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 Office Action is in response to the application filed on February 1, 2024. Claims 1-20 are pending. Claims 1, 11 and 20 are independent.
Priority
Receipt is acknowledged of certified copies of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement
The information disclosure statements (IDSs) submitted on September 23, 2024 and September 23, 2025 have been considered. The submission is in compliance with the provisions of 37 CFR 1.97. The Forms PTO-1449 are signed and attached hereto.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 – 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claims 1 and 20 are directed to a method (i.e., a process), and claim 11 is directed to a system. Therefore, claim 1 is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection.
Claim 1 recites:
1. A computer-implemented method, the computer-implemented method comprising:
receiving runway data associated with a runway;
receiving runway condition data associated with a plurality of sections of the runway, wherein the runway condition data is aggregated from a plurality of runway condition data sources, and wherein the runway condition data indicates a surface condition associated with at least one section of the plurality of sections of the runway;
generating, based at least in part on inputting the runway condition data into a runway condition model, runway section condition output data for the at least one section;
determining, by the runway condition model and based at least in part on the runway section condition output data, a runway condition code for the at least one section;
generating, by the runway condition model, a confidence score associated with the runway condition code;
generating, by the runway condition model, an adjusted runway condition code for the at least one section based at least in part on the confidence score; and
causing rendering of a user interface based at least in part on the at least one section of the plurality of sections of the runway corresponding to the adjusted runway condition code.
The examiner submits that the foregoing bolded limitations constitute a “mental process” because under its broadest reasonable interpretation, the claim covers organizing human activity. Specifically, the “receiving runway data” and “receiving runway condition data” step encompasses collecting information. The “generating” steps encompasses mathematical concepts. The “determining” steps analyzing the data. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
1. A computer-implemented method, the computer-implemented method comprising:
receiving runway data associated with a runway;
receiving runway condition data associated with a plurality of sections of the runway, wherein the runway condition data is aggregated from a plurality of runway condition data sources, and wherein the runway condition data indicates a surface condition associated with at least one section of the plurality of sections of the runway;
generating, based at least in part on inputting the runway condition data into a runway condition model, runway section condition output data for the at least one section;
determining, by the runway condition model and based at least in part on the runway section condition output data, a runway condition code for the at least one section;
generating, by the runway condition model, a confidence score associated with the runway condition code;
generating, by the runway condition model, an adjusted runway condition code for the at least one section based at least in part on the confidence score; and
causing rendering of a user interface based at least in part on the at least one section of the plurality of sections of the runway corresponding to the adjusted runway condition code.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “causing rendering” step encompasses presenting the results. The examiner submits that these limitations are an attempt to generally link additional elements to a technological environment. In particular, the user interface is recited at a high level of generality and merely presents the abstract idea, therefore acting as a generic computer to perform the abstract idea. The user interface is claimed generically and is operating in its ordinary capacity and does not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. The additional limitation is no more than mere instructions to apply the exception using a computer.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitations as an ordered combination or as a whole, the limitations add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
Dependent claims 2-10 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. Therefore, dependent claims 2-10 are not patent eligible under the same rationale as provided for in the rejection of.
Therefore, claims 1-10 are ineligible under 35 USC §101. Claims 2-19 and 20 are ineligible under 35 USC §101 for at least the same reasons of claims 1-10.
Claim Rejections - 35 USC § 102
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.
Claims 1-3, 6-13 and 16-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Publication No. 2024/0105070 to Maalioune et al. (hereinafter “Maalioune”).
Claims 1-3, 6-13 and 16-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Maalioune.
