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 14 is objected to because of the following informalities: the claim recites, in part, “execution of the instructions by the processor further causes the processor to … outputting, by the processor, the determined presence of a flight anomaly” (emphasis added). The term “outputting” should be “output” for grammatical accuracy.
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 9-14 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.
Regarding claim 9, the claim recites the limitation "the mobile device" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Regarding claims 10-14, the claims depend from claim 9 and are rejected for the same reason as claim 9, as they do not cure the deficiencies of claim 9 noted above.
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 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1, the claim recites, in part, “windowing, by the processor, the external flight data, cluster the at least one of acceleration data, gyroscope data, or inertia measurement unit (IMU) data of the flight data to define a plurality of time windows; extracting, by the processor, a plurality of features from the windowed flight data; determining, by the processor, based on the plurality of features, a set of flight regimes including at least one of level flight, landing, turning, and taking off, for each of the plurality of time windows.” These limitations, when read in light of the specification, are mental processes capable of being performed in the human mind. Upon the receipt of acceleration data, as illustrated in Figure 3B for example, a human being can mentally separate the data into specific time windows and identify a take-off/landing/cruising flight regime among the windows based on the acceleration data. Mental processes capable of being performed in the human mind have been held as being abstract ideas (see MPEP 2106.04(a)(2)).
This judicial exception is not integrated into a practical application because the claim does not purport the improvement to the functioning of a computer or other technology, is not applied by way of a particular machine, does not result in the tangible transformation in state of a particular article, and is not applied in some other meaningful manner (see MPEP 2106.05).
The claim recites additional elements of “receiving, by a processor of a mobile device, external flight data acquired from one or more sensors of the mobile device external to an aircraft flight controller for an aircraft during flight, wherein the external flight data comprises at least one of acceleration data, gyroscope data, or IMU data” and “outputting, by the processor, at a graphical user interface of the mobile device or a remote device, the determined set of flight regimes to be used to monitor flight events.” The collection, analysis, and display of available information, when not specifying new sources of data or techniques of data collection, has been held to be within the realm of abstract ideas (see Electric Power Group, LLC. v. Alstom, S.A., 830 F.3d 1350 (Fed. Circ. 2016); hereinafter “Electric Power Group”). Additionally, the limitation “to be used to monitor flight events” does not amount to significantly more than the abstract idea because the limitation merely specifies an intended use of the abstract idea (see MPEP 2106.05(f)).
The claim includes an additional element of a “mobile device” with a “processor”, “sensors”, and “a graphical user interface.” These limitations, when read in light of the specification, amount to a generic computing device such as a conventional smartphone (see [0064] of the specification as-filed). As such, the elements do not amount to significantly more than the abstract idea (see MPEP 2106.05(f)).
Regarding claim 2, the claim recites “determining, by the processor, period of turbulent event from the accelerometer data.” This limitation, when read in light of the specification, is a mental process in the form on a judgement and/or evaluation capable of being performed in the human mind.
The claim further recites “receiving, by the processor, accelerometer data captured during a flight and at around 100 Hz and excluding engine frequency” and “outputting, by the processor, the determined period of turbulent event during the flight.” As noted above in the rejection of claim 1, the collection and display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)).
Regarding claim 3, the claim recites “determining, via an outlier detection operator, based on the plurality of features, presence of a flight anomaly.” This limitation, when read in light of the specification, is a mental process in the form on a judgement and/or evaluation capable of being performed in the human mind. Additionally or alternatively, this limitation is a mathematical operation in the form of identifying an outlier data point using the variance of a data set.
The claim further recites “outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft.” As noted above in the rejection of claim 1, the display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)).
Regarding claim 4, the claim recites “determining, by the processor, based on the plurality of features, a flight path for the aircraft for the flight.” This limitation, when read in light of the specification, is a mental process capable of being performed in the human mind. A human being can mentally trace a flight path given collected position data.
The claim further recites “outputting, by the processor, at the graphical user interface of the mobile device or the remote device, the determined flight path.” As noted above in the rejection of claim 1, the display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)).
