DETAILED ACTION
This Final Office Action is in response to the amendment filed 6/1/2026.
Claims 1-3 and 5-18 have been amended.
Claims 4 and 19 have been canceled.
Claim 20 is a new claim.
Claims 1-3, 5-18, and 20 are pending.
Response to Arguments
Rejections under 35 U.S.C. 101
On pages 10-11 of Remarks filed 6/1/2026, with respect to step 2A prong one, the Applicant contends that the steps of estimating an engine combustor outlet temperature using aircraft-specific learning information and linking the estimated engine condition to maintenance-cost information are specific technical processes that cannot practically be performed in the human mind or by pen and paper.
The Examiner respectfully disagrees. The subject matter eligibility analysis under 35 U.S.C. 101 must be applied to the claims as written, and claims must be given their broadest reasonable interpretation consistent with the specification (see MPEP 2111). The steps referenced by the Applicant include the limitations of:
“the related information comprises an estimated result of an engine combustor outlet temperature of the target aircraft by applying input information based on the candidate flight path to learning information corresponding to characteristics of the target aircraft,
the executed program further causes the processor to acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor, and
the output information includes flight information that minimizes the maintenance cost or makes the maintenance cost fall within an allowable maintenance cost.”
As discussed in detail in the rejections under 35 U.S.C. 101 below, the limitation of “the related information comprises an estimated result of an engine combustor outlet temperature of the target aircraft by applying input information based on the candidate flight path to learning information corresponding to characteristics of the target aircraft” encompasses a person looking at data (i.e. “input information,” “learning information,” and “candidate flight path”) and forming a simple observation and evaluation (i.e. “estimated result of an engine combustor outlet temperature”). For example, a pilot observes a planned flight route (i.e. “candidate flight path”) and observes historical performance tables regarding how a specific aircraft operated (i.e. “learning information”), such that the pilot then mentally maps the planned flight route against the historical performance tables to estimate “an engine combustor outlet temperature.”
The limitation of “acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor” encompasses a person looking at data (i.e. “engine operating time” and “estimated result of the engine combustor”) and forming a simple observation and evaluation (i.e. “acquire information regarding maintenance costs”). For example, an analyst may mentally identify the maintenance cost associated with running an engine for a particular amount of time at a particular engine combustor outlet temperature.
The limitation of “the output information includes flight information that minimizes the maintenance cost or makes the maintenance cost fall within an allowable maintenance cost” encompasses a person looking at data (i.e. “maintenance cost” and “allowable maintenance cost”) and forming a simple observation and evaluation (i.e. identify flight information that minimizes or makes the maintenance cost fall within an allowable maintenance cost). For example, a pilot may mentally weigh flight control options based on their associated maintenance costs, e.g., lower flight speeds may be defined as having lower “maintenance costs” than higher flight speeds. Additionally, this limitation may be interpreted as Certain Methods of Organizing Human Activity, such that choosing a flight path (i.e. “flight information”) based on a business optimization goal (i.e. “allowable maintenance cost”) would be considered a fundamental economic practice.
The limitation of “learning information” is broad, such that by itself, the limitation of “learning information” would not be reasonably interpreted as incorporating any particular machine learning steps. No limitations are provided in how the hardware executes the estimation in claims 1 and 18, and thus, the “estimated result of an engine combustor outlet temperature” is merely data generated from other generally recited data. Linking a condition to “maintenance cost” introduces an additional mental process and/or certain method of organizing human activity, as discussed above.
On page 11 of Remarks, with respect to step 2A prong one, the Applicant contends that claim 6 recites “acquiring, from one or more sensors provided to a target aircraft, real-time condition information regarding conditions of the target aircraft” that go beyond merely acquiring, analyzing, and displaying data.
The Examiner respectfully disagrees. As discussed in detail in the rejections under 35 U.S.C. 101, the “acquire real-time conditions” step is recited at a high level of generality and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “one or more sensors” are generic sensors that are merely claimed as a source of the generally recited data, and therefore, the “one or more sensors” do not impose meaningful limits on the claim. See MPEP 2106.05(b)(III).
The Applicant should note that claims 6 and 20 have been determined to be eligible under 35 U.S.C. 101 for other reasons. Specifically, the claims recite a specific technical improvement in neural network architecture (i.e. “a neural network with a recursive structure” combined with “an attention mechanism pooling layer to share condition within the neural network used for each of the two or more other aircrafts flying simultaneously with the target aircraft”) and does not simply recite “using a neural network,” for example.
On page 11 of Remarks, with respect to step 2A prong one, the Applicant contends that claim 16 is directed to a specific technical process for configuring learning information using machine learning methods and applying the learning information to predict inertia-related information at each point on a flight path of a target aircraft. The Applicant further contends that the steps of claim 16 are specific technical processes that cannot practically be performed in the human mind or by pen and paper.
The Examiner respectfully disagrees and contends that claim 16 is directed to both mental process and mathematical concept abstract ideas. The subject matter eligibility analysis under 35 U.S.C. 101 must be applied to the claims as written, and claims must be given their broadest reasonable interpretation consistent with the specification (see MPEP 2111). The steps referenced by the Applicant include the limitations of:
“acquire, from one or more sensors provided to a target aircraft, real-time condition information regarding conditions of the target aircraft;
acquiring learning information configured by machine learning methods using two or more pairs of learning input information comprising weather information and condition information acquired for a flight of one aircraft, and learning output information comprising inertia-related information measured at each point on a flight path of the one aircraft,
applying input information comprising the weather information and condition information of the target aircraft, to the learning information,
acquiring prediction information regarding inertia information at each point on the candidate flight path of the target aircraft.”
As discussed in detail in the rejections under 35 U.S.C. 101 below, the limitation of “acquiring learning information configured by machine learning methods using two or more pairs of learning input information comprising weather information and condition information acquired for a flight of one aircraft, and learning output information comprising inertia-related information measured at each point on a flight path of the one aircraft” encompasses mathematical calculations in which parameters (i.e. “learning information”) are generated using training pairs (i.e. “learning input information”), which is a known method of supervised learning. Supervised learning is fundamentally a system of mathematical equations. Because the limitation recites explicitly performing a mathematical calculation, the limitation, as drafted, falls within the mathematical concepts grouping of abstract ideas. The limitation of “measured at each point on a flight path of the one aircraft” merely describes the generally recited data (i.e. “inertia-related information”), without requiring active controlled operations of the aircraft itself. The “learning information configured by machine learning methods” is described at a high level of generally such that it amounts to using a computer with a generic machine learning model to apply the abstract idea.
The limitation of “applying input information comprising the weather information and condition information of the target aircraft, to the learning information” encompasses machine learning inference, given that the “learning information” is defined to be “configured by machine learning methods” in a preceding claim element. Inference operates as mathematical calculations. Therefore, the “applying” step may reasonably encompass the underlying mathematical equations on two sets of generally recited data, and thus, the limitation, as drafted, falls within the mathematical concepts grouping of abstract ideas.
The limitation of “acquiring prediction information regarding inertia information at each point on the candidate flight path of the target aircraft” encompasses a person looking at data (i.e. candidate flight path) and forming a simple observation and evaluation (i.e. acquiring prediction information regarding inertia information at each point on the candidate flight path). For example, an analyst may observe a flight path on a map and mentally predict inertia values at various locations along the flight path.
On page 11 of Remarks, with respect to step 2A prong two, the Applicant contends that claims 1 and 18 integrate learning-based engine condition estimation into a practical aircraft operation context by acquiring maintenance-related information directly linked to estimated engine operating conditions, which improves the technical field of aircraft maintenance planning by providing path-dependent, aircraft-specific engine condition evaluation.
The Examiner respectfully disagrees. As is evident from the limitations of claim 1 recited above, no particular machine learning steps are claimed to perform an engine condition estimation. The claim is recited at a high level of generality, and no technological details are recited with respect to how the hardware executes the estimation (e.g., how a machine learning model interacts with physical sensor inputs or how the physical operation of the engine is actively modified). Therefore, the “estimated result of an engine combustor outlet temperature” is interpreted as a result-oriented solution rather than an actual technological improvement and thus does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(f)(1).
Merely limiting the estimation to a particular environment (i.e. aircraft) or a generic business optimization goal (i.e. minimize maintenance cost) constitutes a field-of-use limitation that does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(h).
On pages 11-12 of Remarks, with respect to step 2A prong two, the Applicant contends that claim 6 integrates the specific machine learning into a practical application by predicting the location prediction information showing future positions of two or more other aircrafts along a flight path, enabling to obtain more accurate location prediction information.