With respect to independent claims 1, 11 and 20, Maalioune discloses receiving runway data associated with a runway (see paragraph [0049]: The platform 1 thus includes an interface I for collecting and processing flight data which receives data D1 supplied by the aircraft, a data storage and decoding step II receiving first data D1 decoded by the interface I and second data D2 and a calculation step III receiving data decoded by the storage and decoding step II);
receiving runway condition data associated with a plurality of sections of the runway, wherein the runway condition data is aggregated from a plurality of runway condition data sources, and wherein the runway condition data indicates a surface condition associated with at least one section of the plurality of sections of the runway (see paragraphs [0048] and [0059];
generating, based at least in part on inputting the runway condition data into a runway condition model, runway section condition output data for the at least one section (see paragraphs [0041] and [0059]: This RWYCC coefficient is derived from various data sources and is provided with a confidence index that reflects the reliability of the calculated coefficient. For each data group, a partial runway condition is calculated and the evolution of the runway conditions associated with an estimation of a confidence index from the calculated runway conditions is determined.);
determining, by the runway condition model and based at least in part on the runway section condition output data, a runway condition code for the at least one section (see paragraphs [0039] and [0040]: An exemplary embodiment of a system for determining aircraft landing runway conditions according to the invention is shown in FIG. 1. This system is intended to calculate and provide a runway coefficient RWYCC (Runway Condition Code), for various sections of landing runways at an airport and provide runway conditions to the airport operator to enable optimal use of the runways, in particular by reducing runway closures. This RWYCC coefficient complies with the GRF (Global Reporting Format) regulations in force according to RTM. 0704.);
generating, by the runway condition model, a confidence score associated with the runway condition code (see paragraph [0048]: The system for determining the runway conditions essentially comprises a data acquisition and calculation platform 1 which acquires various data groups D1 and D2 useful for evaluating and monitoring deteriorating conditions of airport runways, and calculates, for each section of runway, for example for each third of the runway, a runway coefficient associated with a confidence index.);
generating, by the runway condition model, an adjusted runway condition code for the at least one section based at least in part on the confidence score (see paragraph [0059] –[0061]: For each data group, a partial runway condition is calculated and the evolution of the runway conditions associated with an estimation of a confidence index from the calculated runway conditions is determined. The weighting coefficient K1 or K2 of a subset is conditioned during the method by the weighting of the data group, the relevance of the analysed data, their sampling frequency, and the dating of the acquired data, as a function of time, the confidence index degrading as a function of time, without new data. The weighting coefficients are also modified if data from another group is taken into account.); and
causing rendering of a user interface based at least in part on the at least one section of the plurality of sections of the runway corresponding to the adjusted runway condition code (see paragraphs [0048] – [9950] and [0091] - [0094]: The system for determining the runway conditions essentially comprises a data acquisition and calculation platform 1 which acquires various data groups D1 and D2 useful for evaluating and monitoring deteriorating conditions of airport runways, and calculates, for each section of runway, for example for each third of the runway, a runway coefficient associated with a confidence index. This platform 1 also provides a man-machine interface accessible for example by means of an API computer application by the airport manager G who provides this information to the air traffic controller Ctrl to supply this information to aircraft in flight A. The API application provides for example a window illustrating different runways, here two in number, comprising multiple sectors S1, S2, S3, S4, S5, S6, each identified.).
With respect to dependent claims 2 and 12, Maalioune discloses the computer-implemented method further comprising: generating, by the runway condition model, a validity score associated with at least one portion of the runway condition data aggregated from the plurality of runway condition data sources, wherein the validity score is based at least in part on timestamp data associated with the at least one portion of the runway condition data; and generating, by the runway condition model, the confidence score associated with the runway condition code based at least in part on the validity score (see paragraphs [0060], [0074] and [0075]: The weighting coefficient K1 or K2 of a subset is conditioned during the method by the weighting of the data group, the relevance of the analysed data, their sampling frequency, and the dating of the acquired data, as a function of time, the confidence index degrading as a function of time, without new data. Furthermore, the filtering used is temporal filtering and is specific to each type of data. In addition, the filtering is carried out as a function of the sampling frequency of the data in order to standardise the sampling frequency used for data acquisition by weighting the data differently according to its sampling frequency. At the end of the filtering step, the first data D1 relating to the braking parameters of the aircraft is processed by the calculation step III for calculating the coefficient II of friction of the runway).
With respect to dependent claims 3 and 13, Maalioune discloses the computer-implemented method further comprising: detecting a runway section transition trend associated with the at least one section of the plurality of sections of the runway, wherein the runway section transition trend indicates a transition of the surface condition of the at least one section from a first state to a second state, and wherein the runway section transition trend is generated based at least in part on ground sensor data generated by ground sensors associated with the runway collected over a predetermined periodicity of time; and generating, by the runway condition model, the confidence score associated with the runway condition code based at least in part on the runway section transition trend (see paragraphs [0059] and [0094]: For each data group, a partial runway condition is calculated and the evolution of the runway conditions associated with an estimation of a confidence index from the calculated runway conditions is determined. Furthermore, each sector is associated with the list of inputs D1 ij to D6 ij, each associated with a weighting coefficient K1 ij to K6 ij. A history of the runways coefficients RWYCCi(t) each associated with their confidence index CIi(t) can also be provided in order to allow the derivation of a variation of runway coefficients to provide decision support based on the history of runway coefficient variation.).
