DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. 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
2. This office action is in response to application number 18/901,675 filed on 09/30/2024, in
which the amendments and arguments filed on 03/30/2026.
Claims 1, 5-6, 8, 10-15, and 18-19 has been amended.
Claims 21 and 22 has been added.
Claims 4 and 18 has been cancelled.
Claims 1-3, 5-17, and 19-22 are currently pending and have been examined.
Priority
3. Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C 119
(a)-(d). The certified copy has been filed in Application No. IN202411062087, filed on
08/16/2024.
Response to Amendment
4. Applicant’s arguments/remarks made in amendment (See Pages 7-10, filed 03/30/2026) have been fully considered and are not persuasive.
Applicant argues, “Tonnerre does not anticipate, either inherently, or expressly, describe, for example, one or more features of and initiating performance of one or more aircraft connectivity related actions based on the aircraft mission connectivity prediction data, wherein the one or more aircraft connectivity related actions are performed prior to entry of an aircraft into a geographical region indicated by at least one of the one or more aircraft connectivity zone representations.”
Examiner respectfully disagrees. The claim language “and initiating performance of one or more aircraft connectivity related actions based on the aircraft mission connectivity prediction data, wherein the one or more aircraft connectivity related actions are performed prior to entry of an aircraft into a geographical region indicated by at least one of the one or more aircraft connectivity zone representations.”, defined in applicant’s specification page 00107, states “In this regard, for example, an aircraft connectivity alert may be configured to alert an operator of the aircraft 110 to perform any communications between a device external to the aircraft 110 and a device within the aircraft 110 before entering a geographic region associated with a moderate connectivity impact level and/or a severe connectivity impact level.”. Under the broadest interpretation, the examiner is interpreting this as a connectivity action being performed before the aircraft reaches a region for connectivity. Under this interpretation, prior art Tonnerre teaches in Paragraph 0059 “Leading-up to the aircraft entering a region where predicted QoE doesn't satisfy a rule, operations can pre-fetch for buffering information from URLs that are predicted to be likely accessed by passenger(s) while the aircraft is located in another region having sufficient QoE enabling such prefetching. For example, operations can pre-fetch website information obtained from user-selectable links provided on a passenger's currently viewed webpage. In a more detailed example, operations prefetch article links on webpage logically following a current article viewed by a passenger.”. Tonnerre also teaches in Paragraph 0062 “Leading-up to regions where predicted connectivity QoE doesn't satisfy a rule, operations can transfer from off-board hosted to on-board application hosted application code having higher QoE requirements. For example, upload code for hosting or activate on-board hosted code and/or data to support certain applications that is otherwise hosted off-board. In one example embodiment, gaming environment data related to a players' game state (e.g., location within an immersive gaming environment) can be transferred on-board.”
In other words, the prior art discloses when an aircraft leads up to a region where the quality of experience does not satisfy a rule, operations are used that pre-fetch buffering information from URLS that are predicted to be used by passengers when in another region that has good quality of experience so the user may be able to continue to access the information on the page. For the above reasons, applicant’s arguments are not persuasive.
Applicant respectfully disagrees that claim 15 and 20 are patentable, and therefore is rejected for the reasons similar to claim 1. Thus claims 2-3, 5-14, 16-17 and 19-22 are also rejected upon dependency to the independent claims. For the reasons explained above the entire rejection has been maintained.
Claim Rejections - 35 USC § 102
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)(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.
5. Claim(s) 1-2, 13-16, and 20-21 is/are rejected under 35 U.S.C. 102 as being unpatentable over Tonnerre (WO 2024263703 A1).
