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 .
DETAILED ACTION
Claims 1-20 are presented for examination.
Claims 1, 8 and 15 were amended.
This is a Non-Final Action.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06/12/2026 has been entered.
Response to Arguments
Applicant’s arguments with respect to claim(s) s 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
101 rejection has been obviated due to applicants amendments to the claims as well are arguments in remarks dated 06/12/2026.
With respect to applicants argument in view of 103 rejection, specifically, in regard to:
Argument 1 on page 12: Examiner respectfully disagrees with the applicant. Applicant’s argument is not persuasive because the rejection relies on the combined teaching not Idupunur alone. Dhulipudi teaches receiving aeronautical feature data in AIXM format. Plantinga teaches comparing fields, records or data of current cycle or newest version of aviation navigation data with one or more previous cycle or versions and identifying information that is different or outside a predetermined range as an indication of “differentness”. Plantinga further teaches recursively comparing fields, records or data between at least two cycles. Indupunur separately teaches determining the flight related criticality of aeronautical information using criticality module and predefined domain rules, thereby supplying the claimed specified flight alert criteria. Thus the combination teaches receiving AIXM aviation data, comparing current aviation feature information against a previously released version to identify changes and evaluating such changes according to predefined flight criticality criteria.
Argument 2 on page 13: Examiner respectfully disagrees with the applicant. Applicant argues Dhulipudi does not teach comparing the valid time of the AIXM file with AIRAC cycle effective dates. Applicant’s argument is not persuasive when the claim is given its BRI and considered with Plantinga. Dhulipudi expressly teaches receiving AIXM aerodrome feature data and processing aeronautical navigation information in accordance with the Aeronautical Information Regulation and Contol (AIRAC) cycle, which it identifies as a 28 day data generation cycle. Under BRI the claim valid time encompasses the period or effectivity during which an aeronautical feature is valid. Plantinga supplies the explicit comparative processing missing from Dhulipudi by comparing current cycle aviation data with prior cycle/version data and determining whether fields, records or data are the same, different or outside a predetermined range. Accordingly, Dhulipudi supplies the AIXM/AIRAC temporal framework while Plantinga supplies the actual comparison and discrepancy detection functionality. Thus the combination teaches this limitation.
Argument 3 on page 14: Examiner respectfully disagrees with the applicant. Lissajoux teaches dynamically determining one or more adjustment recommendations based on received avionic data, the current flying context and predetermined data, and subsequently rendering those recommendations to the crew. Idupunur complements this teaching with database driven processing of identified aeronautical information. Fig 2 retrieves domain rules from a database and applies them to NOTAM information, while its navigation data architecture retrieves aviation features from navigation and airport database for association with identified aeronautical information. Thus, Lissajoux teaches generation of the proposed solution/recommendation, while Idupunur teaches generating responsive aviation information through cross-referencing identified aviation information which stored aviation data. Thus, the combination teaches the limitation.
Furthermore, applicant argued that the “recommendations of Lissajoux are generated from real-time in-flight sensor readings, not from a ground-side cross-reference of an identified AIXM feature change against an aviation database” Examiner respectfully is not persuaded with this argument. Applicant’s characterization of Lissajoux is too narrow. Lissajoux explicitly teaches determining adjustment recommendations based not only on received avionics data and the flying context but also on predetermined data (paragraph 56) further explains that such predetermined data may include data relating to ground-based equipment, data supplied by users, logged recommendations, and predetermined flight procedures.
Examiner respectfully believes that the applicant is viewing the claim mapping based on individual references as the combination of references, however the combination of references teaches the limitation as a whole as explained above.