The Examiner agrees. Claim 6 is indicated as eligible under 35 U.S.C. 101 in the present Office Action.
On page 12 of Remarks, with respect to step 2A prong two, the Applicant contends that claim 16 integrates the specific machine learning into a practical Application by predicting inertia-related information along a flight path, enabling evaluation of how atmospheric conditions influence aircraft operation.
The Examiner respectfully disagrees. Predicting generally recited data (i.e. “inertia-related information”) to enable an “evaluation” is a cognitive outcome that merely improves human decision-making which has been identified as not a sufficient improvement by the courts. See 2106.05(a)(I). Specifically, the claim is recited at a high level of generality, and no technological details are recited with respect to how the hardware executes the prediction (e.g., how the machine learning method interacts with physical sensor inputs or how the physical operation of the aircraft is actively modified). Therefore, the “prediction information regarding inertia information at each point on the candidate flight path” is interpreted as a result-oriented solution rather than an actual technological improvement and thus does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(f)(1).
The “learning information configured by machine learning methods” is used to generally apply the abstract idea without limiting how the “machine learning methods” function. The “machine learning methods” reasonably encompass a computer with a generic machine learning model to apply the abstract idea. The step of “acquiring learning information” only recites the outcome of “acquiring…” without any details about how the outcomes are accomplished. See 2024 AI SME Update.
Merely limiting the estimation to a particular environment (i.e. candidate flight path of an aircraft) constitutes a field-of-use limitation that does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(h).
On page 12 of Remarks, with respect to step 2B, the Applicant contends that the claims recite aircraft-specific learning information, engine condition estimation tied to flight path and operating time, and inertia related prediction based on real-flight training data, which are not shown to be well-understood, routine, or conventional, and therefore provide an inventive concept.
The Examiner respectfully disagrees. The limitations pertaining to “learning information,” “engine combustor outlet temperature,” “candidate flight path,” “engine operating time,” “prediction information regarding inertia information,” and “real-time condition information” merely define the data being analyzed. The use of technology-specific data inputs (e.g., engine combustor outlet temperature) in a generic “estimation” or “prediction” step is merely conventional data analysis applied to a specific field (i.e. aircraft).
As discussed above, claims 6 and 20 have been determined to be eligible, due to reciting a specific technical improvement in neural network architecture (i.e. “a neural network with a recursive structure” combined with “an attention mechanism pooling layer to share condition within the neural network used for each of the two or more other aircrafts flying simultaneously with the target aircraft”), whereas the “learning information configured by machine learning methods” in claim 16 merely recites a generic application of machine learning methods. Applying standard machine learning methods to technology-specific data is not an inventive concept.
Rejections under 35 U.S.C. 112(b)
The amendment filed 6/1/2026 has corrected the errors under 35 U.S.C. 112(b) indicated in the Office Action mailed 6/1/2026; however, the amendment presents new errors, with respect to claims 1, 16, and 18, as discussed below.
Claim Interpretation under 35 U.S.C. 112(f)
The limitations interpreted under 35 U.S.C. 112(f) have been removed from the amendment filed 6/1/2026.
Rejections under 35 U.S.C. 102 and 103
Applicant’s arguments with respect to the claims have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Specifically, due to the amendment filed 6/1/2026, new combinations of references have been applied to claims 6, 7, and 20, and claims 1-3, 5, 8-15, and 16-18 have been indicated as including allowable subject matter below.
Key to Interpreting this Office Action
To enhance clarity, claim language is underlined throughout this Office Action, except within 35 U.S.C. 101 rejections, which follow distinct formatting guidelines detailed therein.
Claim Objections
Claims 1, 6, 14, 16, 18, and 20 are objected to because of the following informalities:
Claim 1 recites acquire related information regarding the candidate flight path and comprising restraint condition with respect to flight of the target aircraft (emphasis added). The limitation of “restraint condition” should recite “a restraint condition” or “restraint conditions,” depending on the Applicant’s intention. Claim 18 is objected to for similar reasons.
Claim 1 recites the limitations of:
the related information comprises an estimated result of an engine combustor outlet temperature of the target aircraft, by applying input information based on the candidate flight path to learning information corresponding to characteristics of the target aircraft,
the executed program further causes the processor to acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor (emphasis added).
The second recitation of the emphasized “estimated result” is assumed to be referencing the “combustor outlet temperature.” For proper claim construction that is clear and consistent, it is recommended to amend the limitation of “the estimated result of the engine combustor” to recite “the estimated result of the engine combustor outlet temperature.” Claim 18 is objected to for similar reasons.
Claim 6 recites an attention mechanism pooling layer to share condition within the neural network (emphasis added). The limitation of “condition” should instead recite “conditions” or “a condition,” depending on the Applicant’s intention. Claim 20 is objected to for similar reasons.
Claim 14 recites the limitation of information regarding condition of atmosphere (emphasis added). This limitation should instead recite “information regarding a condition of the atmosphere” or “information regarding conditions of the atmosphere,” depending on the Applicant’s intention. The “atmosphere” may be considered an inherent feature of the environment.
Claim 16 recites the limitation of the related information is acquired by, followed by the “acquiring,” “applying,” and “acquiring” steps. There should be a colon at the end of this limitation to properly indicate a list of steps.
Claim 16 recites the limitation of information regarding condition of the atmosphere (emphasis added). This limitation should instead recite “information regarding a condition of the atmosphere” or “information regarding conditions of the atmosphere,” depending on the Applicant’s intention.
Claim 16 recites:
acquiring learning information configured by machine learning methods using two or more pairs of learning input information comprising weather information and condition information acquired for a flight of one aircraft, and learning output information comprising inertia-related information measured at each point on a flight path of the one aircraft,
applying input information comprising the weather information and condition information… (emphasis added).
Given that both the “learning input information” and “input information” comprise the same information (i.e. weather information and condition information), these limitations should be amended to be the same limitation with proper antecedent basis.
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 1-3, 5, and 9-18 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.
Claim 1 recites the limitation of the maintenance cost in the last two lines of claim 1. There is insufficient antecedent basis for this limitation in the claim. Specifically, the limitation of “information regarding maintenance costs” is provided in the preceding limitation of the executed program further causes the processor to acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor. One of ordinary skill in the art cannot reasonably determine if the singular “maintenance cost” is referencing the “information regarding maintenance costs” or is to be interpreted as a separate and distinct limitation. Claim 18 is rejected under 35 U.S.C. 112(b) for similar reasons.
Claim 16 recites the limitations of each point on a flight path of the one aircraft and each point on the candidate flight path of the target aircraft. One of ordinary skill in the art cannot reasonably determine the scope of these limitations, given that a plurality of points associated with the respective flight paths has not been defined in the claim, and a flight path is known to be a continuous trajectory in space and time that includes an infinite number of points.
Claims 2, 3, 5, and 9-15 are rejected under 35 U.S.C. 112(b) for incorporating the errors of claim 1 by dependency.
Claim 17 is rejected under 35 U.S.C. 112(b) for incorporating the errors of claim 16 by dependency.
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 1-3, 5, and 9-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis of Claim 1
Claim 1. An information processing device comprising:
a processor; and
a non-transitory memory storing a program, wherein:
the program, when executed by the processor, causes the processor to:
acquire, from one or more sensors provided to a target aircraft, real-time conditions of the target aircraft;
acquire a candidate flight path that the target aircraft is supposed to follow;
acquire related information regarding the candidate flight path and comprising restraint condition with respect to flight of the target aircraft; and
display, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path and the related information that enables a pilot of the target aircraft to modify the candidate flight path, wherein:
the related information comprises an estimated result of an engine combustor outlet temperature of the target aircraft, by applying input information based on the candidate flight path to learning information corresponding to characteristics of the target aircraft,
the executed program further causes the processor to acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor, and
the output information includes flight information that minimizes the maintenance cost or makes the maintenance cost fall within an allowable maintenance cost.
101 Analysis - Step 1: Statutory category - Yes
The claim recites an apparatus. The claim falls within one of the four statutory categories. MPEP 2106.03
101 Analysis - Step 2A Prong one evaluation: Judicial Exception - Yes - Mental processes and Certain Methods of Organizing Human Activity
The claim is to be analyzed to determine whether it recites subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) mental processes, and/or c) certain methods of organizing human activity.
The Office submits that the foregoing bolded limitations constitute judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the claim covers performance using mental processes.