With respect to dependent claims 6 and16, Maalioune discloses the computer-implemented method further comprising: receiving at least one prior vehicle landing deceleration profile, wherein the at least one prior vehicle landing deceleration profile is generated by an onboard runway assessment and landing safety system associated with a vehicle upon landing on a respective runway; and generating, by the runway condition model, the confidence score associated with the runway condition code based at least in part on the at least one prior vehicle landing deceleration profile (see paragraphs [0042] – [0044]: The RWYCC coefficient is in particular derived from first data relating to braking parameters of the aircraft and from second data derived on the ground relating to the taxiing conditions of the aircraft. Also with reference to FIG. 2 , the first data D1 is delivered by the aircraft, after landing, in the form of a radio report. This may include for example data comprising in particular the type of aircraft, the weight of the aircraft, the wheel speed relative to the ground, the hydraulic braking pressure, the flight phase, the thrust reverser status, the brake pedal depression, the GPS positions.).
With respect to dependent claims 7 and 17, Maalioune discloses wherein the confidence score associated with the runway condition code is generated by the runway condition model based at least in part on at least one or more of validity scores associated with one or more portions of the runway condition data, runway section transition trends associated with the plurality of sections of the runway, ground operator input data generated by ground operators associated with the runway, prior vehicle landing deceleration profiles associated with one or more respective vehicles that recently landed on the runway, or vehicle operator confirmations generated by vehicle operators associated with the prior vehicle landing deceleration profiles (see paragraphs [0063] – [0064]: For example, braking data can be combined with radar data in order to correlate the position seen by the aircraft and the position given by the radar. Likewise, the braking data can be combined with sensor data in order to use the braking data, according to the context, to optimise and correlate the calculations. For example, if the radar data r is not available, the positioning data of the aircraft available on the on-board computers is used.).
With respect to dependent claims 8 and 18, Maalioune discloses wherein the plurality of runway condition data sources comprises at least one ground sensor associated with the runway, digital notices to airmen (NOTAMs), voice broadcasts, automated terminal information service (ATIS) messages, datalink messages, pilot reports (PIREPs), or prior vehicle landing deceleration profiles associated with one or more respective vehicles that recently landed on the runway (see paragraphs [0043] – [0048]: Also with reference to FIG. 2 , the first data D1 is delivered by the aircraft, after landing, in the form of a radio report. The second data D2 relates more specifically to the runway conditions and is supplied by sensors C, by radar data Rd, by weather reports W or measurements provided by test trucks Tt. The sensors are used for example for determining the possible presence of contaminants, such as water, snow, stagnant water, mud, . . . , the thickness of the contaminant, the surface condition of the runway, for example dry, wet, slippery wet, the temperature on the ground, . . . The radar data is intended in particular for determining the position of the aircraft and the test truck provides a coefficient of friction. The system for determining the runway conditions essentially comprises a data acquisition and calculation platform 1 which acquires various data groups D1 and D2 useful for evaluating and monitoring deteriorating conditions of airport runways, and calculates, for each section of runway, for example for each third of the runway, a runway coefficient associated with a confidence index. This platform 1 also provides a man-machine interface accessible for example by means of an API computer application by the airport manager G who provides this information to the air traffic controller Ctrl to supply this information to aircraft in flight A.).
With respect to dependent claims 9 and 19, Maalioune discloses wherein the plurality of sections of the runway comprises four or more sections of the runway (see paragraph [0092]: The API application provides for example a window illustrating different runways, here two in number, comprising multiple sectors S1, S2, S3, S4, S5, S6, each identified.).
With respect to dependent claim 10, Maalioune discloses wherein the runway data comprises at least one of a runway identifier, a runway length, a runway threshold, or a runway surface type (see paragraph [0007] – [0013]: According to a first aspect, the object of the invention is therefore a method for determining aircraft landing runway conditions, which comprises the steps of: acquiring a set of data groups of different types for evaluating and monitoring deteriorating runway conditions; deriving weighting coefficients for each data group; filtering the data; determining, for each data group, a partial runway condition; modifying the weighting coefficients of each data group; and combining the partial runway conditions to produce a runway coefficient associated with a confidence index derived from modified weighting coefficients.).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 4, 5, 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Maalioune in view of U.S. Patent Publication No. 2024/0062664 to He.
With respect to dependent claims 4 and 14, Maalioune discloses data comprising in particular the type of aircraft, the weight of the aircraft, the wheel speed relative to the ground, the hydraulic braking pressure, the flight phase, the thrust reverser status, the brake pedal depression. For example, a Random Forest algorithm can be used to predict the value of a coefficient of friction from decoded data. In the following step 20, the runway coefficient is calculated, this runway coefficient being associated with a confidence index calculated from modified weighting coefficients. This calculation is made from the sum of weighted local runway conditions. (see paragraphs [0044], [0084], and [0087] – [0089]).