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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 rejected under 35 U.S.C. 103 as being unpatentable over Lissajoux et al. (US20190389565 - IDS) in view of Dhulipudi et al. (EP 2927894) further in view of Idupunur et al. (US 10,593,214) and Plantinga et al. (US 2021/0271382)
1. Lissajoux teaches, A computer-implemented method of decision making support (Abstract – teaches assisting pilots though onboard processing and recommendations, Lissajoux), the method comprising:
using a number of processors to perform the operations of (Paragraph 32 – teaches that avionic equipment includes one or more on-board computers (means for computing, recording and storing data).”, Lissajoux);
dynamically generating, by a decision-making support system, a proposed solution (Paragraph 53 – teaches determining in the non-avionics system, one or more adjustment recommendations … based on the received avionics type data, on the flying context and/or on predetermined data; Paragraph 21 further explains that the system can provide a proposition, suggestion, advice or candidate result, Lissajoux)
displaying the feature change and the proposed solution with suggested text to a user in an interactive dashboard (Abstract, Paragraph 53 – teaches presenting operational recommendations on cockpit displays to assist the pilots with decision-making actions – discloses the cockpit display functions as the interactive dashboard through which the system presents recommendations to the users; Paragraph 26 – teaches a recommendation can include one or more words, stated in the form of text through graphic display and can include text originating from a regulatory flight procedure, Lissajoux); and
responsive to input of agreement from the user to the proposed solution (Paragraph 46 – teaches one or more recommendations are displayed then confirmed by the pilot before being implemented, Lissajoux), automatically creating a change notice with the suggested text, a business process management ticket, and a data entry into the database (Paragraph 26 – teaches a recommendation can be executable following acceptance or confirmation of the recommendation by the pilot; Fig 2:250, Paragraph 121 – teaches automated recording and processing of operational actions within onboard system once confirmation by user – the recording the accepted operational recommendations as system data corresponds to creating a record or entry in a system database, Lissajoux).
Lissajuox does not explicitly teach or suggest,
by cross-referencing the feature change with a database of aviation data;
receiving input of an Aeronautical Information Exchange Model (AIXM) file, and wherein the current data AIXM file includes a valid time for features within the current data AIXM file;
comparing the valid time of the AIXM current data file with an Aeronautical Information Regulation and Control (AIRAC) cycle effective dates;
responsive to a discrepancy between the valid time of the current data AIXM file and the AIRAC cycle effective dates, identifying a feature change for the discrepancy that is flight critical to safety of a flight, wherein identifying the feature for the discrepancy comprises comparing feature changes between the AIXM file and a previously released data file according to specified flight alert criteria.
However, Dhulipudi teaches,
receiving input of an Aeronautical Information Exchange Model (AIXM) file, and wherein the current data AIXM file includes a valid time for features within the current data AIXM file (Paragraph 19 – teaches terminal area network generator 40 receives aerodrome surface information… in a GIS aerodrome mapping database standard such as D)-272/291, AIXM or ARINC 816 – discloses AIXM format; Paragraph 21 – teaches the generator generates terminal area network every 28 days, in accordance with the AIRAC cycle, Under BRI, the “valid time” is the validity/effectivity period during which the aviation feature is valid, rather than requiring a specifically named AXIM validTime XML field, Dhulipudi);
comparing the valid time of the AIXM current data file with an Aeronautical Information Regulation and Control (AIRAC) cycle effective dates (Paragraphs 5-6 & 21 – teaches manual processing prevented data production in accordance with the AIRAC cycle which is an automatically data generation cycle every 28 days and subsequently teaches and automatic data generation every 28 days in accordance with that cycle– disclosing aeronautical database generation synchronized to the AIRAC cycle, implying evaluation of dataset timing relative to the AIRAC publication cycle, Dhulipudi).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to incorporate Dhulipudi’s aeronautical data processing and AIRAC-cycle dataset management into the decision-support of Lissajoux to enable the system to utilize standardized and regularly updated aeronautical data when generating cockpit alerts and recommendations, thereby improving the accuracy and reliability of the information presented to pilots.
However, Idupunur teaches,
by cross-referencing the feature change with a database of aviation data (Fig 3, Col 3: lines 45-59 – teaches NOTAMs 304… are matched with regular textual expressions (RegEX) 308 from a reference RegEx database 306, a graphical elements for the airspace 312 are retrieved from a navigational database 310 and associated with the text expressions of the NOTAMs, Idupunur);
responsive to a discrepancy, identifying a feature change for the discrepancy that is flight critical to safety of a flight, according to specified flight alert criteria (Claim 1 – teaches “creating a domain rules set for filter engine on board the aircraft, where the domain rule set prioritizes the bundled NOTAMs based on criticality” and “filtering the bundled NOTAMs with the filter engine” – thus teaching evaluating aeronautical notifications according o predefined rule criteria to determine the criticality of the notifications for flight operations. Under BRI, applying such rule-based criticality criteria to aeronautical data changes corresponds to determining the significance of identified aeronautical feature changes according to the specified flight-alert criteria, Idupunur).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to allow Lissajoux’s invention to be combined with Idupunur’s invention because both references are in the same field of endeavor of avionics/decision – support for pilots. The combination would enhance cockpit recommendations (Lissajoux) with validated temporal discrepancies (Idupunur) to ensure flight-critical alerts are displayed in dashboards.