The claim recites the limitation of the related information comprises an estimated result of an engine combustor outlet temperature of the target aircraft, by applying input information based on the candidate flight path to learning information corresponding to characteristics of the target aircraft. Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of an “estimated result of an engine combustor outlet temperature” is data pertaining to an engine combustor outlet temperature and does not require active operation of the “target aircraft.” The broadest reasonable interpretation of “candidate flight path,” in light of the overall claim and Applicant's disclosure, is data pertaining to a potential flight path and does not require active operation of the “target aircraft” along the “candidate flight path.” The broadest reasonable interpretation of “characteristics of the target aircraft,” in light of the overall claim and Applicant's disclosure, is data pertaining to aircraft characteristics and does not require operation of the “target aircraft” in any particular manner. The generally recited “related information” is defined by the “estimated result,” and the generally recited “learning information” is defined by the “characteristics.” The broadest reasonable interpretation of “input information,” in light of the overall claim and Applicant's disclosure, is data being input. The overall limitation encompasses a pilot observing a planned flight route (i.e. “candidate flight path”) and observing historical performance tables regarding how a specific aircraft operated (i.e. “learning information”), such that the pilot then mentally maps the planned flight route against the historical performance tables to estimate “an engine combustor outlet temperature.”
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper. For example, the claim encompasses a person looking at data collected (i.e. input information, learning information, and candidate flight path) and forming a simple observation and evaluation (i.e. providing an estimated result of an engine combustor outlet temperature). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III).
The claim recites the limitation of acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor. Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “information regarding maintenance costs” is data pertaining to maintenance costs and does not require any automated maintenance operations of the “target aircraft.” The broadest reasonable interpretation of “engine operating time,” in light of the overall claim and Applicant's disclosure, is data pertaining to an operating time of an engine and does not require any active operations of the “target aircraft.” The overall limitation encompasses an analyst mentally identifying the maintenance cost associated with running an engine for a particular amount of time at a particular engine combustor outlet temperature. Broad terms like “acquire” do not require specific hardware and may be reasonably associated with mental processes.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper. For example, the claim encompasses a person looking at data collected (i.e. engine operating time and the estimated result of the engine combustor) and forming a simple observation and evaluation (i.e. determine information regarding maintenance costs using an engine operating time and the estimated result of the engine combustor outlet temperature). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III).
The claim recites the limitation of the output information includes flight information that minimizes the maintenance cost or makes the maintenance cost fall within an allowable maintenance cost. Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “flight information” is data pertaining to flight and does not require any active operation of the aircraft. The broadest reasonable interpretation of “maintenance cost,” in light of the overall claim and Applicant's disclosure, is data representative of a cost/score that influences aircraft maintenance, and the limitation of “allowable maintenance cost” is data representative of a threshold associated with the cost. The generally recited “output information” is defined by the “flight information.” This limitation encompasses a pilot mentally weighing flight control options based on their associated maintenance costs, e.g., lower flight speeds may be defined as having lower “maintenance costs” than higher flight speeds.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper. For example, the claim encompasses a person looking at data collected (i.e. maintenance cost and allowable maintenance cost) and forming a simple observation and evaluation (i.e. determine flight information that minimizes the maintenance cost or makes the maintenance cost within an allowable maintenance cost). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III).
Additionally, this limitation may be interpreted as Certain Methods of Organizing Human Activity, such that choosing a flight path (i.e. “flight information”) based on a business optimization goal (i.e. minimizing “allowable maintenance cost”) would be considered a fundamental economic practice.
The recitation of the “processor” as performing the claimed operations is recited at a high level of generality and merely uses a computer (i.e. processor) as a tool to perform the processes which does not preclude the claims from reciting the abstract process when tested per MPEP 2106.04(a)(2)(III)(C)#3.
Thus, the claim recites, describes, or sets forth a mental process.
101 Analysis - Step 2A Prong two evaluation: Practical Application - No
The claim is evaluated for whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined potions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”).
The claim recites additional elements of:
a processor; and
a non-transitory memory storing a program, wherein:
the program, when executed by the processor, causes the processor to:
acquire, from one or more sensors provided to a target aircraft, real-time conditions of the target aircraft;
acquire a candidate flight path that the target aircraft is supposed to follow;
acquire related information regarding the candidate flight path and comprising restraint condition with respect to flight of the target aircraft;
display, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path and the related information that enables a pilot of the target aircraft to modify the candidate flight path.
The “acquire real-time conditions” step is recited at a high level of generality (i.e. as a general acquiring of real-time conditions of the aircraft) and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “one or more sensors” are generic sensors that are merely claimed as a source of the generally recited data, and therefore, the “one or more sensors” do not impose meaningful limits on the claim. See MPEP 2106.05(b)(III).
The “acquire a candidate flight path” step is recited at a high level of generality (i.e. as a general acquiring of a candidate flight path) and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “candidate flight path” does not require active operation of the aircraft along the flight path, due to being defined as a path “that the target aircraft is supposed to follow.”
The “acquire related information” step is recited at a high level of generality (i.e. as a general acquiring of related information regarding the candidate flight path and comprising restraint condition) and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). While the “constraint condition” is defined as being “with respect to flight of the target aircraft,” no active control operations of the aircraft are claimed; therefore, the “restraint condition” may pertain to historical or simulated flight of the aircraft.
The “display” step is recited at a high level of generality (i.e. as a general display of output information that enables a pilot of the target aircraft to modify the candidate flight path) and amounts to post-solution activity based on generally recited data (i.e. condition information, candidate flight path, and related information), which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). As discussed above, the “candidate flight path” is defined as being a path “that the target aircraft is supposed to follow” and does not require active control of the aircraft along the “candidate flight path;” therefore, modifications made to the “candidate flight path” may pertain to modifications of stored data.
No technological details are recited with respect to the “display” itself. Specifically, when tested per MPEP 2106.05(f)(1), such limitation is interpreted as a result-oriented solution rather than an actual technological improvement. Thus, the “display” is found not to integrate the abstract idea into a practical application or provide significantly more.
The “processor” and “non-transitory memory” merely describes how to generally “apply” the otherwise mental judgements in a generic or general-purpose computing environment. The processor and memory are recited at a high level of generality and is merely automating the claimed steps, which does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(f).
101 Analysis - Step 2B evaluation: Inventive concept - No
The claim is evaluated for whether the claim as a whole amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the acquire and display steps were considered to be insignificant extra-solution activity in Step 2A, and thus, they are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The background recites the aircraft as conventional. The specification describes the acquired “condition information,” “candidate flight path,” and “related information” as encompassing stored data and the display as encompassing pre-flight briefings, where the processor and associated memory are disclosed as conventional. MPEP 2106.05(d)(II), and the cases cited therein, including Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016), OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014), but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014), indicate that storing and retrieving information in memory, and receiving or transmitting data over a network are well-understood, routine, and conventional functions when claimed in a merely generic manner, as it is here. Thus, the claim is ineligible.
101 Analysis of Dependent Claims 2, 3, 5, and 9-15
Dependent claims 2, 3, 5, and 9-15 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of the dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application.
Claim 2 recites the additional elements of: wherein the candidate flight path is acquired based on past flight paths flown by aircrafts in the past.
The broadest reasonable interpretation of “past flight paths,” in light of the overall claim and Applicant's disclosure, is data representative of past flights. Broad terms like “acquired” do not require specific hardware and may be reasonably associated with mental processes.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper. For example, the claim encompasses a person looking at data collected (i.e. past flight paths flown by aircrafts in the path) and forming a simple observation and evaluation (i.e. acquire the candidate flight path). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III).
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 2 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
Claim 3 recites the additional elements of: wherein the related information further comprises information regarding airspace facility usage fees for the candidate flight path, and the flight information is output so as to minimize a total cost or make the total cost fall within an allowable cost.
The broadest reasonable interpretation of “information regarding airspace facility usage fees,” in light of the overall claim and Applicant's disclosure, is data that describes airspace facility usage fees. The broadest reasonable interpretation of “total cost” is data representative of a cost/score, and the broadest reasonable interpretation of “allowable cost” is data representative of a threshold associated with the cost. This limitation encompasses a pilot may mentally weighing flight control options based on their associated costs, e.g., lower flight speeds may be defined as having lower “costs” than higher flight speeds.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper. For example, the claim encompasses a person looking at data collected (i.e. total cost and allowable cost) and forming a simple observation and evaluation (i.e. determine flight information that minimizes a total cost or makes the total cost fall within an allowable cost). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III).
Additionally, this limitation may be interpreted as Certain Methods of Organizing Human Activity, such that choosing a flight path (i.e. “flight information”) based on a business optimization goal (i.e. “allowable cost”) would be considered a fundamental economic practice.