Regarding claim 1, Tonnerre discloses A method comprising: identifying historical aircraft connectivity data; (Tonnerre Paragraph 00120: “historical connectivity QoE database storing data indicating previously measured connectivity QoE at locations along the vehicle travel route.”) training an aircraft connectivity prediction model using the historical aircraft connectivity data; (Tonnerre Paragraph 0052: “The historical and predicted connectivity QoE may be provided as detailed information determined for individual set locations, for defined groups of seat locations, etc., and/or provided as notifications (e.g., system will become disconnected in 5 minutes).”) (Tonnerre Paragraph 0053: “Depending on the level of information detail provided to the crew, specific training may be defined to ensure the crew can understand, interpret and explain the historical and predicted connectivity QoE.”) (Tonnerre Paragraph 0082: “Referring to Figure 4, some embodiments are directed to a prediction method based on an average of historical data.”) (Tonnerre Paragraph 0084: “In order to calculate the QoE prediction for a flight, the estimated trajectory of the flight is calculated first using historical data and flight route databases (e.g. using service provided by FlightAware Aviation Co.)”) (Tonnerre Paragraph 00101: “An operation creates 504 connectivity QoE features and uses historical metric data to train the model.”) identifying aircraft mission connectivity impact data; (Tonnerre Paragraph 00040: “A set of targeted indicators to provide a more detailed view of the current connectivity QoE performance levels and network performance level (e.g. availability). The indicators may be associated with specific connectivity requirements of the content available to or requested by passengers. For instance, before purchasing a plan the passenger can check if the connectivity system is available, and can also verify the QoE is sufficient for video streaming before starting to watch a movie or look at WebQoE indicators (QoE for web browsing) before surfing the Internet;”) generating aircraft mission connectivity prediction data by applying the aircraft mission connectivity impact data to the aircraft connectivity prediction model; (Tonnerre Paragraph 0034: “Various embodiments of the present disclosure are directed to operations that provide capabilities to predict connectivity QoE metric performances during an ongoing trip or for upcoming travels, and include operations to report and share indications of the predicted connectivity QoE with the passengers and crew.”) (Tonnerre Paragraph 00101: “The training process can be repeated 510 periodically and/or when a threshold amount of new metric data is obtained, in order to refresh the model and improve its prediction accuracy.”) generating an aircraft mission connectivity prediction interface component, wherein the aircraft mission connectivity prediction interface component comprises one or more aircraft connectivity zone representations, wherein each of one or more aircraft connectivity zone representations is associated with one of a plurality of connectivity impact levels; (Tonnerre Paragraph 0040: “A representation of predicted connectivity QoE for the rest of the flight (and optionally an indication of the experienced past connectivity QoE) providing prediction of the availability and expected level of connectivity QoE. For instance, a timeline can be used to indicate the time of major events (e.g. gap of connectivity, sufficient QoE level for web browsing, sufficient QoE level for audio streaming, sufficient QoE level for video streaming, sufficient QoE level for immersive virtual reality, etc. ) and/or a map with color-coded route showing such predicted levels of connectivity QoE.”) (Tonnerre Paragraph 0079: “Some embodiments are directed to multiple ways to determine QoE predictions, which may use relatively less computationally intensive approaches for calculation of the average of QoE scoring in a predefined area to work computationally intensive operations using Machine Learning (ML) algorithms”) causing the aircraft mission connectivity prediction interface component to be rendered to an aircraft operations interface; (Tonnerre Paragraph 0011: “Figure 1 illustrates an example passenger dashboard displayed on a seatback display and a passenger electronic device to indicate present connectivity QoE metrics and predicted connectivity QoE metrics, in accordance with some embodiments;”)
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and initiating performance of one or more aircraft connectivity related actions based on the aircraft mission connectivity prediction data, wherein the one or more aircraft connectivity related actions are performed prior to entry of an aircraft into a geographical region indicated by at least one of the one or more aircraft connectivity zone representations. (Tonnerre Paragraph 0059: “Leading-up to the aircraft entering a region where predicted QoE doesn't satisfy a rule, operations can pre-fetch for buffering information from URLs that are predicted to be likely accessed by passenger(s) while the aircraft is located in another region having sufficient QoE enabling such prefetching. For example, operations can pre-fetch website information obtained from user-selectable links provided on a passenger's currently viewed webpage. In a more detailed example, operations prefetch article links on webpage logically following a current article viewed by a passenger.”) (Tonnerre Paragraph 0062: “Leading-up to regions where predicted connectivity QoE doesn't satisfy a rule, operations can transfer from off-board hosted to on-board application hosted application code having higher QoE requirements. For example, upload code for hosting or activate on-board hosted code and/or data to support certain applications that is otherwise hosted off-board. In one example embodiment, gaming environment data related to a players' game state (e.g., location within an immersive gaming environment) can be transferred on-board.”) (Note: aircraft connectivity related actions = pre-fetch website information obtained from user-selectable links provided on a passenger's currently viewed webpage or transfer from off-board hosted to on-board application hosted application code having higher QoE requirements.)
