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 .
Status of Claims
This action is in reply to the amendments filed on 08/07/2025.
Claims 1, 3, 6-8, 10, 18, and 20-29 are currently pending and have been examined.
Claims 1, 18, 22-23, and 27-28 have been amended.
Claims 1, 3, 6-8, 10, 18, and 20-29 are currently rejected.
This action is made FINAL.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/07/2025 and 10/20/2025 is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant’s arguments filed 08/07/2025 have been considered but they are not persuasive.
Regarding the 101 rejections applicant argues that the claims are not “directed to a mental process” but instead provide a useful tool to a pilot. The claims as a whole are directed to determining a optimized flight path after a flight using data gathered while in flight. The claims are using generic computers to perform the mental process of determining and generating an optimal flight path and displaying the result of the mental process does not incorporate the mental process into a practical application since that is insignificant post solution activity. Per MPEP 2106.05(I)(A), “Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include:
i. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
iii. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g)); or
iv. Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook, 437 U.S. 584, 588-90, 198 USPQ 193, 197-98 (1978) (MPEP § 2106.05(h)).”
Therefore examiner is maintaining the 101 rejection.
Applicant’s arguments with regards to the art rejections have been considered and appear to be directed solely to the instant amendments to the claims. Accordingly, the claims are addressed in the body of the updated rejections below.
Applicant additionally argues the motivation to combine Dunsdon and McNally as impermissible hindsight. MPEP 2145(X)(A) states “Applicants may argue that the examiner’s conclusion of obviousness is based on improper hindsight reasoning. However, "[a]ny judgment on obviousness is in a sense necessarily a reconstruction based on hindsight reasoning, but so long as it takes into account only knowledge which was within the level of ordinary skill in the art at the time the claimed invention was made and does not include knowledge gleaned only from applicant’s disclosure, such a reconstruction is proper." In re McLaughlin, 443 F.2d 1392, 1395, 170 USPQ 209, 212 (CCPA 1971).” While McNally teaches altering and displaying the current and optimized flight path using in-flight data Dunsdon in at least paragraph [0045] makes clear the benefits of analyzing flight data after the flight has landed to “determine root causes of aircraft inefficiencies” [0045]. This would motivate one having ordinary skill in the art to apply post flight analysis to the process of McNally to arrive at the previously claimed invention. Irrgang also expresses explicit benefits of hindsight analysis further providing motivation to one having ordinary skill in the art to arrive at the claimed invention. Therefore applicants arguments of hindsight are unpersuasive.
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, 6-8, 10, 18, and 20-29 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 3, 6-8, 10, 18, and 20-29 are directed to a system, method, or product, which are/is one of the statutory categories of invention. (Step 1: YES)
The examiner has identified independent method Claim 1 as the claim that represents the claimed invention for analysis and is similar to independent system Claim 18. Claim 1 recites the limitations of:
determining, by processing circuitry after touchdown of an aircraft at a destination point, a completed flight path flown by the aircraft to the destination point;
receiving, by the processing circuitry after completion of the aircraft flying the completed flight path and from a weather radar onboard the aircraft, weather data collected while the aircraft flew the completed flight path;
receiving, by the processing circuitry, flight data for the aircraft while the aircraft flew the completed flight path;
generating, by the processing circuitry, a suggested flight path to the destination point based on the weather data and the flight data, wherein the suggested flight path is different than the completed flight path; and
outputting, by the processing circuitry, an electronic signal to cause a user interface to display the suggested flight path to the destination point and to display the completed flight path flown by the aircraft.
These limitations, under their broadest reasonable interpretation, cover performance of the limitation as mental processes. Determining a flight path and generating an output based on processing received input data recites concepts performed in the human mind. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a concept performed in the human mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. The processing circuitry in Claim 1 is just applying generic computer components to the recited abstract limitations. The recitation of generic computer components in a claim does not necessarily preclude that claim from reciting an abstract idea. Claim 18 is also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims recite an abstract idea.)
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of: receiving data and outputting data. These steps are either insignificant pre- or post- solution activity and do not integrate the mental process into a practical application since these steps are well known and routine operations. Therefore, claims 1 and 18 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application.)
The claims do not include additional elements that are sufficient to amount to significantly more that the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Accordingly, these additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. Thus, claims 1 and 18 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more.)
Dependent claims further define the abstract idea that is present in their respective independent claims 1 and 18 and thus correspond to Mental Processes and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the dependent claims are directed to an abstract idea. Thus, the claims 1, 3, 6-8, 10, 18, and 20-29 are not patent-eligible. To overcome these 101 rejections, the examiner suggests amending the claims to either add a limitation of adjusting the control of the aircraft based on the calculated suggested path or add in limitations that show that the data being processed is beyond what a person can reasonably perform in the human mind.
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
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.
Claim(s) 1 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dunsdon et. al. (US 2021/0005093), herein Dunsdon in view of McNally et. al. (US PAT 9,171,473) (from IDS), herein McNally and Irrgang et. al. (US 2015/0279218), herein Irrgang.