Further limiting the “related information” to include information regarding airspace facility usage fees for the candidate flight path represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 3 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
Claim 5 recites the additional elements of: wherein the executed program causes the processor to acquire two or more candidate flight paths that the target aircraft is supposed to follow, and acquire information indicating a recommended flight path for the target aircraft based on whether each of the candidate flight paths satisfies specified recommendation conditions, based on specified information designating one or more of specified factors for each candidate flight path and values of respective factors.
Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “recommended flight path” is data pertaining to a recommended flight path and does not require any active operation of the aircraft. Similar to claim 1, the broadest reasonable interpretation of “candidate flight paths,” in light of the overall claim and Applicant's disclosure, is data pertaining to a potential flight path and does not require active operation of the “target aircraft” along the “candidate flight paths.” The broadest reasonable interpretation of “specified recommendation conditions,” in light of the overall claim and Applicant's disclosure, is data associated with requirements of the “candidate flight paths,” and the broadest reasonable interpretation of “specified information” that designates “specified factors” and “values of respective factors” are merely generic data associated with “candidate flight paths.” The claim encompasses an analyst looking at flight paths on a map and mentally identifying whether each flight meets various operational constraints. Broad terms like “acquiring” do not require specific hardware and may be reasonably associated with mental processes.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper. For example, the claim encompasses a person looking at data collected (i.e. each candidate flight path and specified recommendation conditions) and forming a simple observation and evaluation (i.e. acquire information indicating a recommended flight path based on whether each of the candidate flight paths satisfies specified recommendation conditions). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III).
The recitation of the “processor” as performing the claimed operations is recited at a high level of generality and merely uses a computer (i.e. processor) as a tool to perform the processes which does not preclude the claims from reciting the abstract process when tested per MPEP 2106.04(a)(2)(III)(C)#3.
The “acquire two or more candidate flight paths” step is recited at a high level of generality (i.e. as a general acquiring two or more candidate flight paths) and amounts to mere data gathering, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “candidate flight paths” does not require active operation of the aircraft along the flight path, due to being defined as paths “that the target aircraft is supposed to follow.”
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 5 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
Claim 9 recites the additional elements of: wherein the executed program further causes the processor to acquire congestion information indicating a congestion level at a destination of the target aircraft based on information regarding another aircraft heading to a same destination, and the output information is obtained based on the congestion information.
Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “congestion information” is data pertaining to a level of congestion at a destination. The broadest reasonable interpretation of “information regarding another aircraft,” in light of the overall claim and Applicant's disclosure, is data pertaining to another aircraft. Defining the “another aircraft” as “heading to a same destination” further describes the aircraft without requiring any active control of the aircraft to generate the “information.” Broad terms like “acquire” do not require specific hardware and may be reasonably associated with mental processes.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper. For example, the claim encompasses a person looking at data collected (i.e. information regarding another aircraft) and forming a simple observation and evaluation (i.e. acquire congestion information), and a person looking at data collected (i.e. congestion information) and forming a simple observation and evaluation (i.e. obtain output information). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III).
The recitation of the “processor” as performing the claimed operations is recited at a high level of generality and merely uses a computer (i.e. processor) as a tool to perform the processes which does not preclude the claims from reciting the abstract process when tested per MPEP 2106.04(a)(2)(III)(C)#3.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 9 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
Claim 10 recites the additional elements of: wherein the output information corresponds to timing of the target aircraft arriving at the destination based on the congestion information and the condition information.
Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “timing of the target aircraft arriving at the destination” is data pertaining to a time of arrival. No active control operations of the “target aircraft” are claimed.
Further limiting the “output information” to correspond to timing of the target aircraft arriving at the destination based on the congestion information and the condition information represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 10 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
Claim 11 recites the additional elements of: wherein the executed program further causes the processor to acquire information regarding at least one other aircraft different from the target aircraft, and the congestion information comprises information of the destination based on the information regarding the at least one other aircraft currently flying.
The broadest reasonable interpretation of “information regarding at least one other aircraft different from the target aircraft,” in light of the overall claim and Applicant's disclosure, is data pertaining to another aircraft. The limitation that defines the “other aircraft” as “currently flying” merely describes the general circumstance in which the “information” is associated. No particular aircraft sensors or controlled aircraft operations are claimed.
The “acquire information” step is recited at a high level of generality (i.e. as a general acquiring of information regarding at least one other aircraft) and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Further limiting the “congestion information” to include information of the destination based on the information regarding the at least one other aircraft currently flying represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract.
The “processor” is recited at a high level of generality and is merely automating the “acquire information” step, which does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(f).
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 11 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
Claim 12 recites the additional elements of: wherein the output information comprises information regarding changing flight condition of the target aircraft based on the congestion information and the condition information while the target aircraft is flying.
The broadest reasonable interpretation of “information regarding changing flight condition,” in light of the overall claim and Applicant's disclosure, is data pertaining to a changing flight condition and does not require actively acquiring data from particular sensors onboard the aircraft. While the “target aircraft” is defined as “flying,” this merely describes the circumstances in which the generally recited data is generated.
Further limiting the “output information” to include information regarding changing flight condition of the target aircraft based on the congestion information and the condition information while the target aircraft is flying represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 12 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
Claim 13 recites the additional elements of: wherein the output information comprises information for visually displaying the congestion level at the destination by time zone in which the target aircraft arrives.
Further limiting the “output information” to include information for visually displaying the congestion level at the destination by time zone in which the target aircraft arrives represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract.
No technological details are recited with respect to the step of “visually displaying.” Specifically, when tested per MPEP 2106.05(f)(1), such limitation is interpreted as a result-oriented solution rather than an actual technological improvement. Thus, the limitation of “visually displaying” is found not to integrate the abstract idea into a practical application or provide significantly more.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 13 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
Claim 14 recites the additional elements of: wherein the executed program further causes the processor to acquire weather information comprising information regarding condition of atmosphere, the related information comprises prediction results of turbulence intensity in an area corresponding to the candidate flight path based on the weather information, and the output information comprises information correlating the prediction results of turbulence intensity.
Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “weather information” is data pertaining to weather that includes an atmospheric condition. The broadest reasonable interpretation of “prediction results of turbulence intensity,” in light of the overall claim and Applicant's disclosure, is data pertaining to predicted turbulence. Simply defining the “candidate flight path” as associated with an “area” does not incorporate any particular location-based operations or services.
The “acquire weather information” step is recited at a high level of generality (i.e. as a general acquiring of weather information comprising information regarding condition of atmosphere) and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Further limiting the “related information” to include prediction results of turbulence intensity in an area corresponding to the candidate flight path based on the weather information represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract.
Further limiting the “output information” to include information correlating the prediction results of turbulence intensity represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract.
The “processor” contributes only nominally or insignificantly to the execution of the claimed method (e.g., in an insignificant extra-solution activity step or in a field-of-use limitation) and is merely an object on which the method operates (e.g., “acquire” step); therefore, the processor limitation does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(b).
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 14 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
Claim 15 recites the additional elements of: wherein the output information comprises information for displaying an image that illustrates the prediction results of turbulence intensity overlaid on the candidate flight path.
Further limiting the “output information” to include information for displaying an image that illustrates the prediction results of turbulence intensity overlaid on the candidate flight path represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract.
No technological details are recited with respect to the step of “displaying an image.” Specifically, when tested per MPEP 2106.05(f)(1), such limitation is interpreted as a result-oriented solution rather than an actual technological improvement. Thus, the limitation of “displaying an image” is found not to integrate the abstract idea into a practical application or provide significantly more.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 15 is not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
101 Analysis of Claim 16
Claim 16. An information processing device comprising a weather information acquisition unit that acquires comprising:
a processor; and
a non-transitory memory storing a program, wherein:
the program, when executed by the processor, causes the processor to:
acquire, from one or more sensors provided to a target aircraft, real-time condition information regarding conditions of the target aircraft;
acquire a candidate flight path that the target aircraft is supposed to follow;
acquire related information regarding the candidate flight path;
acquire weather information comprising information regarding condition of the atmosphere; and
display, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path, the related information and the weather information that enables a pilot of the target aircraft to modify the candidate flight path,
wherein the related information is acquired by
acquiring learning information configured by machine learning methods using two or more pairs of learning input information comprising weather information and condition information acquired for a flight of one aircraft, and learning output information comprising inertia-related information measured at each point on a flight path of the one aircraft,
applying input information comprising the weather information and condition information of the target aircraft, to the learning information, and
acquiring prediction information regarding inertia information at each point on the candidate flight path of the target aircraft,
the inertia information comprises disturbance in movement of the target aircraft, and
the output information includes flight information that minimizes the disturbance of the target aircraft.