Regarding claim 5, the claim does not recite any limitations that are indicative of integration into a practical application or that amount to significantly more than the abstract idea. The claim merely further specifies the “plurality of features”, which does not change the “determining” step in claim 1 from being a mental process capable of being performed in the human mind.
Regarding claim 6, the claim recites “determining presence of a flight anomaly using a thresholded value from a Mahalanobis distances determined for at least one of the plurality of features.” This limitation is a mathematical operation. Mathematical calculations have been held as being abstract ideas (see MPEP 2106.04(a)(2)).
The claim further recites “outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft.” As noted above in the rejection of claim 1, the display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)). Additionally, the limitation “is used for predictive maintenance of the aircraft” does not amount to significantly more than the abstract idea because the limitation merely specifies an intended use of the abstract idea (see MPEP 2106.05(f)). Recited at a high level of generality, the claim limitation does not actually require the performance of predictive maintenance, only that the output data can be used for such an application.
Regarding claim 7, the claim does not recite any limitations that are indicative of integration into a practical application or that amount to significantly more than the abstract idea. The claim merely further specifies that the aircraft is a “fixed-wing aircraft.” This merely defines the technological environment to which the abstract idea is applied and does not amount to a particular machine used for practice of the abstract idea.
Regarding claim 8, the claim does not recite any limitations that are indicative of integration into a practical application or that amount to significantly more than the abstract idea. The claim merely further specifies that the aircraft is a “helicopter.” This merely defines the technological environment to which the abstract idea is applied and does not amount to a particular machine used for practice of the abstract idea.
Regarding claim 9, the claim recites, in part, “window the external flight data, cluster the at least one of acceleration data, gyroscope data, or inertia measurement unit (IMU) data of the flight data to define a plurality of time windows; extract a plurality of features from the windowed flight data; determining, by the processor, based on the plurality of features, a set of flight regimes including at least one of level flight, landing, turning, and taking off, for each of the plurality of time windows.” These limitations, when read in light of the specification, are mental processes capable of being performed in the human mind. Upon the receipt of acceleration data, as illustrated in Figure 3B for example, a human being can mentally separate the data into specific time windows and identify a take-off/landing/cruising flight regime among the windows based on the acceleration data. Mental processes capable of being performed in the human mind have been held as being abstract ideas (see MPEP 2106.04(a)(2)).
This judicial exception is not integrated into a practical application because the claim does not purport the improvement to the functioning of a computer or other technology, is not applied by way of a particular machine, does not result in the tangible transformation in state of a particular article, and is not applied in some other meaningful manner (see MPEP 2106.05).
The claim recites additional elements of “receive external flight data acquired from one or more sensors of the mobile device external to an aircraft flight controller for an aircraft during flight, wherein the external flight data comprises at least one of acceleration data, gyroscope data, or IMU data” and “output, at a graphical user interface of the mobile device or a remote device, the determined set of flight regimes to be used to monitor flight events.” The collection, analysis, and display of available information, when not specifying new sources of data or techniques of data collection, has been held to be within the realm of abstract ideas (see Electric Power Group, LLC. v. Alstom, S.A., 830 F.3d 1350 (Fed. Circ. 2016); hereinafter “Electric Power Group”). Additionally, the limitation “to be used to monitor flight events” does not amount to significantly more than the abstract idea because the limitation merely specifies an intended use of the abstract idea (see MPEP 2106.05(f)).
The claim recites additional elements of a “mobile device” and a “non-transitory computer readable medium having instructions stored thereon.” These limitations, when read in light of the specification, amount to a generic computing device such as a conventional smartphone (see [0064] of the specification as-filed). As such, the elements do not amount to significantly more than the abstract idea (see MPEP 2106.05(f)).
Regarding claim 10, the claim recites “determine period of turbulent event from the accelerometer data.” This limitation, when read in light of the specification, is a mental process in the form on a judgement and/or evaluation capable of being performed in the human mind.