Regarding claim 1:
Dunsdon teaches:
A method (a method of flight optimization [abstract]) comprising:
Determining, by processing circuitry after touchdown of an aircraft at a destination point (at operation 740, the post-flight cycle 600 is performed after the flight has landed [0049]), a completed flight path flown by the aircraft to the destination point (where flight data is collected [0049]; The event measurement system 340 also receives navigational data [0045]);
receiving, by the processing circuitry after completion of the aircraft flying the completed flight path (at operation 740, the post-flight cycle 600 is performed after the flight has landed [0049]) and from a weather radar [onboard the aircraft], weather data collected while the aircraft flew the completed flight path (The event measurement system 340 also receives navigational data and global weather data 97 [0045]);
receiving, by the processing circuitry, flight data for the aircraft while the aircraft flew the completed flight path (The flight data from the aircraft 450 which is stored in the quick access recorder/flight data recorder 455 is wirelessly downloaded to the event measurement system 340 [0045]);
McNally also teaches:
A method (a method for analyzing in-flight aircraft in en-route airspace to automatically find time-saving corrections to existing weather-avoidance routes [col 2, lines 11-13]) comprising:
receiving, by processing circuitry, after completion of an aircraft flying a [completed] flight path and from a weather radar onboard the aircraft, weather data (The dynamic weather route system 102 receives current and forecast weather model data from a weather data source 122. [col 6, lines 32-34]) collected while the aircraft flew the [completed] flight path (The framework 100 comprises a dynamic weather route system 102 for generating dynamic weather routes for in-flight aircraft. [col 5, lines 33-35]);
receiving, by the processing circuitry, flight data for the aircraft (The dynamic weather route system 102 receives host radar tracking data and flight plan data from a radar data source 124. In an illustrative embodiment, the radar data source 124 is the Center Host or En Route Automation Modernization (ERAM) computer system operated by the FAA. In an embodiment, the radar track data and flight plan data are updated every 12 seconds with fresh surveillance tracking data and flight plan amendments [col 6, lines 46-55]; The dynamic weather route system 102 receives atmospheric data, including wind, temperature, and pressure data, from an atmospheric monitoring and forecast modeling source 126. In an illustrative embodiment, the atmospheric monitoring and modeling source 126 is the National Oceanic and Atmospheric Association (NOAA) Rapid Refresh atmospheric data, including wind forecasts. In an illustrative embodiment, the atmospheric data are updated every hour from the atmospheric monitoring source 126. [col 6, lines 56-64]) while the aircraft flew the [completed] flight path (FIG. 1, there is shown a block diagram of a framework 100 for dynamically routing in-flight aircraft pursuant to an illustrative embodiment of the present invention. The framework 100 comprises a dynamic weather route system 102 for generating dynamic weather routes for in-flight aircraft. [col 5, lines 30-35]);
Dunsdon does not explicitly teach, however McNally teaches:
generating, by the processing circuitry, a suggested flight path to the destination point (the processor 104 to generate dynamic weather routes for in-flight aircraft [col 6, lines 2-3]) based on the weather data (At step 208, if weather or traffic conflicts are detected on the reference route in the previous step, the dynamic weather route system 102 automatically attempts to find minimum delay reroute, referred to herein as the candidate alternate route relative to the reference route. Candidate alternate routes are further tested as described herein to determine if they meet the criteria to be the proposed as the dynamic weather route. Exemplary dynamic weather routes are shown in FIGS. 4 and 5 and are labeled as “dynamic weather route” in each of FIGS. 4 and 5. [col 12, lines 23-32]; The dynamic weather route system 102 receives current and forecast weather model data from a weather data source 122 [col 6, lines 32-33]) and the flight data (The dynamic weather route system 102 receives atmospheric data, including wind, temperature, and pressure data, from an atmospheric monitoring and forecast modeling source 126. In an illustrative embodiment, the atmospheric monitoring and modeling source 126 is the National Oceanic and Atmospheric Association (NOAA) Rapid Refresh atmospheric data, including wind forecasts. In an illustrative embodiment, the atmospheric data are updated every hour from the atmospheric monitoring source 126. [col 7, lines 46-66]),
outputting, by the processing circuitry, an electronic signal (Referring to FIG. 3, at step 218, the dynamic weather route system 102 includes a trial planner that is the user's primary tool for evaluating dynamic flight plan routes. In particular, an interactive rapid-feedback trial planner tool, which is part of the dynamic weather route system 102, enables users to quickly and easily visualize the proposed dynamic flight plan routes and modify them if necessary. [col 14, lines 27-33]; see also figs. 4-6 and 8; Traffic and weather conflict status, flying time savings, and downstream sector congestion information are updated and displayed in real-time as a user adjusts the trial plan route. [col 14, lines 34-44]) to cause a user interface to display the suggested flight path to the destination point and to display the completed (examiner notes that in light of Irrgang as shown below it would be obvious to display the actual flight path and hindsight flightpath for the operator to visually see and learn from instead of using a path optimized in real time in-flight. It would be obvious by substituting one known element for another known element to achieve a predictable result,) flight path flown by the aircraft (FIG. 8 depicts an exemplary screen shot 280 of a graphical user interface. A user may click on the list to activate a trial plan for a selected flight. Through the graphical user interface, a user is able to change the capture fix. Auxiliary waypoints may be moved through a click and drag procedure to adjust the dynamic flight plan route or to automatically snap to a nearby named fix. Auxiliary waypoint may also be added or removed the point and click actions. Traffic and weather conflict status, flying time savings, and downstream sector congestion information are updated and displayed in real-time as a user adjusts the trial plan route. [col 14, lines 34-44]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon to include the teachings as taught by McNally with a reasonable expectation of success. McNally teaches the benefits of “A dynamic weather route system automatically analyzes routes for in-flight aircraft flying in convective weather regions and attempts to find more time and fuel efficient reroutes around current and predicted weather cells. The dynamic weather route system continuously analyzes all flights and provides reroute advisories that are dynamically updated in real time while the aircraft are in flight. The dynamic weather route system includes a graphical user interface that allows users to visualize, evaluate, modify if necessary, and implement proposed reroutes. [McNally, abstract]”.
Irrgang also teaches:
determining, by processing circuitry after touchdown of an aircraft at a destination point, a completed flight path flown by the aircraft to the destination point ();
receiving, by the processing circuitry after completion of the aircraft flying the completed flight path and from a weather radar onboard the aircraft, weather data collected while the aircraft flew the completed flight path (After a flight has been performed by looking at the actual weather conditions during the particular flight to determine what would have been the most optimal flight plan. [0127]);
receiving, by the processing circuitry, flight data for the aircraft while the aircraft flew the completed flight path (A third profile 22 represents the actual flight operation of the aircraft [0090]);
Dunsdon in view of McNally does not explicitly teach, however Irrgang teaches:
generating, by the processing circuitry, a suggested flight path to the destination point based on the weather data and the flight data, wherein the suggested flight path is different than the completed flight path (the airline fuel profiler 1 can create an alternate removed/replaced flight plan 126 [0127]); and
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally to include the teachings as taught by Irrgang with a reasonable expectation of success. Irrgang teaches the benefit of “after a flight has taken place, the airline fuel profiler 1 can apply hindsight analysis to the alternate removed/replaced flight plan 126, using actual weather data to determine a hindsight optimal flight plan 128. As discussed in more detail below, the various fuel loads for each of the flight plans can be compared to calculate a cost (in fuel load) for the buffers eliminated between successive flight plans [Irrgang, 0095]”.