101 Analysis - Step 1: Statutory category - Yes
The claim recites an apparatus. The claim falls within one of the four statutory categories. MPEP 2106.03
101 Analysis - Step 2A Prong one evaluation: Judicial Exception - Yes - Mental processes and Mathematical concepts
The claim is to be analyzed to determine whether it recites subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) mental processes, and/or c) certain methods of organizing human activity.
The Office submits that the foregoing bolded limitations constitute judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the claim covers performance using mental processes.
The claim recites the limitation of acquiring learning information configured by machine learning methods using two or more pairs of learning input information comprising weather information and condition information acquired for a flight of one aircraft, and learning output information comprising inertia-related information measured at each point on a flight path of the one aircraft.
Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “learning information” is data derived from “machine learning methods.” The limitation of “weather information” is data pertaining to weather, and the limitation of “condition information” is data pertaining to a condition of the “target aircraft.” The generally recited “learning input information” is defined by the “weather information” and “condition information.” The limitation of “inertia-related information” is data pertaining to inertia at each point on a flight path. The generally recited “learning output information” is defined by the “inertia-related information.” The limitation of “measured at each point on a flight path of the one aircraft” merely describes the generally recited data (i.e. “inertia-related information”), without requiring active operations of the aircraft itself.
This limitation encompasses mathematical calculations in which parameters (i.e. “learning information”) are generated using training pairs (i.e. “learning input information”), which is a known method of supervised learning. Supervised learning is fundamentally a system of mathematical equations. Because the limitation recites explicitly performing a mathematical calculation, the limitation, as drafted, falls within the mathematical concepts grouping of abstract ideas.
The claim recites the limitation of applying input information comprising the weather information and condition information of the target aircraft, to the learning information.
When interpreting this limitation in light of the limitation of “acquiring learning information configured by machine learning methods,” this limitation encompasses machine learning inference, which operates entirely using mathematical calculations. Therefore, the “applying” step may reasonably encompass the underlying mathematical equations on two sets of generally recited data (i.e. “weather information” and “condition information”), and thus, the limitation, as drafted, falls within the mathematical concepts grouping of abstract ideas.
The claim recites the limitation of acquiring prediction information regarding inertia information at each point on the candidate flight path of the target aircraft.
Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “inertia information” is data pertaining to inertia. While the “inertia information” is associated with each point on the “candidate flight path,” no particular active control operations of the aircraft are claimed, and thus, the limitation encompasses an analyst observing a flight path on a map and mentally predicting inertia values at various locations along the flight path. Broad terms like “acquiring” do not require specific hardware and may be reasonably associated with mental processes.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper. For example, the claim encompasses a person looking at data collected (i.e. candidate flight path) and forming a simple observation and evaluation (i.e. acquiring prediction information regarding inertia information at each point on the candidate flight path). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III).
The recitation of the “processor” as performing the claimed steps is recited at a high level of generality and merely uses a computer (i.e. processor) as a tool to perform the processes which does not preclude the claims from reciting the abstract process when tested per MPEP 2106.04(a)(2)(III)(C)#3.
Thus, the claim recites, describes, or sets forth a mental process.
101 Analysis - Step 2A Prong two evaluation: Practical Application - No
The claim is evaluated for whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined potions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”).
The claim recites additional elements of:
a processor;
a non-transitory memory storing a program,
the program, when executed by the processor, causes the processor to:
acquire, from one or more sensors provided to a target aircraft, real-time condition information regarding conditions of the target aircraft;
acquire a candidate flight path that the target aircraft is supposed to follow;
acquire related information regarding the candidate flight path;
acquire weather information comprising information regarding condition of the atmosphere; and
display, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path, the related information and the weather information that enables a pilot of the target aircraft to modify the candidate flight path,
the inertia information comprises disturbance in movement of the target aircraft,
the output information includes flight information that minimizes the disturbance of the target aircraft.
The “acquire real-time conditions” step is recited at a high level of generality (i.e. as a general acquiring of real-time conditions of the aircraft) and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “one or more sensors” are generic sensors that are merely claimed as a source of the generally recited data, and therefore, the “one or more sensors” do not impose meaningful limits on the claim. See MPEP 2106.05(b)(III).
The “acquire a candidate flight path” step is recited at a high level of generality (i.e. as a general acquiring of a candidate flight path) and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “candidate flight path” does not require active operation of the aircraft along the flight path, due to being defined as a path “that the target aircraft is supposed to follow.”
The “acquire related information” step is recited at a high level of generality (i.e. as a general acquiring of related information regarding the candidate flight path) and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “acquire weather information” step is recited at a high level of generality (i.e. as a general acquiring of weather information) and amounts to mere data gathering which is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “display” step is recited at a high level of generality (i.e. as a general display of output information that enables a pilot of the target aircraft to modify the candidate flight path) and amounts to post-solution activity based on generally recited data (i.e. condition information, candidate flight path, related information, and weather information), which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). As discussed above, the “candidate flight path” is defined as being a path “that the target aircraft is supposed to follow” and does not require active control of the aircraft along the “candidate flight path;” therefore, modifications made to the “candidate flight path” may pertain to modifications of stored data.
No technological details are recited with respect to the “display” itself. Specifically, when tested per MPEP 2106.05(f)(1), such limitation is interpreted as a result-oriented solution rather than an actual technological improvement. Thus, the “display” is found not to integrate the abstract idea into a practical application or provide significantly more.
Further limiting the “inertia information” to include disturbance in movement of the target aircraft represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract, and further limiting the “output information” to include flight information that minimizes the disturbance of the target aircraft represents a mere narrowing of the abstract idea (step 2A prong one) and does not impose meaningful limits on the claim beyond what has already been identified as abstract
The “processor” and “non-transitory memory” merely describes how to generally “apply” the otherwise mental judgements in a generic or general-purpose computing environment. The processor and memory are recited at a high level of generality and is merely automating the claimed steps, which does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(f).
101 Analysis - Step 2B evaluation: Inventive concept - No
The claim is evaluated for whether the claim as a whole amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the acquire and display steps were considered to be insignificant extra-solution activity in Step 2A, and thus, they are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The background recites the aircraft as conventional. The specification describes the acquired “condition information,” “candidate flight path,” “related information,” and “weather information” as encompassing stored data and the display as encompassing pre-flight briefings, where the processor and associated memory are disclosed as conventional. MPEP 2106.05(d)(II), and the cases cited therein, including Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016), OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014), but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014), indicate that storing and retrieving information in memory, and receiving or transmitting data over a network are well-understood, routine, and conventional functions when claimed in a merely generic manner, as it is here. Thus, the claim is ineligible.
101 Analysis of Dependent Claim 17
Dependent claim 17 does not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of the dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application.
Claim 17 recites the additional elements of: wherein the executed program causes the processor to acquire two or more candidate flight paths that the target aircraft is supposed to follow, and the related information comprises information indicating a recommended flight path for the target aircraft, based on whether each of the candidate flight paths satisfies recommendation conditions based on the prediction information.
Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “recommended flight path” is data pertaining to a recommended flight path and does not require any active operation of the aircraft. Similar to claim 16, the broadest reasonable interpretation of “candidate flight paths,” in light of the overall claim and Applicant's disclosure, is data pertaining to a potential flight path and does not require actual operation of the “target aircraft” along the “candidate flight paths.” The broadest reasonable interpretation of “recommendation conditions,” in light of the overall claim and Applicant's disclosure, is data associated with recommendations of the “candidate flight paths.” The claim encompasses an analyst looking at flight paths on a map and mentally identifying whether each flight meets various constraints related to the predicted inertia. Broad terms like “indicating” do not require specific hardware and may be reasonably associated with mental processes.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper. For example, the claim encompasses a person looking at data collected (i.e. each candidate flight path, recommendation conditions, and prediction information) and forming a simple observation and evaluation (i.e. determine information indicating a recommended flight path based on whether each of the candidate flight paths satisfies recommendation conditions). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III).
The “acquire two or more candidate flight paths” step is recited at a high level of generality (i.e. as a general acquiring two or more candidate flight paths) and amounts to mere data gathering, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “candidate flight paths” does not require active operation of the aircraft along the flight path, due to being defined as paths “that the target aircraft is supposed to follow.”
The “processor” contributes only nominally or insignificantly to the execution of the claimed method (e.g., in an insignificant extra-solution activity step or in a field-of-use limitation) and is merely an object on which the method operates (e.g., “acquire” step); therefore, the processor does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(b).
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B). Therefore, dependent claim 17 is not patent eligible under the same rationale as provided for in the rejection of independent claim 16.