The claim further recites “receive accelerometer data captured during a flight and at around 100 Hz and excluding engine frequency” and “output the determined period of turbulent event during the flight.” As noted above in the rejection of claim 9, the collection and display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)).
Regarding claim 11, the claim recites “determine, via an outlier detection operator, based on the plurality of features, presence of a flight anomaly.” This limitation, when read in light of the specification, is a mental process in the form on a judgement and/or evaluation capable of being performed in the human mind. Additionally or alternatively, this limitation is a mathematical operation in the form of identifying an outlier data point using the variance of a data set.
The claim further recites “output, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft.” As noted above in the rejection of claim 9, the display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)).
Regarding claim 12, the claim recites “determine based on the plurality of features, a flight path for the aircraft for the flight.” This limitation, when read in light of the specification, is a mental process capable of being performed in the human mind. A human being can mentally trace a flight path given collected position data.
The claim further recites “output, at the graphical user interface of the mobile device or the remote device, the determined flight path.” As noted above in the rejection of claim 1, the display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)).
Regarding claim 13, the claim does not recite any limitations that are indicative of integration into a practical application or that amount to significantly more than the abstract idea. The claim merely further specifies the “plurality of features”, which does not change the “determine” limitation in claim 9 from being a mental process capable of being performed in the human mind.
Regarding claim 14, the claim recites “determine presence of a flight anomaly using a thresholded value from a Mahalanobis distances determined for at least one of the plurality of features.” This limitation is a mathematical operation. Mathematical calculations have been held as being abstract ideas (see MPEP 2106.04(a)(2)).
The claim further recites “outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft.” As noted above in the rejection of claim 1, the display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)). Additionally, the limitation “is used for predictive maintenance of the aircraft” does not amount to significantly more than the abstract idea because the limitation merely specifies an intended use of the abstract idea (see MPEP 2106.05(f)). Recited at a high level of generality, the claim limitation does not actually require the performance of predictive maintenance, only that the output data can be used for such an application.
Regarding claim 15, the claim recites, in part, “windowing, by the processor, the external flight data, cluster the at least one of acceleration data, gyroscope data, or inertia measurement unit (IMU) data of the flight data to define a plurality of time windows; extracting, by the processor, a plurality of features from the windowed flight data; determining, by the processor, based on the plurality of features, a set of flight regimes including at least one of level flight, landing, turning, and taking off, for each of the plurality of time windows.” These limitations, when read in light of the specification, are mental processes capable of being performed in the human mind. Upon the receipt of acceleration data, as illustrated in Figure 3B for example, a human being can mentally separate the data into specific time windows and identify a take-off/landing/cruising flight regime among the windows based on the acceleration data. Mental processes capable of being performed in the human mind have been held as being abstract ideas (see MPEP 2106.04(a)(2)).
This judicial exception is not integrated into a practical application because the claim does not purport the improvement to the functioning of a computer or other technology, is not applied by way of a particular machine, does not result in the tangible transformation in state of a particular article, and is not applied in some other meaningful manner (see MPEP 2106.05).
The claim recites additional elements of “receiving, by a processor of a computing device, external flight data acquired from one or more sensors of a remote instrument external to an aircraft flight controller for an aircraft during flight, wherein the external flight data comprises at least one of acceleration data, gyroscope data, or IMU data” and “outputting, by the processor, at a graphical user interface of the computing device or a remote device, the determined set of flight regimes to be used to monitor flight events.” The collection, analysis, and display of available information, when not specifying new sources of data or techniques of data collection, has been held to be within the realm of abstract ideas (see Electric Power Group, LLC. v. Alstom, S.A., 830 F.3d 1350 (Fed. Circ. 2016); hereinafter “Electric Power Group”). Additionally, the limitation “to be used to monitor flight events” does not amount to significantly more than the abstract idea because the limitation merely specifies an intended use of the abstract idea (see MPEP 2106.05(f)).