Regarding claim 18:
Dunsdon teaches:
A method (a method of flight optimization [abstract]) comprising:
Determining, by processing circuitry after touchdown of an aircraft at a destination point (at operation 740, the post-flight cycle 600 is performed after the flight has landed [0049]), a completed flight path flown by the aircraft to the destination point (where flight data is collected [0049]; The event measurement system 340 also receives navigational data [0045]);
receiving, by the processing circuitry after completion of the aircraft flying the completed flight path (at operation 740, the post-flight cycle 600 is performed after the flight has landed [0049]) and from a weather radar [onboard the aircraft], weather data collected while the aircraft flew the completed flight path (The event measurement system 340 also receives navigational data and global weather data 97 [0045]);
receiving, by the processing circuitry, flight data for the aircraft while the aircraft flew the completed flight path (The flight data from the aircraft 450 which is stored in the quick access recorder/flight data recorder 455 is wirelessly downloaded to the event measurement system 340 [0045]);
McNally also teaches:
A method (a method for analyzing in-flight aircraft in en-route airspace to automatically find time-saving corrections to existing weather-avoidance routes [col 2, lines 11-13]) comprising:
receiving, by processing circuitry, after completion of an aircraft flying a completed flight path and from a weather radar onboard the aircraft, weather data (The dynamic weather route system 102 receives current and forecast weather model data from a weather data source 122. [col 6, lines 32-34]) collected while the aircraft flew the completed flight path (The framework 100 comprises a dynamic weather route system 102 for generating dynamic weather routes for in-flight aircraft. [col 5, lines 33-35]);
receiving, by the processing circuitry, flight data for the aircraft (The dynamic weather route system 102 receives host radar tracking data and flight plan data from a radar data source 124. In an illustrative embodiment, the radar data source 124 is the Center Host or En Route Automation Modernization (ERAM) computer system operated by the FAA. In an embodiment, the radar track data and flight plan data are updated every 12 seconds with fresh surveillance tracking data and flight plan amendments [col 6, lines 46-55]; The dynamic weather route system 102 receives atmospheric data, including wind, temperature, and pressure data, from an atmospheric monitoring and forecast modeling source 126. In an illustrative embodiment, the atmospheric monitoring and modeling source 126 is the National Oceanic and Atmospheric Association (NOAA) Rapid Refresh atmospheric data, including wind forecasts. In an illustrative embodiment, the atmospheric data are updated every hour from the atmospheric monitoring source 126. [col 6, lines 56-64]) while the aircraft flew the completed flight path (FIG. 1, there is shown a block diagram of a framework 100 for dynamically routing in-flight aircraft pursuant to an illustrative embodiment of the present invention. The framework 100 comprises a dynamic weather route system 102 for generating dynamic weather routes for in-flight aircraft. [col 5, lines 30-35]);
Dunsdon does not explicitly teach, however McNally teaches:
generate a suggested flight path (the processor 104 to generate dynamic weather routes for in-flight aircraft [col 6, lines 2-3]) based on the stored weather data (At step 208, if weather or traffic conflicts are detected on the reference route in the previous step, the dynamic weather route system 102 automatically attempts to find minimum delay reroute, referred to herein as the candidate alternate route relative to the reference route. Candidate alternate routes are further tested as described herein to determine if they meet the criteria to be the proposed as the dynamic weather route. Exemplary dynamic weather routes are shown in FIGS. 4 and 5 and are labeled as “dynamic weather route” in each of FIGS. 4 and 5. [col 12, lines 23-32]) and the flight data of the observed flight path (The dynamic weather route system 102 receives atmospheric data, including wind, temperature, and pressure data, from an atmospheric monitoring and forecast modeling source 126. In an illustrative embodiment, the atmospheric monitoring and modeling source 126 is the National Oceanic and Atmospheric Association (NOAA) Rapid Refresh atmospheric data, including wind forecasts. In an illustrative embodiment, the atmospheric data are updated every hour from the atmospheric monitoring source 126. [col 7, lines 46-66]);
output an electronic signal (Referring to FIG. 3, at step 218, the dynamic weather route system 102 includes a trial planner that is the user's primary tool for evaluating dynamic flight plan routes. In particular, an interactive rapid-feedback trial planner tool, which is part of the dynamic weather route system 102, enables users to quickly and easily visualize the proposed dynamic flight plan routes and modify them if necessary. [col 14, lines 27-33]; see also figs. 4-6 and 8; Traffic and weather conflict status, flying time savings, and downstream sector congestion information are updated and displayed in real-time as a user adjusts the trial plan route. [col 14, lines 34-44]) to cause a user interface to display the suggested flight path to the destination point and to display the completed (examiner notes that in light of Irrgang as shown below it would be obvious to display the actual flight path and hindsight flightpath for the operator to visually see and learn from instead of using a path optimized in real time in-flight. It would be obvious by substituting one known element for another known element to achieve a predictable result,) flight path flown by the aircraft (FIG. 8 depicts an exemplary screen shot 280 of a graphical user interface. A user may click on the list to activate a trial plan for a selected flight. Through the graphical user interface, a user is able to change the capture fix. Auxiliary waypoints may be moved through a click and drag procedure to adjust the dynamic flight plan route or to automatically snap to a nearby named fix. Auxiliary waypoint may also be added or removed the point and click actions. Traffic and weather conflict status, flying time savings, and downstream sector congestion information are updated and displayed in real-time as a user adjusts the trial plan route. [col 14, lines 34-44]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon to include the teachings as taught by McNally with a reasonable expectation of success. McNally teaches the benefits of “A dynamic weather route system automatically analyzes routes for in-flight aircraft flying in convective weather regions and attempts to find more time and fuel efficient reroutes around current and predicted weather cells. The dynamic weather route system continuously analyzes all flights and provides reroute advisories that are dynamically updated in real time while the aircraft are in flight. The dynamic weather route system includes a graphical user interface that allows users to visualize, evaluate, modify if necessary, and implement proposed reroutes. [McNally, abstract]”.
