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 .
Terminal Disclaimer
The terminal disclaimer filed on 11/10/2025 disclaiming the terminal portion of any patent granted on this application which would extend beyond the expiration date of U.S. pending reference application number 18/308,925 has been reviewed and is accepted. The terminal disclaimer has been recorded. The previous double patenting rejection has been overcome.
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 1-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. “mathematical relationships” which the court has identified as abstract) without significantly more. Claims 1, 9 and 16 are directed to the abstract idea of generate a series of covariance matrices for DAS data from the φ-OTDR, determine acoustic events based upon the covariance matrices and a machine learning network. These limitations fall under mathematical concepts. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the only additional elements are an optical fiber; a phase-sensitive optical time domain reflectometer (b-OTDR) coupled to the optical fiber; and a processor cooperating with the φ-OTDR; which are conventional equipment and generating an acoustic event report from the acoustic events; which is considered an extra solution activity such as outputting data (i.e. generating a report). The claims as a whole do not amount to significantly more than the abstract idea itself.
The data processing are recited so generically (no details whatsoever are provided other than e.g., “determining acoustic events based upon the covariance matrices and a machine learning network”) that it represents no more than mere instructions to apply the judicial exceptions on a computer. It can also be viewed as nothing more than an attempt to generally link the use of the judicial exceptions to the technological environment of a computer. Noting MPEP 2106.04(d)(I): “It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2A Prong Two. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception does not guarantee eligibility. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1983-84 (2014) ("The fact that a computer ‘necessarily exist[s] in the physical, rather than purely conceptual, realm,’ is beside the point")”.
Thus, under Step 2A, prong 2 of the analysis, even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claims are directed to the judicial exception. No specific practical application is associated with the claimed system. For instance, nothing is done with the generated acoustic event report.
Under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as described above, merely amount to a general purpose computer system that attempts to apply the abstract idea in a technological environment, limiting the abstract idea to a particular field of use, and/or merely insignificant extra-solution activity. Such insignificant extra-solution activity, e.g. data gathering and output, when re-evaluated under Step 2B is further found to be well-understood, routine, and conventional See MPEP 2106.05(d)(II).
Dependent claims 2-8, 10-15 and 17-22 merely expand upon the abstract idea further defining the abstract steps of claims 1 and 20 respectively, and therefore stand rejected under 35 USC 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.
Claim(s) 1-3, 9-11, 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Farhadiroushan et al. (US 2014/0025319, hereinafter Far) and further in view of Ba et al. (US 2023/0251646, hereinafter Ba).
Regarding claims 1, 9 and 16, Far discloses a distributed acoustic sensing (DAS) method/system and device comprising:
an optical fiber (see abstract);
a phase-sensitive optical time domain reflectometer (φ-OTDR) coupled to the optical fiber (see para. 0052); and
a processor cooperating with the φ -OTDR (see para. 0026 and 0057) and configured to
generate a series of covariance matrices for DAS data from the φ -OTDR (see para. 0103),
determine acoustic events based upon the covariance matrices (see para. 0020), and
generate an acoustic event report from the acoustic events (see para. 0022, 0121).
However, Far fails to expressly disclose that the acoustic events are determined based upon the covariance matrices and a machine learning network.
Ba discloses the use of machine learning and covariance matrixes to determine anomaly events (see para. 0073, 0076 and 0083).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Far’s invention to incorporate machine learning as described in Ba for the benefit of detecting an anomaly in the process.
Regarding claims 2, 10 and 17, Far in view of Ba discloses the DAS method/system and device of claims 1, 9 and 16 respectively, wherein the machine learning network comprises a Variational Autoencoder (VAE) network. (The Examiner takes official notice noting that machine learning networks can comprise a variational autoencoder network since introduced in 2013).
Regarding claims 3, 11 and 18, Far in view of Ba discloses the DAS system of claims 1, 9 and 16 respectively, wherein the machine learning network comprises a Long Short Term Memory (LSTM) network (see Ba para. 0076 and 0099).
Claim(s) 6, 14 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Far, Ba, and further in view of Peters et al. US 2022/0076044, hereinafter Pete).
Regarding claims 6, 14 and 21, Far in view of Ba discloses the DAS method/system and device of claims 1, 9 and 16 respectively.
However, Far in view of Ba fail to disclose the DAS method/system and device of claims 1, 9 and 16 respectively, wherein the processor is further configured to select a subset of the covariance matrices from which to determine the acoustic events based upon comparing the series of covariance matrices with a corresponding Toeplitz matrix.
Pete discloses training a flow system comprising, as illustrated in Figures 1-12, obtaining data from a sensor 30 (e.g. para. 0105, 0116; Figure 3); a processor 45 (e.g. a processor; para.0114) cooperating with the sensor; generating a series of covariance matrices for the data (e.g. paragraph [0142]); comparing the series of covariance matrices with a corresponding Toeplitz matrix (e.g. para 0093 and 0046). (See, para. 0011 to 0070 and 0088 to 0151).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have readily recognize the advantages and desirability to employ comparing the series of covariance matrices with a corresponding Toeplitz matrix as suggested by Pete to the system of Far in view of Ba in order to have the ability to map the weights of convolutional layer to a 2-D matrix and provide a multivariate normal distribution as an identity matrix. (See para. 0093 and 0142 of Pete).
Response to Arguments
Applicant's arguments filed 11/10/2025 have been fully considered but they are not persuasive.
Applicant argues that the claims are patentable under 101 and are geared towards a practical application with structure of an optical fiber.
In response the Examiner respectfully disagrees and points to the rejection above. The claims don’t recite any practical application but merely generate an acoustic event report which is simply outputting data. The structural limitations such as a processor, an optical fiber and a time domain reflectometer are conventional equipment and not novel. Under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as described above, merely amount to a general purpose computer system that attempts to apply the abstract idea in a technological environment, limiting the abstract idea to a particular field of use, and/or merely insignificant extra-solution activity (outputting an acoustic report).
Applicant argues that Ba et al. fails to disclose a machine learning network by a processor in cooperation with an φ -OTDR.
In response the Examiner points to the fact that Ba et al et al. was brought in to cure the deficiency of Farhadiroushan et al. for not having a machine learning network. Ba et al. solves the problem area as specified in the claim using machine learning. Machine learning can be used in conjunction with sensors or φ -OTDR systems.
In response to applicant's argument that the applied references is non-analogous art, it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, Ba et al. is solving the problem area of using a learning network.
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANUEL A RIVERA VARGAS whose telephone number is (571)270-7870. The examiner can normally be reached M-F 9:00-6:00.
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/MANUEL A RIVERA VARGAS/Primary Examiner, Art Unit 2857
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