Maalioune does not explicitly discloses. determining, based at least in part on a combination of the runway data, vehicle profile data associated with a vehicle, and one or more adjusted runway condition codes associated with the plurality of sections of the runway, a plurality of required landing parameters for each section of the plurality of sections of the runway, wherein the plurality of required landing parameters are associated with executing a landing procedure for the vehicle via the runway, and wherein the plurality of required landing parameters comprise a required landing distance associated with each section of the plurality of sections of the runway; determining, based at least in part on the plurality of required landing parameters, that a required runway length associated with the landing procedure does not satisfy an available runway length associated with the runway; and in response to determining that the required runway length does not satisfy the available runway length: causing display of an alert via one or more computing devices.
He teaches the FMS, when performing take-off and landing calculations for the runway, to separately calculate a required landing distance for each of the plurality of runway segments. For example, the FMS may calculate a landing distance for a first segment (e.g., touchdown portion) of the runway using the categorized contaminant information 203 for the first segment, calculate a required landing distance for the second segment (e.g., midpoint portion) of the runway using the categorized contaminant information 203 for the second segment, and calculate a required landing distance for the third segment (e.g., rollout portion) of the runway using the categorized contaminant condition for the third segment. The FMS 140 and/or the ROAAS 142 may calculate a required runway length for the aircraft by calculating a first landing distance associated with an initial runway segment (e.g., the touchdown segment) of the runway based on the surface condition or contaminant associated with that respective segment, calculating a second landing distance for a second runway segment (e.g., midpoint segment) based on the surface condition or contaminant associated with that respective segment, calculating a third landing distance for a third runway segment (e.g., rollout segment) based on the surface condition or contaminant associated with that respective segment, and then adding the respective distances associated with the respective runway segments to arrive at a required runway length for the aircraft. When the required runway length is less than the available runway length for the destination runway, the ROAAS 142 generates or otherwise provides one or more alerts or other user notifications to alert the pilot or other members of the flight crew. (See paragraphs [0034] and [0041]) .
It would have been obvious to one skilled in the art, before the effective filing date of the of the invention, to combine the runway condition codes in FMS landing calculations of He with the method of assessing runway conditions for runway sections of Maalioune to improve aircraft landing safety and preventing runway excursions.
With respect to dependent claims 5 and 15, Maalioune discloses a platform 1 also provides a man-machine interface accessible for example by means of an API computer application by the airport manager G who provides this information to the air traffic controller Ctrl to supply this information to aircraft in flight A. The runway coefficient is calculated, this runway coefficient being associated with a confidence index calculated from modified weighting coefficients. This calculation is made from the sum of weighted local runway conditions. The API application provides for example a window illustrating different runways, here two in number, comprising multiple sectors S1, S2, S3, S4, S5, S6, each identified. (See paragraphs [0048], [0087] – [0089] and [0092]).
Maalioune does not explicitly disclose updating, based at least in part on input received via the user interface, data related to at least one current surface condition associated with the at least one section of the plurality of sections of the runway associated with the adjusted runway condition code; and generating, based on updating the adjusted runway condition code, one or more required landing parameters for the at least one section of the plurality of sections of the runway.
He discloses (See paragraphs [0017], [0057], [0060] and [0061]: the user notification of the discrepancy may be provided on a graphical user interface (GUI) display in connection with a button or similar GUI element that is selectable or otherwise manipulable by the pilot or other user to provide indication of a desire to use the message-based value in lieu of the previously defined value for the particular runway surface condition attribute. In response to receiving indication from a user that verifies or otherwise confirms that the message-derived value for a particular runway condition field should be utilized, the runway condition augmentation process 400 updates the value for that particular runway condition field at the onboard system(s) using the message-derived value. In response to receiving user confirmation to use a NOTAM-derived value, the NOTAM analysis service 300 instructs or otherwise configures the FMS 308 and/or the ROAAS 310 to substitute the specified value derived from the NOTAM for the value that was previously input or previously configured for that runway condition attribute. In other embodiments, the NOTAM analysis service 300 may augment or otherwise combine the previously input or previously configured value for that runway condition attribute using the specified value to arrive at an augmented value for that runway condition attribute that reflects the previous value but is influenced by the specified value for that runway condition attribute derived from the NOTAM.
It would have been obvious to one skilled in the art, before the effective filing date of the invention, to combine updated the method of updating runway conditions that automatic recalculation of landing parameters of He with the user input system to runway condition codes generated by Maalioune in order to provide runway safety in integrated aircraft systems with a user interface input for updating runway condition codes.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEMETRA R SMITH-STEWART whose telephone number is (571)270-3965. The examiner can normally be reached 10am - 6pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Peter Nolan can be reached at 571-270-7016. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DEMETRA R SMITH-STEWART/Examiner, Art Unit 3661
/PETER D NOLAN/Supervisory Patent Examiner, Art Unit 3661