Irrgang also teaches:
determining, by processing circuitry after touchdown of an aircraft at a destination point, a completed flight path flown by the aircraft to the destination point ();
receiving, by the processing circuitry after completion of the aircraft flying the completed flight path and from a weather radar onboard the aircraft, weather data collected while the aircraft flew the completed flight path (After a flight has been performed by looking at the actual weather conditions during the particular flight to determine what would have been the most optimal flight plan. [0127]);
receiving, by the processing circuitry, flight data for the aircraft while the aircraft flew the completed flight path (A third profile 22 represents the actual flight operation of the aircraft [0090]);
Dunsdon in view of McNally does not explicitly teach, however Irrgang teaches:
generating, by the processing circuitry, a suggested flight path to the destination point based on the weather data and the flight data, wherein the suggested flight path is different than the completed flight path (the airline fuel profiler 1 can create an alternate removed/replaced flight plan 126 [0127]); and
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally to include the teachings as taught by Irrgang with a reasonable expectation of success. Irrgang teaches the benefit of “after a flight has taken place, the airline fuel profiler 1 can apply hindsight analysis to the alternate removed/replaced flight plan 126, using actual weather data to determine a hindsight optimal flight plan 128. As discussed in more detail below, the various fuel loads for each of the flight plans can be compared to calculate a cost (in fuel load) for the buffers eliminated between successive flight plans [Irrgang, 0095]”.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dunsdon et. al. (US 2021/0005093), herein Dunsdon in view of McNally et. al. (US PAT 9,171,473) (from IDS), herein McNally and Irrgang et. al. (US 2015/0279218), herein Irrgang in further view of LaCivita et. al. (US 2021/0183253).
Regarding claim 3:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 1, upon which this claims is dependent.
McNally further teaches:
generating, by the processing circuitry, a respective suggested flight path (the processor 104 to generate dynamic weather routes for in-flight aircraft [col 6, lines 2-3]);
comparing, by the processing circuitry, each respective suggested flight path to the respective historical flight path (a method for analyzing in-flight aircraft in en-route airspace to automatically find time-saving corrections to existing weather-avoidance routes [col 2, lines 11-13]; Referring to FIG. 3, at step 212, the dynamic weather route system 102 tests the candidate alternate route that results in the minimum flying time delay relative to the reference route found in steps 208 and 210 for potential flying time savings relative to the actual current flight plan trajectory. [col 13, lines 25-29]);
calculating, by the processing circuitry, respective one or more factors based on each comparison (Referring to FIG. 3, at step 212, the dynamic weather route system 102 tests the candidate alternate route that results in the minimum flying time delay relative to the reference route found in steps 208 and 210 for potential flying time savings relative to the actual current flight plan trajectory. If the time to fly along the candidate alternate route saves more time than a preset amount, e.g., 5 minutes, the process continues to step 214. If the time saved by the proposed candidate alternate route is less than the preset amount, then the process returns to step 204. The preset amount of flying time savings may be user adjustable dependent upon workload. The preset amount of flying time savings may also be set to some value less than the trigger value for the reference route, e.g., less than 5 minutes. [col 13, lines 25-50]); and
outputting, by the processing circuitry, the electronic signal, wherein the electronic signal further comprises [each historical flight path], each respective suggested flight path (Referring to FIG. 3, at step 218, the dynamic weather route system 102 includes a trial planner that is the user's primary tool for evaluating dynamic flight plan routes. In particular, an interactive rapid-feedback trial planner tool, which is part of the dynamic weather route system 102, enables users to quickly and easily visualize the proposed dynamic flight plan routes and modify them if necessary. [col 14, lines 27-33]; see also figs. 4-6 and 8) and each of the respective one or more factors (Traffic and weather conflict status, flying time savings, and downstream sector congestion information are updated and displayed in real-time as a user adjusts the trial plan route. [col 14, lines 34-44]).
Dunsdon in view of McNally and Irrgang does not explicitly teach, however LaCivita teaches:
wherein the suggested flight path is a first suggested flight path (fig. 1, flight route 108a), the method further comprising:
retrieving, by the processing circuitry and from a memory, data indicative of a plurality of historical flight paths (FIG. 2 is a schematic block diagram of an aircraft flight strategy selection system 200, according to an example of the subject disclosure. The aircraft flight strategy selection system 200 includes a flight strategy analysis control unit 202 in communication with a historical flight strategy database 204, a historical weather database 206, a historical flight schedule database 208, and an aircraft database 210, such as through one or more wired or wireless connections. In at least one example, the flight strategy analysis control unit 202 is collocated with the historical flight strategy database 204, the historical weather database 206, the historical flight schedule database 208, and the aircraft database 210. [0035]);
for each historical flight path of the plurality of historical flight paths (At 318, the flight strategy analysis control unit 202 determines one or more days from the historical weather data 207 and the historical flight schedule data 209 that are similar to the current day. For example, the flight strategy analysis control unit 202 determines one or more historical days having weather conditions and a flight schedule that are the same as, or substantially the same as (such as within a predetermined percentage of similarity, such as 90% or more similar) the weather conditions (as determined via the weather forecast data 213) and the flight schedule (as determined via the flight schedule data 215) of the current day. [0064]; At 320, after identifying the similar day, the flight strategy analysis control unit 202 identifies the flight strategies for the similar day(s) as possible flight strategies for the current day(s). After the possible flight strategies are determined (for example, identified), at 322, the flight strategy analysis control unit 202 compares the possible flight strategies for the current day in relation to one or more metrics. [0065]), generating, by the processing circuitry, a respective suggested flight path (Each flight strategy 100a, 100b, 100c, 100d, and 100e includes a flight route 108a, 108b, 108c, 108d, and 108e, respectively, to the airport 104, which include trajectories at various positions along each of the flight routes 108a, 108b, 108c, 108d, 108e, altitudes at various positions along each of the flight routes 108a, 108b, 108c, 108d, and 108e, and airspeeds at the various positions along each of the flight routes 108a, 108b, 108c, 108d, and 108e. The trajectories, airspeeds, and altitudes at different positions along each of the flight routes 108a, 108b, 108c, 108d, and 108e may differ. For example, the trajectory, airspeed, and altitude of the aircraft 102 at a position 100 miles from the airport 104 differs from the trajectory, airspeed and altitude of the aircraft 102 at a position immediately before landing at the airport 104. [0030])
comparing, by the processing circuitry, each respective (LaCivita teaches in fig. 3, steps 316-322 to receive and compare multiple historical flight paths. While the examiner believes that LaCivita discloses enough to teach that the comparing, generating, calculating, and outputting is performed for each respective historical flight data, ultimately arriving at fig. 1 with the best suggested routes displayed based on the different factors, it would also be obvious under duplication of parts to arrive at the claimed invention. Using multiple historical data points is simply proving more data to allow for a more accurate calculation to be performed and does not create any unexpected results that makes it patentable significant. See MPEP 2144.04(VI)(B).) suggested flight path to the respective historical flight path (After the possible flight strategies are determined (for example, identified), at 322, the flight strategy analysis control unit 202 compares the possible flight strategies for the current day in relation to one or more metrics. [0065]);