101 Analysis of Claim 18
Claim 18. An information processing method, comprising:
acquiring, from one or more sensors provided to a target aircraft, real-time condition information regarding conditions of the target aircraft;
acquiring a candidate flight path that the target aircraft is supposed to follow;
acquiring related information regarding the candidate flight path and comprising restraint condition with respect to flight of the target aircraft; and
displaying, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path and the related information that enables a pilot of the target aircraft to modify the candidate flight path, wherein:
the related information comprises an estimated result of an engine combustor outlet temperature of the target aircraft, by applying input information based on the candidate flight path to learning information corresponding to characteristics of the target aircraft,
the method further comprise acquiring information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor, and
the output information includes flight information that minimizes the maintenance cost or makes the maintenance cost fall within an allowable maintenance cost.
101 Analysis - Step 1: Statutory category - Yes
The claim recites a method including at least one step. The claim falls within one of the four statutory categories. MPEP 2106.03
101 Analysis - Step 2A Prong one evaluation: Judicial Exception - Yes - Mental processes
An analysis similar to that of independent claim 1 is made for independent claim 18 in step 2A prong one.
101 Analysis - Step 2A Prong two evaluation: Practical Application - No
An analysis similar to that of independent claim 1 is made for independent claim 18 in step 2A prong two.
101 Analysis - Step 2B evaluation: Inventive concept - No
An analysis similar to that of independent claim 1 is made for independent claim 18 in step 2B.
Thus, the claim is ineligible.
Claims 1-3, 5, and 9-18 are thus found ineligible under 35 U.S.C. §101 as directed to an abstract idea, with the additional computer-based elements, as tested above, not integrating the abstract idea into a practical application (Step 2A prong two) or providing significantly more (Step 2B).
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.
Claims 6 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over del Pozo de Poza et al. (US 2013/0317733 A1), hereinafter Poza, in view of Xu et al. (“Multi-Aircraft Trajectory Collaborative Prediction Based on Social Long Short-Term Memory Network,” April 19, 2021, MDPI), hereinafter Xu.
Claim 6
Poza discloses the claimed information processing device comprising a processor and a non-transitory memory storing a program (see ¶0039, regarding that a computer is provided with a computer readable medium having a stored computer program comprising instructions that when executed on the computer, cause the computer to perform the methods), wherein the program, when executed by the processor, causes the processor to:
acquire a candidate flight path (i.e. user-preferred trajectory) that the target aircraft is supposed to follow (see ¶0069, with respect to Figure 3, regarding that aircraft 16 establishes contact with air traffic management 12 and transmits the user-preferred trajectory information 42 expressed as user-preferred aircraft intent data 28a to air traffic management 12, which is used by trajectory computation infrastructure 36 to produce the corresponding trajectory, as described in ¶0070);
acquire related information regarding the candidate flight path and comprising restraint condition with respect to flight of the target aircraft (see ¶0070, regarding that the user-preferred trajectory is analyzed by traffic management logic 34 in order to detect potential conflicts with other aircraft trajectories using applicable minimum inter-aircraft distances, described in ¶0107; ¶0162, regarding that the separation distance is considered a hard constraint, and other objectives may be considered, e.g., fairness, operating costs, environmental impact, and user-preferred arrival time constraints, as well as terminal area constraints described in ¶0168).
Poza further discloses that communication between aircraft 16 and air traffic management 12 is performed by ADS-B (see ¶0058). ADS-B is known to one of ordinary skill in the art to be used for transmitting aircraft state vectors of position, speed, and altitude derived from an onboard satellite navigation system. Additionally, Poza discloses that the method is performed repeatedly by air traffic management 12 to account for variable conditions that may affect the calculated trajectories, such that repetition of the method is used to check that aircraft 16 are indeed following the user-preferred and revised trajectories and that the airspace remains free of predicted conflicts (see ¶0084). One of ordinary skill in the art would not be capable of checking compliance with user-preferred and revised trajectories without “real-time condition information” acquired from “one or more sensors provided to a target aircraft;” therefore, Poza may inherently disclose the step of acquire, from one or more sensors provided to a target aircraft, real-time condition information regarding conditions of the target aircraft.
Xu further teaches this inherency with respect to similar data being acquired from sensors of an aircraft by a ground station for similar trajectory prediction and conflict detection operations (see abstract; Figure 1). Specifically, Xu teaches the known technique of acquiring a state vector (longitude, latitude, altitude, speed, and angle) of an aircraft (similar to the aircraft state of Poza) (see first paragraph of section 2.4) using ADS-B data (see Acknowledgements on page 20) for showing the real-time position and representative trajectory of the aircraft (see first paragraph of section 4.5).
Since the systems of Poza and Xu are directed to the same purpose, i.e. predicting trajectories of a plurality of aircraft, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the aircraft state of Poza to be real-time condition information regarding conditions of the target aircraft acquired from one or more sensors provided to a target aircraft, in light of Xu, with the predictable result of using ADS-B-derived state vectors as appropriate input (Acknowledgements on page 20 of Xu) to ensure safe and orderly operation of aircraft (abstract of Xu) for the trajectory prediction of Poza, where variable conditions such as unexpected winds may give rise to conflicts that were not previously predicted (¶0084 of Poza).
Poza, as modified by Xu, further discloses that the processor is caused to display, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path and the related information that enables a pilot of the target aircraft to modify the candidate flight path (see ¶0064, regarding trajectory computation infrastructure 32 displays a trajectory corresponding to revised aircraft intent data 28 provided by the ground-based automation system 22 such that the pilot may approve the revised trajectory, which is generated from a conflict detection process 110 that considers aircraft state (“condition information”) and the aircraft’s user-preferred aircraft intent 28a (“candidate flight path”), as described in ¶0102-0106, and constraints (“related information”), described in at least ¶0107; ¶0062, regarding trajectory computation infrastructure 32 is part of the flight computer of aircraft 16).
Poza further discloses that the executed program further causes the processor to acquire location prediction information showing future positions of two or more other aircrafts different from the target aircraft in a time series (see ¶0106, regarding that trajectory computation infrastructure 36 predicts the trajectories within its sector for all aircraft 16 in aircraft list 405 from the current simulation time forward, such that the aircraft state at each prediction time step for all aircraft is provided), the related information is acquired using the location prediction information (see ¶0107-0111, regarding that the conflict detection process 110 starts calculating the evolution of the inter-aircraft distances for all possible aircraft pairs along the prediction timeline, such that a conflict occurs when the predicted inter-aircraft distance between two aircraft 16 falls below the applicable minimum during a certain time interval; ¶0070, regarding that the user-preferred trajectory is analyzed by traffic management logic 34 in order to detect potential conflicts with other aircraft trajectories).
Poza does not disclose that the “location prediction information” is acquired by applying input information to a neural network with a recursive structure, such that the location prediction information is acquired for each of the two or more of the other aircrafts using a prediction model including an attention mechanism pooling layer to share condition within the neural network used for each of the two or more other aircrafts flying simultaneously with the target aircraft. However, Poza further teaches that any of its algorithms may be varied or entirely replaced (see ¶0066); therefore, it would be obvious to use a prediction model including an attention mechanism pooling layer to “acquire the location prediction information” of Poza, in light of Xu.
Specifically, Xu teaches the known technique of realizing multi-aircraft trajectory collaborative prediction (similar to the step of acquire location prediction information of Poza) by applying input information to a neural network with a recursive structure (see abstract, regarding that a model based on the S-LSTM network is used to realize the multi-aircraft trajectory collaborative prediction, where the LSTM NN is an extension of the recurrent NN, as described in the first paragraph in section 3.1; page 10, section 3.4, regarding that the trained S-LSTM model is used to predict the entire trajectory through continuous iteration). Xu further teaches that the multi-aircraft trajectory collaborative prediction is performed using a prediction model including an attention mechanism pooling layer to share condition within the neural network used for each aircraft (similar to the two or more other aircrafts flying simultaneously with the target aircraft of Poza) (see abstract, regarding that the model establishes an LSTM network for each aircraft and a pooling layer to integrate the hidden states of the associated aircraft, which can effectively capture the interaction between them; section 3.2, with respect to Figures 3 and 4, regarding that a pool-based S-LSTM model that can simultaneously predict all aircraft trajectories in the scene; section 5, regarding the improvement of the S-LSTM network by using an attention mechanism).
In case the “attention mechanism” is not explicitly taught by Xu, Xu teaches that including this feature to the S-LSTM network (i.e. “prediction model”) would be an improvement to the S-LSTM network (see section 5); therefore, given no technical details of the “attention mechanism” are claimed, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the prediction model including a pooling layer of Xu to further include an attention mechanism, in light of section 5 of Xu, with the predictable result of using a popular element attention mechanism in neural networks to complete similar tasks, thus making the neural network focus on processing a small part of the useful information in a large amount of input information and ignore other information (last paragraph of section 5 of Xu).