Plantinga teaches,
wherein identifying the feature for the discrepancy comprises comparing feature changes between the AIXM file and a previously released data file (Paragraph 74-75, 78 – teaches determining sameness or differentness between fields, records or data of the current cycle or new version and one or more previous cycles or versions, when the current information differs or falls outside a predetermined range it is designated with an indication of differentness, by comparing of at least one field, record or data between at least two cycles or multiple disparate navigational databases, Plantinga).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to modify the combination of Lissajoux, Dhulipudi and Idupunur to incorporate Plantinga’s current versus prior navigation data comparison in order to identify changes or discrepancies in AIRAC cycles aeronautical data before evaluating criticality and generating recommendations. Such a modification would predictably improve data validation and reduce reliance on outdated or inconsistent aviation information.
2. The combination of Lissajoux, Dhulipudi, Idupunur and Plantinga teach, The method of claim 1, further comprising, responsive to a determination that the feature change is flight critical, automatically creating a flight alert. (Abstract - teaches A domain rules set for a filter engine on board the aircraft is created that prioritizes the bundled NOTAMs based on their criticality and the NOTAM messages are then displayed to the pilot on a graphical display device on board the aircraft., Idupunur)
3. The combination of Lissajoux, Dhulipudi, Idupunur and Plantinga teach, The method of claim 1, further comprising, responsive to a determination there is no discrepancy between the valid time of the AIXM file and the AIRAC cycle effective dates (Paragraph 21 – teaches terminal area network generator 40… generates terminal area networks every 28 days, in accordance with the AIRAC cycle, Dhulipudi), automatically creating only the business process management ticket and the data entry into the database. (Abstract – The prioritized critical NOTAMs are stored on board in an electronic database and retrieved during the relevant phase of the flight path of the aircraft, Idupunur)
4. The combination of Lissajoux, Dhulipudi, Idupunur and Plantinga teach, The method of claim 1, further comprising, responsive to input of disagreement from the user to the proposed solution, displaying, in the dashboard, input options to manually enter a solution and update the database. (Paragraph 46 - teaches manual operator input when rejecting or modifying a recommendation, equivalent to “dashboard input options” for manual updates, Lissajoux).
5. The combination of Lissajoux, Dhulipudi, Idupunur and Plantinga teach, The method of claim 1, wherein the features include at least one of runway identity, altitude, Airspace, Elevation, Azimuth, Route and Glidepath. (Claim 1, Paragraph 19 - teaches aerodrome and navigation datasets including runway and route information, “Terminal area network generator 40 receives aerodrome surface information, map data ("data"), in a GIS aerodrome mapping database standard such as DO-272/DO-291, AIXM or ARINC 816”, Dhulipudi)
6. The combination of Lissajoux, Dhulipudi, Idupunur and Plantinga teach, The method of claim 1, wherein the flight alert criteria is updated regularly based on industry standards. (Paragraph 21 – teaches “the terminal area network generator 40 is a land-based system and method that generates terminal area networks every 28 days, in accordance with the Aeronautical Information Regulation and Control (AIRAC) cycle.” Dhulipudi).
7. The combination of Lissajoux, Dhulipudi, Idupunur and Plantinga teach, The method of claim 1, wherein the dashboard further displays at least one of: a timeline of the feature changes; overlap of the valid time with the AIRAC cycle effective dates; a timeframe of flight alert; or a timeframe of change notice. (Paragraphs 60-65 teaches – dashboard display of contextual timelines and accessibility info. While not in the exact AIRAC phrasing, it covers temporal/timeframe visualization of recommendations, Lissajoux).
Claims 8-20 are similar to claims 1-7 hence rejected similarly.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
RAB et al. (US 2020/0202318) – teaches system and methods for recording usage of aviation software products using shared ledger database (Abstract, Fig 1).
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/AMRESH SINGH/Primary Examiner, Art Unit 2159
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