calculating, by the processing circuitry, respective (LaCivita teaches in fig. 3, steps 316-322 to receive and compare multiple historical flight paths. While the examiner believes that LaCivita discloses enough to teach that the comparing, generating, calculating, and outputting is performed for each respective historical flight data, ultimately arriving at fig. 1 with the best suggested routes displayed based on the different factors, it would also be obvious under duplication of parts to arrive at the claimed invention. Using multiple historical data points is simply proving more data to allow for a more accurate calculation to be performed and does not create any unexpected results that makes it patentable significant. See MPEP 2144.04(VI)(B).) one or more factors based on each comparison (After the possible flight strategies are determined, the flight strategy analysis control unit 202 compares the possible flight strategies for the current day in relation to one or more metrics. The metrics include one or more of flight time, fuel consumption, generated noise, and the like. For example, the flight strategy analysis control unit 202 determines that the aircraft 102 flying according to the flight strategy 100c arrives at the airport 104 the quickest (for example, the flight strategy 100c is the quickest flight strategy), the aircraft 102 flying according to the flight strategy 100a generates the least amount of noise in relation to the airport 104 or one or more locations proximate to the airport 104 (for example, the flight strategy 100a is the quietest flight strategy), while the aircraft 102 flying according to the flight strategy 100d consumes the least amount of fuel (for example, the flight strategy 100d is the most fuel efficient flight strategy) [0051]); and
outputting, by the processing circuitry, the electronic signal, wherein the electronic signal further comprises each historical flight path (FIG. 1 shows a set of flight strategies 100a, 100b, 100c, 100d, and 100e that have already been used to fly aircraft to the airport 104. A particular one of the flight strategies 100a, 100b, 100c, 100d, or 100e is selected for a current or future flight, as described herein. The set of flight strategies 100a, 100b, 100c, 100d, and 100e may include more or less flight strategies than shown. [0029]), each respective suggested flight path (FIG. 1 shows a set of flight strategies 100a, 100b, 100c, 100d, and 100e that have already been used to fly aircraft to the airport 104. A particular one of the flight strategies 100a, 100b, 100c, 100d, or 100e is selected for a current or future flight, as described herein. The set of flight strategies 100a, 100b, 100c, 100d, and 100e may include more or less flight strategies than shown. [0029]) and each of the respective one or more factors (the flight strategy analysis control unit 202 presents the different possible flight strategies and associated metrics (for example, flight time, fuel consumption, and generated noise) to an individual on the display 218 of the user interface 216 [0051]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by LaCivita with a reasonable expectation of success. LaCivita teaches the benefits of “A need exists for a system and a method for efficiently identifying one or more flight strategies for aircraft that are scheduled to arrive at an airport. Further, a need exists for a system and a method for automatically selecting one or more flight strategies for aircraft that are scheduled to arrive at an airport. With those needs in mind, certain examples of the subject disclosure provide an aircraft flight strategy selection system that is configured to determine one or more possible flight strategies for an aircraft at an airport. The aircraft flight strategy selection system includes a flight strategy analysis control unit that determines the possible flight strategy(s) for the aircraft based on weather forecast data for a selected time period, flight schedule data for the selected time period, historical weather data for a prior time frame, and historical flight schedule data for the prior time frame. [LaCivita, 0006-0007]”.
Claim(s) 6, 22-23, 25, and 27-28 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dunsdon et. al. (US 2021/0005093), herein Dunsdon in view of McNally et. al. (US PAT 9,171,473) (from IDS), herein McNally and Irrgang et. al. (US 2015/0279218), herein Irrgang in further view of Baker et. al. (US 2010/0191458), herein Baker.
Regarding claim 6:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 1, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Baker teaches:
wherein generating the suggested flight path comprises generating the suggested flight path based further on one or more of an amount of fuel used (The criteria may include, but is in no way limited to, total time, time in flight, distance, overall cost, fuel required, or some other best fit heuristic. [0032]), a duration (The criteria may include, but is in no way limited to, total time, time in flight, distance, overall cost, fuel required, or some other best fit heuristic. [0032]), a time of flight takeoff to touchdown (The criteria may include, but is in no way limited to, total time, time in flight, distance, overall cost, fuel required, or some other best fit heuristic. [0032]), and exposure to weather hazards (historical weather information [0023]; the query includes current or forecast aviation weather information (i.e. winds aloft, air temperature, icing, etc.) received by Web Server 11, such as from the National Oceanic and Atmospheric Administration (NOAA), so that only the previous flight plans most closely matching the weather which should be encountered by the current flight would be considered. [0029]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Baker with a reasonable expectation of success. Baker teaches a “present invention solves a number of these inefficiencies as well as other problems present in the process of flight planning [Baker, 0004]” by “calculates an optimized route for the flight based upon aircraft performance data, available fuel costs, and up-to-date current or forecast aviation weather [Baker, 0005]”.
Regarding claim 22:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 1, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Baker teaches:
wherein to cause the user interface to display the suggested flight path and the completed flight path that the aircraft flew, the electronic signal causes the user interface to display a departure point and a destination point that is common to both the suggested flight path and the flight path that the aircraft flew (Once the user input is processed, service 10 builds a number of departure airport/destination airport combinations (step 206). In the event the origin and destination provided by the user are both specific airports, then only a single combination may be identified. [0027]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Baker with a reasonable expectation of success. Baker teaches a “present invention solves a number of these inefficiencies as well as other problems present in the process of flight planning [Baker, 0004]” by “calculates an optimized route for the flight based upon aircraft performance data, available fuel costs, and up-to-date current or forecast aviation weather [Baker, 0005]”.
Regarding claim 23:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 1, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Baker teaches:
wherein to cause the user interface to display the suggested flight path and the completed flight path that the aircraft flew, the electronic signal causes the user interface to display a first set of geographic waypoints corresponding to the suggested flight path and a second set of geographic waypoints corresponding to the completed flight path, wherein at least some geographic waypoints of the first set of geographic waypoints are not included in the second set of geographic waypoints (while column 420 gives specifics of the full route. The route displayed may be in short form or in decoded form providing the latitude and longitude of each waypoint and an associated altitude and or climb rate. [0034]; see also fig.4 displaying the different routes.).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Baker with a reasonable expectation of success. Baker teaches a “present invention solves a number of these inefficiencies as well as other problems present in the process of flight planning [Baker, 0004]” by “calculates an optimized route for the flight based upon aircraft performance data, available fuel costs, and up-to-date current or forecast aviation weather [Baker, 0005]”.