Since the systems of Poza and Xu are directed to the same purpose, i.e. predicting trajectories of a plurality of aircraft, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the step of acquire location prediction information of Poza to be performed by applying input information to a neural network with a recursive structure, such that the location prediction information is acquired for each of the two or more of the other aircrafts using a prediction model including an attention mechanism pooling layer to share condition within the neural network used for each of the two or more other aircrafts flying simultaneously with the target aircraft, in light of Xu, with the predictable result of providing a model for accurately predicting flight trajectories (abstract of Xu), which may be reasonably substituted for the algorithms used for predicting flight trajectories of Poza (see ¶0066).
Claim 20
The combination of Poza and Xu teach the claimed information processing method, as discussed in the rejection of claim 6.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Poza in view of Xu, and in further view of Wise et al. (US 2010/0145599 A1), hereinafter Wise.
Claim 7
Poza further discloses that the related information is acquired while the target aircraft is flying (see ¶0057, with respect to Figure 1, regarding that aircraft 16 is passing through airspace 10 under control of air traffic management facility 12).
Poza does not further disclose that the output information comprises information for displaying positions of one or more of the two or more other aircrafts after a first period and a second period and positions of the target aircraft after the first period and the second period on a map. However, including the display of the target aircraft and other aircraft positions with respect to different time periods would be obvious, in light of Wise.
Specifically, Wise teaches the known technique of displaying nearby aircraft 308 depicted in Figures 3 and 4 (similar to the positions of one or more of the other aircraft taught by Poza) after a first period and a second period (see Figures 3 and 4, depicting nearby aircraft 308 and its projected flight trajectory 310 and predicted protected air space 312 for nearby aircraft 308, described in ¶0032 as further including additional aircraft of interest) and first aircraft 302 (similar to the positions of the target aircraft taught by Poza) after the first period and the second period on a map (see Figures 3 and 4, depicting first aircraft 302 and its projected flight trajectory 304 and predicted protected air space 306 for first aircraft 302, as described in ¶0030). Similar to Poza, Wise further teaches that the projected flight trajectory path of aircraft 302 may be altered (see ¶0034). The limitations of “first period” and “second period” are broadly claimed and are not defined with respect to time or space.
Since the systems of Poza and Wise are directed to the same purpose, i.e. predicting aircraft trajectories, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the output information of Poza to comprise information for displaying the positions of one or more of the other aircraft after a first period and a second period and the positions of the target aircraft after the first period and the second period on a map, in light of Wise, with the predictable result of quickly and accurately allowing pilots to assess aircraft separation (¶0007 of Wise).
Allowable Subject Matter
Per MPEP 2106.05(I), the novelty of any elements or steps in a process or even the process itself, is of no relevance in determining whether the subject matter of a claim falls within the §101 categories of possibly patentable subject matter. A claim for a new abstract idea is still an abstract idea.
Claims 1-3, 5, and 9-18 would be allowable if rewritten to overcome the rejections under 35 U.S.C. 112(b) and 35 U.S.C. §101 set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Claim 8 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
With respect to claims 1 and 18, the closest prior art of record, Sindlinger et al. (US 2018/0137765 A1), hereinafter Sindlinger, Mattikalli et al. (US 2023/0192304 A1), hereinafter Mattikalli, DiRusso et al. (US 2019/0121369 A1), hereinafter DiRusso, and Malta et al. (US 2017/0259944 A1), hereinafter Malta, taken alone or in combination, does not teach the claimed information processing method and information processing device comprising:
a processor; and
a non-transitory memory storing a program, wherein:
the program, when executed by the processor, causes the processor to:
acquire, from one or more sensors provided to a target aircraft, real-time conditions of the target aircraft;
acquire a candidate flight path that the target aircraft is supposed to follow;
acquire related information regarding the candidate flight path and comprising restraint condition with respect to flight of the target aircraft; and
display, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path and the related information that enables a pilot of the target aircraft to modify the candidate flight path, wherein:
the related information comprises an estimated result of an engine combustor outlet temperature of the target aircraft, by applying input information based on the candidate flight path to learning information corresponding to characteristics of the target aircraft,
the executed program further causes the processor to acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor, and
the output information includes flight information that minimizes the maintenance cost or makes the maintenance cost fall within an allowable maintenance cost.
Specifically, as discussed in detail in the Office Action mailed 3/2/2026, Sindlinger teaches a similar system (see Figure 3) that performs the method comprising the steps of acquire, from one or more sensors provided to a target aircraft, real-time conditions of the target aircraft (see ¶0019; ¶0016, with respect to Figure 2), acquire a candidate flight path that the target aircraft is supposed to follow (see ¶0019-0020; ¶0017), acquire related information regarding the candidate flight path (see ¶0020; ¶0030), and display, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path and the related information that enables a pilot of the target aircraft to modify the candidate flight path (see ¶0020). However, Sindlinger does not teach the “related information” as comprising restraint condition with respect to flight of the target aircraft, nor does Sindlinger teach that the related information comprises an estimated result of an engine combustor outlet temperature of the target aircraft, by applying input information based on the candidate flight path to learning information corresponding to characteristics of the target aircraft, such that the steps further comprise to acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor, and the output information includes flight information that minimizes the maintenance cost or makes the maintenance cost fall within an allowable maintenance cost.
As discussed in the Office Action mailed 3/2/2026, the application of Mattikalli depended on a broad interpretation necessitated by the 35 U.S.C. 112(b) indefiniteness rejections. Because the amendment filed 6/1/2026 resolves the 35 U.S.C. 112(b) issues and narrows the scope of the claim, Mattikalli cannot reasonably be construed to teach the limitations not taught by Sindlinger.
Upon further search and consideration of the amendment filed 6/1/2026, DiRusso and Malta have been identified as most relevant prior art.
Specifically, DiRusso teaches a similar method (see Figure 11) performed by a processor (i.e. FMC 138, described as a flight management computer in ¶0048) caused to acquire, from one or more sensors provided to a target aircraft, real-time conditions of the target aircraft (see ¶0049, regarding FMC 138 is in communication with various sensors, so as to receive information indicating altitude from aircraft altitude sensor, as described in ¶0062, perform continuous monitoring of variation in weight and altitude of the aircraft during the climb phase, as described in ¶0111, and determine the temperature at a turbine stage within the engine via a sensor measurement, as described in ¶0112), acquire a candidate flight path that the target aircraft is supposed to follow (see ¶0107, regarding determining a climb trajectory prior to flight), acquire related information regarding the candidate flight path and comprising restraint condition with respect to flight of the target aircraft (see ¶0095-0096, regarding the use of range constraints associated with airspeed, climb thrust, and rate of climb to minimize a multi-object function; ¶0098, regarding the additional constraint for internal temperature of the engine), display, on a display device within the target aircraft, output information generated based on the candidate flight path and the related information (see ¶0055, regarding that FMC 138 generates a display of a GUI in the cockpit showing climb thrust derate options for crew selection; ¶0076, regarding the aircraft crew enters the desired aircraft cruise insertion point), and acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft (see ¶0092, regarding that engine maintenance cost is established as a function of a given temperature within the engine and may be a function of a duration of time that the engine spends operating within a predetermined temperature range), the output information includes flight information that minimizes the maintenance cost or makes the maintenance cost fall within an allowable maintenance cost (see ¶0094-0097, regarding minimizing the multi-objective function includes engine maintenance cost, where RCM 138 varies rate of climb of the aircraft based on the engine maintenance cost information, as described in ¶0113).
However, DiRusso teaches the “output information” as being pre-flight (see Figure 4, with respect to preflight flight crew inputs 136C), such that any flight modifications are performed automatically by the FMC (see ¶0078), and therefore, DiRusso does not teach the displayed “output information” as generated based on the condition information, defined as “real-time condition information regarding conditions of the target aircraft” in a preceding claim element, that enables a pilot of the target aircraft to modify the candidate flight path. DiRusso also does not teach that the related information comprises an estimated result of an engine combustor outlet temperature of the target aircraft, by applying input information based on the candidate flight path to learning information corresponding to characteristics of the target aircraft and thus does not further teach that the step of “acquire information regarding maintenance costs” uses the estimated result of the engine combustor.
