DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Election/Restrictions
Applicant’s election without traverse of Invention I (claims 1-12) in the reply filed on 03/30/2026 is acknowledged.
Claims 13-20 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to nonelected Inventions, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 03/30/2026.
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 1-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1/7 A method for improving the fuel efficiency of an aircraft flight, the method comprising:
storing, in a flight plan data store, a flight plan for the aircraft flight, the flight plan comprising a scheduled route for the aircraft flight, a scheduled landing runway at a destination aerodrome, and a scheduled arrival time and date at the destination aerodrome;
storing, in a weather data store, predicted weather data corresponding to the vicinity of the airport at the scheduled arrival time and date;
receiving, at a first cluster mapping module of a trained machine learning prediction module, the scheduled route for the aircraft flight, the scheduled landing runway at a destination aerodrome, and the predicted weather data corresponding to the vicinity of the destination aerodrome at the scheduled arrival time and date;
determining, by the first cluster mapping module, based on the trained machine learning of the prediction module, a predicted arrival route and a predicted landing runway;
determining, by a second cluster mapping module of the trained machine learning prediction module, based on the predicted arrival route and the predicted landing runway, a plurality of descent flight trajectories for the aircraft flight;
filtering, by a trajectory filter of the trained machine learning prediction module, to obtain the most probable descent flight trajectories, each ranked by a conditional probability based on one or more environmental factors;
determining, by a distance prediction module of the trained machine learning prediction module, a distance corresponding to each of the most probable descent flight trajectories;
outputting, to a pilot, one or more of the most probable descent flight trajectories and the corresponding distances;
determining a recommended top of descent location corresponding to the distance determined for the most probable descent flight trajectory based on a desired angle of descent and windspeed data of the predicted weather data; and
outputting the recommended top of descent location to the pilot or to a flight director system of the aircraft's avionics for control of an associated autopilot system;
wherein the trained machine learning prediction model is trained based on historical aircraft flight data.
101 Analysis - Step 1: Statutory category – Yes
The claims recite a system/method. The claims fall within one of the four statutory categories. MPEP 2106.03
101 Analysis - Step 2A Prong one evaluation: Judicial Exception – Yes – Mental processes
In Step 2A, Prong one of the 2019 Patent Eligibility Guidance (PEG), a 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 limitation(s) constitutes judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the limitations can be “performed in the human mind, or by a human using a pen and paper” to solve optimization problem. See MPEP 2106.04(a)(2)(III).
The claim recites the limitation of “determining…a predicted arrival route and a predicted landing runway …”, “determining…a plurality of descent flight trajectories”, “filtering…to obtain the most probable descent flight trajectories”, “determining … a distance” and “determining a recommended top of descent location”. The limitation, as drafted, are processes that, under their broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of “the first cluster mapping module”, “a second cluster mapping module”, “trajectory filter”, and “distance prediction module”. That is, other than reciting “the first cluster mapping module”, “a second cluster mapping module”, “trajectory filter”, and “distance prediction module” nothing in the claim precludes the steps from practically being performed in the mind. For example, but for the “the first cluster mapping module”, “a second cluster mapping module”, “trajectory filter”, and “distance prediction module” language, the claim encompasses a user looking at received data to determine a optimal top of descent location. The mere nominal recitation of “the first cluster mapping module”, “a second cluster mapping module”, “trajectory filter”, and “distance prediction module” do not take the claim limitations out of the mental process grouping.
Thus, the claim recites a mental process.
101 Analysis - Step 2A Prong two evaluation: Practical Application - No
In Step 2A, Prong two of the 2019 PEG, a claim is to be evaluated whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in MPEP 2106.04(d), 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, such that the claim is more than a drafting effort designed to monopolize the judicial exception. The courts have indicated that additional elements such as: 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.”
The Office submits that the foregoing underlined limitation(s) recite additional elements that do not integrate the recited judicial exception into a practical application.
The claim recites additional elements of “the first cluster mapping module”, “a second cluster mapping module”, “trajectory filter”, and “distance prediction module”, merely describes how to generally “apply” the otherwise mental judgements using a generic or general-purpose vehicle control environment, i.e. a computer. “the first cluster mapping module”, “a second cluster mapping module”, “trajectory filter”, and “distance prediction module” are generic computer components and are recited at a high level of generality and is merely automates the storing/receiving/determining/filtering/outputting steps. The limitation “storing… a flight plan…”, “storing… predicted weather data”, “receiving…the scheduled route” are recited at a high level of generality (i.e. as a pre-solution activity of gathering data) and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The “outputting, to a pilot…” and “outputting the recommended top of descent location to the pilot…” are also recited at high level of generality (i.e. as a general means of displaying/presenting for the determining steps), and amounts to mere post solution, which is a form of insignificant extra-solution activity.
Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
101 Analysis - Step 2B evaluation: Inventive concept - No
In Step 2B of the 2019 PEG, a claim is to be evaluated as to 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. See MPEP 2106.05.
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 “storing/receiving/determining/filtering/outputting” 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 specification does not provide any indication that the “the first cluster mapping module”, “a second cluster mapping module”, “trajectory filter”, and “distance prediction module” are anything other than a conventional computer within an aircraft. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Further, the Federal Circuit in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere displaying of data is a well understood, routine, and conventional function. Accordingly, a conclusion that the determine steps are well-understood, routine, conventional activity is supported under Berkheimer.
Thus, the claims are ineligible.
Dependent claims 2-6 and 8-12 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. Therefore, dependent claims 2-6 and 8-12 are not patent eligible under the same rationale as provided for in the rejection of claims 1 and 7.
Therefore, claims 1-12 are ineligible under 35 USC §101.
Allowable Subject Matter
Claims 1-12 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter:
Wu et al. (US 9423799 B1) discloses a method/system for improving the fuel efficiency of an aircraft flight, the method comprising: storing (Col. 10, lines 25-59), in a flight plan data store (Fig. 3, adaptation parameters memory 315), a flight plan for the aircraft flight (step 602), the flight plan comprising a scheduled route for the aircraft flight (Col. 10, lines 49-54), a scheduled landing runway at a destination aerodrome (Fig. 2, airspace region), and a scheduled arrival time and date at the destination aerodrome (Col. 10, lines 25-35, descent time period); storing, in a weather data store, predicted weather data (Winds and temperature data 320) corresponding to the vicinity of the airport at the scheduled arrival time and date; receiving, the scheduled route for the aircraft flight, the scheduled landing runway at a destination aerodrome (Fig. 6, step 604, Col. 10, lines 25-59), and the predicted weather data corresponding to the vicinity of the destination aerodrome at the scheduled arrival time and date (Fig. 6, step 608, Col. 12, lines 6-13); determining, a predicted arrival route and a predicted landing runway (arrival delay model 328; col. 7, lines 46-67; "airspace arrival delay models server 412"; fig. 6, col. 12, lines 28-46; col. 14, lines 12-15); determining, based on the predicted arrival route and the predicted landing runway, a plurality of descent flight trajectories for the aircraft flight (Fig. 6, col. 12, lines 47-col. 13, line 15; col. 14, lines 16-20); filtering, to obtain the most probable descent flight trajectories ("flyability constraints metric 508 for the trajectory”, Fig. 5, col. 10, lines 1-16; col. 13, lines 21-32; col. 14, lines 16-36), each ranked based on one or more environmental factors ("a cumulative aggregated fuel consumption value 510 aggregated over the calculated trajectory of the particular flight corresponding to the particular descent profile, Fig. 5; col. 13, lines 17-21); outputting, to a pilot, one or more of the most probable descent flight trajectories and the corresponding distances (col. 13, lines 35-48; col. 13, lines 49-51; col. 14, lines 8-15); determining a recommended top of descent location (Fig. 1-2, Col. 6, lines 63-Col. 7, line 7; col. 7, lines 20-26, corresponding to the distance determined for the most probable descent flight trajectory based on a desired angle of descent and windspeed data of the predicted weather data (col. 14, lines 10-12, "using the received and retrieved flight information from the data sources"; step 608, col. 12, lines 6-19).
Wu does not disclose the use of first/second cluster mapping module of a trained machine learning prediction module; filtering to obtain the most probable descent flight trajectories are ranked by a conditional probability based on one or more environmental factors; determining, by a distance prediction module of the trained machine learning prediction module, a distance corresponding to each of the most probable descent flight trajectories; outputting the recommended top of descent location to the pilot or to a flight director system of the aircraft's avionics for control of an associated autopilot system; wherein the trained machine learning prediction model is trained based on historical aircraft flight data.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ce Li Li whose telephone number is (571)270-5564. The examiner can normally be reached M-F, 10AM-7PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Peter D Nolan can be reached at 571-270-7016. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
CE LI . LI
Examiner
Art Unit 3661
/PETER D NOLAN/Supervisory Patent Examiner, Art Unit 3661
Prosecution Insights