Regarding claim 25:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 18, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Baker teaches:
wherein to generate the suggested flight path, the processing circuitry is configured to generate the suggested flight path based on one or more of an amount of fuel used (The criteria may include, but is in no way limited to, total time, time in flight, distance, overall cost, fuel required, or some other best fit heuristic. [0032]), a duration (The criteria may include, but is in no way limited to, total time, time in flight, distance, overall cost, fuel required, or some other best fit heuristic. [0032]), a time of flight takeoff to touchdown (The criteria may include, but is in no way limited to, total time, time in flight, distance, overall cost, fuel required, or some other best fit heuristic. [0032]), and exposure to weather hazards (historical weather information [0023]; the query includes current or forecast aviation weather information (i.e. winds aloft, air temperature, icing, etc.) received by Web Server 11, such as from the National Oceanic and Atmospheric Administration (NOAA), so that only the previous flight plans most closely matching the weather which should be encountered by the current flight would be considered. [0029]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Baker with a reasonable expectation of success. Baker teaches a “present invention solves a number of these inefficiencies as well as other problems present in the process of flight planning [Baker, 0004]” by “calculates an optimized route for the flight based upon aircraft performance data, available fuel costs, and up-to-date current or forecast aviation weather [Baker, 0005]”.
Regarding claim 27:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 18, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Baker teaches:
wherein to cause the user interface to display the suggested flight path and the completed flight path, the electronic signal causes the user interface to display a departure point and the destination point that is common to both the suggested flight path and the flight path that the aircraft flew (Once the user input is processed, service 10 builds a number of departure airport/destination airport combinations (step 206). In the event the origin and destination provided by the user are both specific airports, then only a single combination may be identified. [0027]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Baker with a reasonable expectation of success. Baker teaches a “present invention solves a number of these inefficiencies as well as other problems present in the process of flight planning [Baker, 0004]” by “calculates an optimized route for the flight based upon aircraft performance data, available fuel costs, and up-to-date current or forecast aviation weather [Baker, 0005]”.
Regarding claim 28:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 18, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Baker teaches:
wherein to cause the user interface to display the suggested flight path and the completed flight path, the electronic signal causes the user interface to display a first set of geographic waypoints corresponding to the suggested flight path and a second set of geographic waypoints corresponding to the completed flight path, wherein at least some geographic waypoints of the first set of geographic waypoints are not included in the second set of geographic waypoints (while column 420 gives specifics of the full route. The route displayed may be in short form or in decoded form providing the latitude and longitude of each waypoint and an associated altitude and or climb rate. [0034]; see also fig.4 displaying the different routes.).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Baker with a reasonable expectation of success. Baker teaches a “present invention solves a number of these inefficiencies as well as other problems present in the process of flight planning [Baker, 0004]” by “calculates an optimized route for the flight based upon aircraft performance data, available fuel costs, and up-to-date current or forecast aviation weather [Baker, 0005]”.
Claim(s) 7-8 and 20-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dunsdon et. al. (US 2021/0005093), herein Dunsdon in view of McNally et. al. (US PAT 9,171,473) (from IDS), herein McNally and Irrgang et. al. (US 2015/0279218), herein Irrgang in further view of Baker et. al. (US 2010/0191458) and Ladurini et. al. (US 2022/0261012), herein Ladurini.
Regarding claim 7:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 1, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Baker teaches:
is trained based on a plurality of historical flight paths (With reference to flight plans herein, it should be understood that it may be the flight plans of others as filed are the source of data, but more preferably, preference may be given to data from the flight plans of others in the form approved by the FAA, or alternatively to data from flight plans that have been amended by en route changes from an actual flight taken. It can be further appreciated that a reference to flight plan data herein can also encompass historical data from an actual flight that has been completed [0030]; Database Server 12 maintains at least 1 month of historical previously filed flight plans in data store 34, and most preferably maintains at least six months [0022]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Baker with a reasonable expectation of success. Baker teaches a “present invention solves a number of these inefficiencies as well as other problems present in the process of flight planning [Baker, 0004]” by “calculates an optimized route for the flight based upon aircraft performance data, available fuel costs, and up-to-date current or forecast aviation weather [Baker, 0005]”.
Dunsdon in view of McNally and Irrgang and Baker does not explicitly teach, however Ladurini teaches:
wherein generating the suggested flight path comprises generating the suggested flight path (The systems and methods described here can leverage ML techniques to evaluate the weather data and vehicle data to determine the optimized flight route for the aerial vehicle. The systems and methods escribes use ML to examine atmospheric conditions to determine a flight route that conserves and leverages energy efficiencies to increase flight time (e.g., a mission duration). By defining a power and energy regeneration ability of the aerial vehicle, the systems and methods described herein can delineate an optimal flight route for the aerial vehicle for reaching the destination or completing the mission. [0015]) based on a machine learning model (Machine learning (ML) is a subset of artificial intelligence in which a computer uses algorithms and statistical models to accurately perform tasks without using explicitly coded instructions after having analyzed a learning or training data set, in effect relying on patterns and inferences to generalize from past experiences. ML-based systems can be capable of solving problems not previously seen or considered and for which it would not be possible to code for every individual case. [0003]) that receives the weather data (at 518, weather data (e.g., the weather data 224, as shown in FIG. 2) can be processed by the route determination module 206 [0107]) and the flight data (At 508, a route determination module (e.g., the route determination module 206, as shown in FIG. 2) can be configured to receive or retrieve the mission data and flight path data. [0106]) as input
wherein the machine learning model (Machine learning (ML) is a subset of artificial intelligence in which a computer uses algorithms and statistical models to accurately perform tasks without using explicitly coded instructions after having analyzed a learning or training data set, in effect relying on patterns and inferences to generalize from past experiences. ML-based systems can be capable of solving problems not previously seen or considered and for which it would not be possible to code for every individual case. [0003])
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang and Baker include the teachings as taught by Ladurini with a reasonable expectation of success. Ladurini teaches the benefits of “Machine learning (ML) is a subset of artificial intelligence in which a computer uses algorithms and statistical models to accurately perform tasks without using explicitly coded instructions after having analyzed a learning or training data set, in effect relying on patterns and inferences to generalize from past experiences. ML-based systems can be capable of solving problems not previously seen or considered and for which it would not be possible to code for every individual case. [Ladurini, 0003]” which is applied to optimization of a flight path, which is the same field of endeavor as the instant claims.