The claim includes an additional element of a “computing device” with a “processor”, “sensors”, and “a graphical user interface.” These limitations, when read in light of the specification, amount to a generic computing device such as a conventional smartphone (see [0064] of the specification as-filed). As such, the elements do not amount to significantly more than the abstract idea (see MPEP 2106.05(f)).
Regarding claim 16, the claim recites “determining, by the processor, period of turbulent event from the accelerometer data.” This limitation, when read in light of the specification, is a mental process in the form on a judgement and/or evaluation capable of being performed in the human mind.
The claim further recites “receiving, by the processor, accelerometer data captured during a flight and at around 100 Hz and excluding engine frequency” and “outputting, by the processor, the determined period of turbulent event during the flight.” As noted above in the rejection of claim 15, the collection and display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)).
Regarding claim 17, the claim recites “determining, via an outlier detection operator, based on the plurality of features, presence of a flight anomaly.” This limitation, when read in light of the specification, is a mental process in the form on a judgement and/or evaluation capable of being performed in the human mind. Additionally or alternatively, this limitation is a mathematical operation in the form of identifying an outlier data point using the variance of a data set.
The claim further recites “outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft.” As noted above in the rejection of claim 15, the display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)).
Regarding claim 18, the claim recites “determining, by the processor, based on the plurality of features, a flight path for the aircraft for the flight.” This limitation, when read in light of the specification, is a mental process capable of being performed in the human mind. A human being can mentally trace a flight path given collected position data.
The claim further recites “outputting, by the processor, at the graphical user interface of the mobile device or the remote device, the determined flight path.” As noted above in the rejection of claim 15, the display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)).
Regarding claim 19, the claim does not recite any limitations that are indicative of integration into a practical application or that amount to significantly more than the abstract idea. The claim merely further specifies the “plurality of features”, which does not change the “determining” step in claim 15 from being a mental process capable of being performed in the human mind.
Regarding claim 20, the claim recites “determining presence of a flight anomaly using a thresholded value from a Mahalanobis distances determined for at least one of the plurality of features.” This limitation is a mathematical operation. Mathematical calculations have been held as being abstract ideas (see MPEP 2106.04(a)(2)).
The claim further recites “outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft.” As noted above in the rejection of claim 15, the display of data for use in an abstract idea does not amount to significantly more than the abstract idea (see Electric Power Group and MPEP 2106.05(g)). Additionally, the limitation “is used for predictive maintenance of the aircraft” does not amount to significantly more than the abstract idea because the limitation merely specifies an intended use of the abstract idea (see MPEP 2106.05(f)). Recited at a high level of generality, the claim limitation does not actually require the performance of predictive maintenance, only that the output data can be used for such an application.
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.
Claims 1, 3, 5, 7-9, 11, 13, 15, 17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Nachbar et al. (United States Patent Application Publication No. US 2024/0267454 A1) [hereinafter “Nachbar”] in view of Dunning et al. (United States Patent Application Publication No. US 2021/0394920 A1) [hereinafter “Dunning”].
Regarding claim 1, Nachbar teaches a method of performing flight monitoring, the method comprising:
receiving, by a processor of a mobile device, external flight data acquired from one or more sensors of the mobile device external to an aircraft flight controller for an aircraft during flight, wherein the external flight data comprises at least one of acceleration data, gyroscope data, or IMU data (see [0006]-[0009], [0035], [0038]-[0039], and [0053]-[0064]);
windowing, by the processor, the external flight data, cluster the at least one of acceleration data, gyroscope data, or inertia measurement unit (IMU) data of the flight data to define a plurality of time windows (see [0060]-[0065] and [0067]);
extracting, by the processor, a plurality of features from the windowed flight data (see at least [0060]-[0070]);
determining, by the processor, based on the plurality of features, a set of flight regimes including taking off, for each of the plurality of time windows (see [0060]-[0070]).
Nachbar does not expressly teach outputting, by the processor, at a graphical user interface of the mobile device or a remote device, the determined set of flight regimes to be used to monitor flight events.