Malta teaches a method (see Figure 2) performed by a processor (i.e. probabilistic model platform 150, described in ¶0012-0015) caused to acquire related information regarding the candidate flight path (see ¶0021, regarding a maximum threshold value that the exhaust gas temperature value will not exceed, defined by an operator, as described in ¶0033), the related information comprises an estimated result of an engine combustor outlet temperature of a target aircraft, by applying input information to learning information corresponding to characteristics of the target aircraft (see ¶0027-0029, regarding a Gaussian mixture model is employed to capture the relationship between exhaust gas temperature and other variables calculated from historical aircraft data recorded during flight and is used to derive the probability of exhaust gas temperature exceedance given other variables that the airline has the ability to change, where the model may instead be an artificial intelligence model, as described in ¶0020; ¶0023-0024, with respect to Figure 3, regarding the various “characteristics of the target aircraft” that are used in the calculation of exhaust gas temperature probability distribution). However, the “input information” described in ¶0023 of Malta is not based on a candidate flight path, and Malta further fails to acquire information regarding maintenance costs of the target aircraft using an engine operating time of the target aircraft and the estimated result of the engine combustor. While Malta teaches a display on user platforms 170 (see ¶0013-0016, with respect to Figure 1), Malta does not teach this display as being provided onboard an aircraft, and therefore, Malta fails to teach the step of display, on a display device within the target aircraft, output information…the output information includes flight information that minimizes the maintenance cost or makes the maintenance cost fall within an allowable maintenance cost.
No reasonable combination of prior art can be made to teach the claimed invention. The claimed invention would not have been obvious before the effective filing date.
With respect to claim 8, the closest prior art of record, Poza, Xu, and Roberts et al. (US 2009/0005960 A1), hereinafter Roberts, taken alone or in combination, does not teach that the claimed related information comprises information regarding changing the candidate flight path of the target aircraft which is obtained based on the location prediction information, when it is determined that future relationship between the target aircraft and one or more of the two or more other aircrafts satisfies relationship conditions based on issuance history of control instructions in air traffic control while the target aircraft is flying, in light of the overall claim.
Specifically, the combination of Poza and Xu does not further teach the “related information,” defined in claim 6, as further comprising “information regarding changing the candidate flight path of the target aircraft which is obtained based on the location prediction information, when it is determined that future relationship between the target aircraft and one or more of the two or more other aircrafts satisfies relationship conditions based on issuance history of control instructions in air traffic control while the target aircraft is flying,” as in claim 8.
Roberts teaches information regarding changing the candidate flight path of the target aircraft which is obtained based on the location prediction information (see ¶0126, regarding evaluating tentative or “what-if” trajectories before issuing instructions to the pilot, where the new tentative trajectory is employed by the trajectory predictor 1082 for that aircraft, as described in ¶0135-0136; ¶0089, regarding trajectory predictor 1082 calculates, for each aircraft, a set of future trajectory points, starting with the known present position of the aircraft and predicting forward in time based on predicted rate of change of position and other variables to the next point) when it is determined that future relationship between pairs of aircraft (similar to the target aircraft and one or more of the two or more other aircrafts of Poza) satisfies relationship conditions (see ¶0091, regarding that medium term conflict detector 1084 detects spatial interactions between pairs of aircraft, where a given air traffic controller may need to be aware of 20 aircraft within the sector) while an aircraft (similar to the target aircraft of Poza) is flying (see ¶0023, with respect to Figure 1).
However, Roberts does not determine that the “future relationship” satisfies “relationship conditions” based on issuance history of control instructions in air traffic control. Roberts further teaches its display as being associated with a ground station (see ¶0028-0029, with respect to Figure 1), not “a display device within the target aircraft,” as defined in claim 1, in which the display is generated “based on…the related information.”
No reasonable combination of prior art can be made to teach the claimed invention, in light of the overall claim. The overall claimed invention would not have been obvious to one of ordinary skill before the effective filing date.
With respect to claim 16, the closest prior art of record, Sindlinger, Tucker et al. (US 2021/0199685 A1), hereinafter Tucker, and Hochwarth et al. (US 2019/0304314 A1), hereinafter Hochwarth, taken alone or in combination, does not teach the claimed information processing device comprising a weather information acquisition unit that acquires comprising:
a processor; and
a non-transitory memory storing a program, wherein:
the program, when executed by the processor, causes the processor to:
acquire, from one or more sensors provided to a target aircraft, real-time condition information regarding conditions of the target aircraft;
acquire a candidate flight path that the target aircraft is supposed to follow;
acquire related information regarding the candidate flight path;
acquire weather information comprising information regarding condition of the atmosphere; and
display, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path, the related information and the weather information that enables a pilot of the target aircraft to modify the candidate flight path,
wherein the related information is acquired by
acquiring learning information configured by machine learning methods using two or more pairs of learning input information comprising weather information and condition information acquired for a flight of one aircraft, and learning output information comprising inertia-related information measured at each point on a flight path of the one aircraft,
applying input information comprising the weather information and condition information of the target aircraft, to the learning information, and
acquiring prediction information regarding inertia information at each point on the candidate flight path of the target aircraft,
the inertia information comprises disturbance in movement of the target aircraft, and
the output information includes flight information that minimizes the disturbance of the target aircraft.
Specifically, as discussed in detail in the Office Action mailed 3/2/2026, Sindlinger teaches a similar system (see Figure 3) that performs the method comprising the steps of acquire, from one or more sensors provided to a target aircraft, real-time conditions of the target aircraft (see ¶0019; ¶0016, with respect to Figure 2), acquire a candidate flight path that the target aircraft is supposed to follow (see ¶0019-0020; ¶0017), acquire related information regarding the candidate flight path (see ¶0020; ¶0030), acquire weather information comprising information regarding condition of the atmosphere (see ¶0027; ¶0016), and display, on a display device within the target aircraft, output information generated based on the condition information, the candidate flight path, the related information, and the weather information that enables a pilot of the target aircraft to modify the candidate flight path (see ¶0020). However, Sindlinger does not teach that the related information is acquired by acquiring learning information configured by machine learning methods using two or more pairs of learning input information comprising weather information and condition information acquired for a flight of one aircraft, and learning output information comprising inertia-related information measured at each point on a flight path of the one aircraft, applying input information comprising the weather information and condition information of the target aircraft, to the learning information, and acquiring prediction information regarding inertia information at each point on the candidate flight path of the target aircraft, the inertia information comprises disturbance in movement of the target aircraft, and the output information includes flight information that minimizes the disturbance of the target aircraft.
As discussed in the Office Action mailed 3/2/2026, the application of Tucker depended on a broad interpretation necessitated by the 35 U.S.C. 112(b) indefiniteness rejections. Because the amendment filed 6/1/2026 resolves the 35 U.S.C. 112(b) issues and narrows the scope of the claim, Tucker cannot reasonably be construed to teach the limitations not taught by Sindlinger.
Upon further search and consideration of the amendment filed 6/1/2026, Hochwarth has been identified as most relevant prior art.
Specifically, Hochwarth teaches the technique of applying input information comprising the weather information and condition information of the target aircraft (see ¶0027, regarding predicting a trajectory for completion of the flight based on performance data 56 for aircraft 10 and real-time weather data 52), acquiring prediction information regarding inertia information at each point on the candidate flight path of the target aircraft (see ¶0044, regarding each aircraft uses its data combined with exchanged data to interpolate new weather data along its projected route, including a turbulence event, which is determined automatically by repeatedly sampling the inertial reference system’s accelerator outputs at high frequency), the inertia information comprises disturbance in movement of the target aircraft (see ¶0044, regarding that turbulence events are determined automatically by repeatedly sampling the inertial reference system’s accelerator outputs at high frequency), the output information includes flight information that minimizes the disturbance of the target aircraft (see ¶0039, regarding that display 21 presents multiple predicted trajectories along with their associated weather conditions to a pilot for selection of a desired trajectory from a list including an automatically-generated recommendation, where trajectories can be predicted to avoid turbulent weather conditions, as described in ¶0045).
However, Hochwarth does not teach acquiring learning information configured by machine learning methods using two or more pairs of learning input information comprising weather information and condition information acquired for a flight of one aircraft, and learning output information comprising inertia-related information measured at each point on a flight path of the one aircraft, and therefore, Hochwarth further does not teach that the “input information” is applied to the learning information.
No reasonable combination of prior art can be made to teach the claimed invention. The claimed invention would not have been obvious to one of ordinary skill in the art before the effective filing date.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Specifically, Sadeghian et al. (“SoPhi: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints,” September 2018, arXiv) teaches that the model that incorporates an attention mechanism outperforms the (no attention) S-LSTM and S-GAN baselines (see section 4.1), and Tieftrunk et al. (US 2016/0057032 A1) teaches displaying a flight tracking map that integrates graphical representations of regions of interest that include turbulence and air traffic based on an external monitoring system overlying the projected flight path of the aircraft (see ¶0024).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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