Regarding claim 8:
Dunsdon in view of McNally, Irrgang, Baker, and Ladurini teaches all the limitations of claim 7, upon which this claims is dependent.
Ladurini further teaches:
wherein the machine learning model comprises a neural network (Types of ML models that can be trained on the training data include artificial neural networks [0003]).
Regarding claim 20:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 18, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Baker teaches:
trained based on a plurality of historical flight paths (With reference to flight plans herein, it should be understood that it may be the flight plans of others as filed are the source of data, but more preferably, preference may be given to data from the flight plans of others in the form approved by the FAA, or alternatively to data from flight plans that have been amended by en route changes from an actual flight taken. It can be further appreciated that a reference to flight plan data herein can also encompass historical data from an actual flight that has been completed [0030]; Database Server 12 maintains at least 1 month of historical previously filed flight plans in data store 34, and most preferably maintains at least six months [0022]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Baker with a reasonable expectation of success. Baker teaches a “present invention solves a number of these inefficiencies as well as other problems present in the process of flight planning [Baker, 0004]” by “calculates an optimized route for the flight based upon aircraft performance data, available fuel costs, and up-to-date current or forecast aviation weather [Baker, 0005]”.
Dunsdon in view of McNally and Irrgang and Baker does not explicitly teach, however Ladurini teaches:
wherein to generate the suggested flight path the processing circuitry is configured to generate the suggested flight path (The systems and methods described here can leverage ML techniques to evaluate the weather data and vehicle data to determine the optimized flight route for the aerial vehicle. The systems and methods escribes use ML to examine atmospheric conditions to determine a flight route that conserves and leverages energy efficiencies to increase flight time (e.g., a mission duration). By defining a power and energy regeneration ability of the aerial vehicle, the systems and methods described herein can delineate an optimal flight route for the aerial vehicle for reaching the destination or completing the mission. [0015]) based on a machine learning model (Machine learning (ML) is a subset of artificial intelligence in which a computer uses algorithms and statistical models to accurately perform tasks without using explicitly coded instructions after having analyzed a learning or training data set, in effect relying on patterns and inferences to generalize from past experiences. ML-based systems can be capable of solving problems not previously seen or considered and for which it would not be possible to code for every individual case. [0003]), and
wherein the machine learning algorithm (Machine learning (ML) is a subset of artificial intelligence in which a computer uses algorithms and statistical models to accurately perform tasks without using explicitly coded instructions after having analyzed a learning or training data set, in effect relying on patterns and inferences to generalize from past experiences. ML-based systems can be capable of solving problems not previously seen or considered and for which it would not be possible to code for every individual case. [0003])
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang and Baker to include the teachings as taught by Ladurini with a reasonable expectation of success. Ladurini teaches the benefits of “Machine learning (ML) is a subset of artificial intelligence in which a computer uses algorithms and statistical models to accurately perform tasks without using explicitly coded instructions after having analyzed a learning or training data set, in effect relying on patterns and inferences to generalize from past experiences. ML-based systems can be capable of solving problems not previously seen or considered and for which it would not be possible to code for every individual case. [Ladurini, 0003]” which is applied to optimization of a flight path, which is the same field of endeavor as the instant claims.
Regarding claim 21:
Dunsdon in view of McNally, Irrgang, Baker, and Ladurini teaches all the limitations of claim 20, upon which this claims is dependent.
Ladurini further teaches:
wherein the machine learning model comprises a neural network (Types of ML models that can be trained on the training data include artificial neural networks [0003]).
Claim(s) 10 and 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dunsdon et. al. (US 2021/0005093), herein Dunsdon in view of McNally et. al. (US PAT 9,171,473) (from IDS), herein McNally and Irrgang et. al. (US 2015/0279218), herein Irrgang in further view of Christianson et. al. (US PAT 10,365,365), herein Christianson.
Regarding claim 10:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 1, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Christianson teaches:
wherein the weather data from the weather radar onboard the aircraft comprises one or more of storm pattern reflectivity (The enhanced weather radar processing system 104 of aircraft 200 may determine the reflectivity of each of the individual portions 331-342 of vertical column 330 as shown, and then enhanced weather radar mapping unit 106 aboard aircraft 200 may determine the VIR of vertical column 330. In particular, enhanced weather radar mapping unit 106 may first receive the reflectivity information for portions 331-342. Enhanced weather radar mapping unit 106 may then check whether any of the portions 331-342 have a reflectivity dBZ in the highest reflectivity range of over 40 dBZ in the reflectivity range divisions applicable in this example. Enhanced weather radar mapping unit 106 may detect that cells 337 and 338 have reflectivity above 40 dBZ. In response to determining that at least one of the portions of vertical column 330 is in the highest reflectivity range of greater than 40 dBZ, enhanced weather radar mapping unit 106 may then proceed to determine the VIR of the vertical column 330. [col 13, lines 15-32]), a predicted storm track (the examiner is interpreting this limitation in the alternative.), a weather cell trend (the examiner is interpreting this limitation in the alternative.), or a weather cell track (the examiner is interpreting this limitation in the alternative.).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Christianson with a reasonable expectation of success. Christianson teaches the benefits of “An aircraft may use an onboard weather radar system to detect adverse weather conditions, which may enable the flight crew to make changes to the flight plan as necessary to avoid potentially hazardous weather. An aircraft in flight may also receive weather information from ground stations. Up-to-date weather information may assist the flight crew in evaluating whether or how to modify a flight plan to avoid hazards for the flight. Airborne weather radar detects reflectivity of weather associated with precipitation. Reflectivity of a radar signal is an electrical quantity related to the percentage of power (normalized for range) returned from the weather being illuminated by the radar transmission. Reflectivity is generally related to rate of precipitation. [Christianson, col 1, lines 7-19]”
Regarding claim 26:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 18, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Christianson teaches:
wherein the weather data from the weather radar onboard the aircraft comprises one or more of storm pattern reflectivity (The enhanced weather radar processing system 104 of aircraft 200 may determine the reflectivity of each of the individual portions 331-342 of vertical column 330 as shown, and then enhanced weather radar mapping unit 106 aboard aircraft 200 may determine the VIR of vertical column 330. In particular, enhanced weather radar mapping unit 106 may first receive the reflectivity information for portions 331-342. Enhanced weather radar mapping unit 106 may then check whether any of the portions 331-342 have a reflectivity dBZ in the highest reflectivity range of over 40 dBZ in the reflectivity range divisions applicable in this example. Enhanced weather radar mapping unit 106 may detect that cells 337 and 338 have reflectivity above 40 dBZ. In response to determining that at least one of the portions of vertical column 330 is in the highest reflectivity range of greater than 40 dBZ, enhanced weather radar mapping unit 106 may then proceed to determine the VIR of the vertical column 330. [col 13, lines 15-32]), a predicted storm track (the examiner is interpreting this limitation in the alternative.), a weather cell trend (the examiner is interpreting this limitation in the alternative.), or a weather cell track (the examiner is interpreting this limitation in the alternative.).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Christianson with a reasonable expectation of success. Christianson teaches the benefits of “An aircraft may use an onboard weather radar system to detect adverse weather conditions, which may enable the flight crew to make changes to the flight plan as necessary to avoid potentially hazardous weather. An aircraft in flight may also receive weather information from ground stations. Up-to-date weather information may assist the flight crew in evaluating whether or how to modify a flight plan to avoid hazards for the flight. Airborne weather radar detects reflectivity of weather associated with precipitation. Reflectivity of a radar signal is an electrical quantity related to the percentage of power (normalized for range) returned from the weather being illuminated by the radar transmission. Reflectivity is generally related to rate of precipitation. [Christianson, col 1, lines 7-19]”
Claim(s) 24 and 29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dunsdon et. al. (US 2021/0005093), herein Dunsdon in view of McNally et. al. (US PAT 9,171,473) (from IDS), herein McNally and Irrgang et. al. (US 2015/0279218), herein Irrgang in further view of Ladurini et. al. (US 2022/0261012), herein Ladurini.
Regarding claim 24:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 1, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Ladurini teaches:
determining, by the processing circuitry, from the weather data, a direction of movement for a storm cell (the FPO system can be configured to employ ML techniques to predict a movement of one or more clouds 320 from a first cloud location (at which the one or more clouds 320 can be referred to as “Current Cloud Cover” in the example of FIG. 3) to a second cloud location (at which the one or more clouds 320 can be referred to as “Expected Cloud Cover” in the example of FIG. 3), as shown in FIG. 3. [0102]); and
generating, by the processing circuitry, the suggested flight path based further on the direction of movement for the storm cell (The predicted movement of the clouds 320 can be employed to provide the optimized flight route 302 for the aerial vehicle for executing the mission, such that the aerial vehicle avoids the clouds 320, thereby maximizing an exposure of the vehicle to a solar source (e.g., the Sun). Moreover, the FPO system can be configured to enable the aerial vehicle to take advantage of a first thermal draft 322, a second thermal draft 324, and a third thermal draft 326 located in the atmosphere by maneuvering the aerial vehicle along the thermal flight route segments 308, such as shown in FIG. 3. [0102]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Ladurini with a reasonable expectation of success. Ladurini teaches the benefits of “Machine learning (ML) is a subset of artificial intelligence in which a computer uses algorithms and statistical models to accurately perform tasks without using explicitly coded instructions after having analyzed a learning or training data set, in effect relying on patterns and inferences to generalize from past experiences. ML-based systems can be capable of solving problems not previously seen or considered and for which it would not be possible to code for every individual case. [Ladurini, 0003]” which is applied to optimization of a flight path, which is the same field of endeavor as the instant claims.
Regarding claim 29:
Dunsdon in view of McNally and Irrgang teaches all the limitations of claim 18, upon which this claims is dependent.
Dunsdon in view of McNally and Irrgang does not explicitly teach, however Ladurini teaches:
wherein the processing circuitry is further configured to: determine from the weather data a direction of movement for a storm cell (the FPO system can be configured to employ ML techniques to predict a movement of one or more clouds 320 from a first cloud location (at which the one or more clouds 320 can be referred to as “Current Cloud Cover” in the example of FIG. 3) to a second cloud location (at which the one or more clouds 320 can be referred to as “Expected Cloud Cover” in the example of FIG. 3), as shown in FIG. 3. [0102]); and
generate the suggested flight path based further on the direction of movement for the storm cell (The predicted movement of the clouds 320 can be employed to provide the optimized flight route 302 for the aerial vehicle for executing the mission, such that the aerial vehicle avoids the clouds 320, thereby maximizing an exposure of the vehicle to a solar source (e.g., the Sun). Moreover, the FPO system can be configured to enable the aerial vehicle to take advantage of a first thermal draft 322, a second thermal draft 324, and a third thermal draft 326 located in the atmosphere by maneuvering the aerial vehicle along the thermal flight route segments 308, such as shown in FIG. 3. [0102]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Dunsdon in view of McNally and Irrgang to include the teachings as taught by Ladurini with a reasonable expectation of success. Ladurini teaches the benefits of “Machine learning (ML) is a subset of artificial intelligence in which a computer uses algorithms and statistical models to accurately perform tasks without using explicitly coded instructions after having analyzed a learning or training data set, in effect relying on patterns and inferences to generalize from past experiences. ML-based systems can be capable of solving problems not previously seen or considered and for which it would not be possible to code for every individual case. [Ladurini, 0003]” which is applied to optimization of a flight path, which is the same field of endeavor as the instant claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kumar (US 2020/0290742) discloses electrically-driven propulsors for regional aircraft. These combine fans optimized for quiet regional operations with rotating variable pitch mechanisms contained within the hubs and highly efficient ring electric motors. The ring motors are used to drive annular fans at the inner or outer radius, or a conventional fan at the inner radius. The assembly combines a single fan, fixed or variable pitch, with a row of stators, or multiple counter-rotating fans without stators. Our focus is on propulsors optimized for quiet and efficient regional flights, but many elements apply to long-haul air and several other applications referred to herein.
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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Scott R. Jagolinzer
Examiner
Art Unit 3665
/S.R.J./Examiner, Art Unit 3665 /CHRISTIAN CHACE/Supervisory Patent Examiner, Art Unit 3665
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