claims, including at least:
“...an extraction module configured to receive data corresponding to system component logs including characteristics of an enforcement event, extract the data, and determine whether the data is structured or unstructured;
an analysis module configured to analyze the extracted data via one or more models to determine a root cause and generate an analysis result, wherein one or more analysis thresholds determine whether a single analysis model or multiple analysis models are required;
an event watch module configured to receive the analysis result from the analysis module and generate a high-level classification for the enforcement event and assign a unique ID to the analysis result, when the analysis result does not include the root cause; and
an automation production module configured to transmit a detailed synopsis to a user”.
Conclusion
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/LUIS A SITIRICHE/Primary Examiner, Art Unit 2126
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