Dunning also generally teaches using a mobile device separate from an aircraft flight controller to measure aircraft accelerations (see [0018]-[0023]). Dunning teaches that the determined flight regime data can be displayed to an occupant for analysis and maintenance requirement tracking (see at least [0035]). Dunning teaches that the data is acquired over multiple flight regimes, but that the user is required to confirm the current flight regime (see [0033]-[0034]).
As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to apply the method taught by Nachbar to the device taught by Dunning resulting in outputting the determined set of flight regimes to be used to monitor flight events at a graphical user interface of the mobile device, in view of Dunning, as the resultant combination would allow the collection of data in the system taught by Dunning without the necessity for the operator to specifically enter or confirm the current flight regime.
Regarding claim 3, the combination of Nachbar and Dunning further teaches determining, via an outlier detection operator, based on the plurality of features, presence of a flight anomaly, and outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft (see [0022]-[0025] and [0033]-[0035] of Dunning).
Regarding claim 5, the combination of Nachbar and Dunning further teaches the plurality of features includes variance value for magnitude of the acceleration data for one axis (see [0068]-[0069] of Nachbar).
Regarding claim 7, the combination of Nachbar and Dunning further teaches the aircraft is a fixed-wing aircraft (see Figure 1 of Nachbar).
Regarding claim 8, the combination of Nachbar and Dunning further teaches the aircraft is a helicopter (see Figure 1 of Dunning).
Regarding claim 9, the combination of Nachbar and Dunning, as applied to claim 1 above, teaches a non-transitory computer readable medium having instructions stored thereon (see [0081]-[0085] of Nachbar), wherein execution of the instructions by a processor causes the processor to:
receive external flight data acquired from one or more sensors of the mobile device external to an aircraft flight controller for an aircraft during flight, wherein the external flight data comprises at least one of acceleration data, gyroscope data, or IMU data (see [0006]-[0009], [0035], [0038]-[0039], and [0053]-[0064] of Nachbar);
window the external flight data, cluster the at least one of acceleration data, gyroscope data, or inertia measurement unit (IMU) data of the flight data to define a plurality of time windows (see [0060]-[0065] and [0067] of Nachbar);
extract a plurality of features from the windowed flight data (see at least [0060]-[0070] of Nachbar);
determining, by the processor, based on the plurality of features, a set of flight regimes including taking off, for each of the plurality of time windows (see [0060]-[0070] of Nachbar); and
output, at a graphical user interface of the mobile device or a remote device, the determined set of flight regimes to be used to monitor flight events (see [0035] of Dunning and the rejection of claim 1).
Regarding claim 11, the combination of Nachbar and Dunning further teaches execution of the instructions by the processor further causes the processor to: determine, via an outlier detection operator, based on the plurality of features, presence of a flight anomaly; and output, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft (see [0022]-[0025] and [0033]-[0035] of Dunning).
Regarding claim 13, the combination of Nachbar and Dunning further teaches the plurality of features includes variance value for magnitude of the acceleration data for one axis (see [0068]-[0069] of Nachbar).
Regarding claim 15, the combination of Nachbar and Dunning, as applied to claim 1 above, teaches a method of performing flight monitoring, the method comprising:
receiving, by a processor of a computing device, external flight data acquired from one or more sensors of a remote instrument external to an aircraft flight controller for an aircraft during flight, wherein the external flight data comprises at least one of acceleration data, gyroscope data, or IMU data (see [0006]-[0009], [0035], [0038]-[0039], and [0053]-[0064] of Nachbar);
windowing, by the processor, the external flight data, cluster the at least one of acceleration data, gyroscope data, or inertia measurement unit (IMU) data of the flight data to define a plurality of time windows (see [0060]-[0065] and [0067] of Nachbar);
extracting, by the processor, a plurality of features from the windowed flight data (see at least [0060]-[0070] of Nachbar);
determining, by the processor, based on the plurality of features, a set of flight regimes including taking off, for each of the plurality of time windows (see [0060]-[0070] of Nachbar);
outputting, by the processor, at a graphical user interface of the computing device or a remote device, the determined set of flight regimes to be used to monitor flight events (see [0035] of Dunning and the rejection of claim 1).
Regarding claim 17, the combination of Nachbar and Dunning further teaches determining, via an outlier detection operator, based on the plurality of features, presence of a flight anomaly, and outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft (see [0022]-[0025] and [0033]-[0035] of Dunning).
Regarding claim 19, the combination of Nachbar and Dunning further teaches the plurality of features includes variance value for magnitude of the acceleration data for one axis (see [0068]-[0069] of Nachbar).
Claims 4, 12, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Nachbar and Dunning, as applied to claim 1 above, and further in view of Dugan (United States Patent Application Publication No. US 2014/0106333 A1).
Regarding claim 4, the combination of Nachbar and Dunning, as applied to claim 1 above, does not expressly teach determining, by the processor, based on the plurality of features, a flight path for the aircraft for the flight, and outputting, by the processor, at the graphical user interface of the mobile device or the remote device, the determined flight path.
Nachbar teaches the mobile device includes a GPS receiver 260 that tracks a position of the mobile device and aircraft (see [0018] and [0050]-[0051]), but does not expressly teach using this data to determine a flight path and output the flight path.
Dugan also generally teaches a portable electronic device for use on an airplane (see Abstract). Dugan teaches GPS data from the portable electronic device is used to determine a flight path of the aircraft, which is displayed on the portable electronic device (see at least [0031] and Figures 3A-3B).
As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention taught by the combination of Nachbar and Dunning to determine the flight path of the aircraft and display the flight path on the mobile device, in view of Dugan, as Dugan teaches displaying the flight path along with acceleration data can help to reduce a passenger’s anxiety (see at least [0007]).
Regarding claim 12, the combination of Nachbar, Dunning, and Dugan further teaches execution of the instructions by the processor further causes the processor to: determine based on the plurality of features, a flight path for the aircraft for the flight; and output, at the graphical user interface of the mobile device or the remote device, the determined flight path (see the rejection of claim 4 above).
Regarding claim 18, the combination of Nachbar, Dunning, and Dugan further teaches determining, by the processor, based on the plurality of features, a flight path for the aircraft for the flight; and outputting, by the processor, at the graphical user interface of the mobile device or the remote device, the determined flight path (see the rejection of claim 4 above).
Claims 2, 10, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Nachbar, Dunning, and Dugan, as applied to claim 4 above, and further in view of Mansfield et al. (Mansfield, N.J.; Aggarwal, G. “Whole-Body Vibration Experienced by Pilots, Passengers and Crew in Fixed-Wing Aircraft: A State-of-the-Science Review”. Vibration 2022, 5, 110-120. <https://doi.org/10.3390/vibration5010007>).
Regarding claim 2, the combination of Nachbar, Dunning, and Dugan, as applied to claim 4 above, teaches receiving, by the processor, accelerometer data captured during a flight (see [0060]-[0065] of Nachbar); determining, by the processor, period of turbulent event from the accelerometer data (see [0017], [0028], and [0046] of Dugan); outputting, by the processor, the determined period of turbulent event during the flight (see [0028] of Dugan).
The combination of Nachbar, Dunning, and Dugan does not expressly teach the accelerometer data is captured at around 100 Hz and excluding engine frequency.
Mansfield teaches that engine vibration is generally observed at frequencies of about 1000 Hz (see Section 5). Mansfield further teaches that human body vibration data to determine turbulent events is typically observed up to 100 Hz (see Section 5).
As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention taught by the combination of Nachbar, Dunning, and Dugan to capture the accelerometer data at around 100 Hz and exclude engine frequency, in view of Mansfield, as Mansfield teaches body vibration to detect turbulent events occurs around 100 Hz, and such would exclude engine frequency.
Regarding claim 10, the combination of Nachbar, Dunning, Dugan, and Mansfield further teaches execution of the instructions by the processor further causes the processor to: receive accelerometer data captured during a flight and at around 100 Hz and excluding engine frequency; determine period of turbulent event from the accelerometer data; output the determined period of turbulent event during the flight (see the rejection of claim 2 above).
Regarding claim 16, the combination of Nachbar, Dunning, Dugan, and Mansfield further teaches receiving, by the processor, accelerometer data captured during a flight and at around 100 Hz and excluding engine frequency; determining, by the processor, period of turbulent event from the accelerometer data; outputting, by the processor, the determined period of turbulent event during the flight (see the rejection of claim 2 above).
Claims 6, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Nachbar and Dunning, as applied to claim 1 above, and further in view of Khalastchi et al. (United States Patent Application Publication No. US 2014/0149806 A1) [hereinafter “Khalastchi”].
Regarding claim 6, the combination of Nachbar and Dunning, as applied to claim 1 above, teaches outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft (see [0003], [0019], and [0035] of Dunning).
The combination of Nachbar and Dunning does not expressly teach determining presence of the flight anomaly using a threshold value from a Mahalanobis distances determined for at least one of the plurality of features.
Khalastchi generally teaches detecting an anomaly in aircraft behavior (see [0008]). Khalastchi teaches an anomaly is detected based on a Mahalanobis distance in collected data being greater than a threshold (see [0008] and [0120]).
As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention taught by the combination of Nachbar and Dunning to detect the presence of the flight anomaly based on a Mahalanobis distance for detected data being above a threshold value, in view of Khalastchi, as Khalastchi teaches this is a known method of identifying anomalous behavior in an aircraft.
Regarding claim 14, the combination of Nachbar, Dunning, and Khalastchi further teaches execution of the instructions by the processor further causes the processor to: determine presence of a flight anomaly using a thresholded value from a Mahalanobis distances determined for at least one of the plurality of features; outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft (see the rejection of claim 6 above).
Regarding claim 20, the combination of Nachbar, Dunning, and Khalastchi further teaches determining presence of a flight anomaly using a thresholded value from a Mahalanobis distances determined for at least one of the plurality of features; outputting, by the processor, the determined presence of a flight anomaly, wherein the outputted determination for flight anomaly is used for predictive maintenance of the aircraft (see the rejection of claim 6 above).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Halsey et al. (US 2021/0183254 A1) generally teaches:
System and method for forecasting availability of network services during flight is provided. The system of the disclosed invention utilizes flight plans and coverage data to provide users aboard aircraft with status of satellite Internet services. The system couples the flight plans with the coverage data to provide information regarding how the flight path of the aircraft will affect availability of Internet services during the flight. The method includes retrieving a flight plan to generate a flight path having one or more waypoints, transmitting one or more service coverage data from service providers, coupling the flight path with the service coverage data to determine portions of the flight path in which the network service is unavailable, and delivering to the users information about the service unavailable portions of the flight path.
Fields et al. (US 2019/0279439 A1) generally teaches:
Systems, computer-implemented methods and/or computer program products that facilitate capturing aircraft flight segment are provided. In one embodiment, a computer-implemented method comprises: respectively providing, by a mobile computing device comprising a processor, data sets, wherein the data sets include operation, location, altitude, speed, orientation, vibration data and noise data of an aircraft; classifying, by the mobile computing device, the data sets into current flight segment, state of aircraft engine and type of engine; and generating, by the mobile computing device, a visualization regarding the current flight segment, the state of aircraft engine and the type of engine. In another embodiment, a computer-implemented method comprises: performing, by a system operatively coupled to a processor, an Internet search and aggregates historical flight information relevant to a user to determine at least one of: user lifetime air mileage, flight segments traveled, aircraft traveled, engine usage, statistics on cruise speeds, altitudes or frequent flyer miles; and scanning, by the system, the Internet search for live information displayed via social media or news outlets that is relevant to the user's travel history.
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/ANSHUL SOOD/ Primary Examiner, Art Unit 3667