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Regarding claim 2, Tonnerre discloses The method of claim 1, wherein the aircraft mission connectivity prediction interface component is associated with an in-flight state. (Tonnerre Paragraph 0011: “Figure 1 illustrates an example passenger dashboard displayed on a seatback display and a passenger electronic device to indicate present connectivity QoE metrics and predicted connectivity QoE metrics, in accordance with some embodiments;”)
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Regarding claim 13, Tonnerre discloses The method of claim 1, further comprising: generating a negative connectivity indication display item; and generating an aircraft mission visualization interface component, wherein the aircraft mission visualization interface component comprises the negative connectivity indication display item. (Tonnerre Paragraph 0072: “Operations may classify the calculated metric into a category, which will be associated with a score. For instance, a scoring methodology can be defined to assign FCP average to 5 different classes from -2 to +2 or from 1 to 5 as described below. If the FCP average is 5 seconds during the defined time window, then the score associated will be 3/5.” & 00115: “In some embodiments, the operations further include to provide for display the vehicle travel route, wherein the vehicle travel route is displayed with route segments having shading, color, and/or texture selected to indicate the predicted level of connectivity QoE for the respective route segment.”)
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Regarding claim 14, Tonnerre discloses The method of claim 1, further comprising: generating a positive connectivity indication display item; and generating an aircraft mission visualization interface component, wherein the aircraft mission visualization interface component comprises the positive connectivity indication display item. (Tonnerre0072: “Operations may classify the calculated metric into a category, which will be associated with a score. For instance, a scoring methodology can be defined to assign FCP average to 5 different classes from -2 to +2 or from 1 to 5 as described below. If the FCP average is 5 seconds during the defined time window, then the score associated will be 3/5.” & Paragraph 00115: “In some embodiments, the operations further include to provide for display the vehicle travel route, wherein the vehicle travel route is displayed with route segments having shading, color, and/or texture selected to indicate the predicted level of connectivity QoE for the respective route segment.”)
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Regarding claim 15, Tonnerre discloses An apparatus comprising memory and one or more processors communicatively coupled to the memory, the one or more processors configured to: (Tonnerre Paragraph 0007 : “The connectivity QoE prediction module includes: at least one network interface configured to communicate through a cabin network; a display device configured to display video to a passenger or crew of the vehicle; a processor; and a memory”) identify historical aircraft connectivity data; (Tonnerre Paragraph 00120: “historical connectivity QoE database storing data indicating previously measured connectivity QoE at locations along the vehicle travel route.”) train an aircraft connectivity prediction model using the historical aircraft connectivity data; (Tonnerre Paragraph 0052: “The historical and predicted connectivity QoE may be provided as detailed information determined for individual set locations, for defined groups of seat locations, etc., and/or provided as notifications (e.g., system will become disconnected in 5 minutes).”) (Tonnerre Paragraph 0053: “Depending on the level of information detail provided to the crew, specific training may be defined to ensure the crew can understand, interpret and explain the historical and predicted connectivity QoE.”) (Tonnerre Paragraph 0082: “Referring to Figure 4, some embodiments are directed to a prediction method based on an average of historical data.”) (Tonnerre Paragraph 0084: “In order to calculate the QoE prediction for a flight, the estimated trajectory of the flight is calculated first using historical data and flight route databases (e.g. using service provided by FlightAware Aviation Co.)”) (Tonnerre Paragraph 00101: “An operation creates 504 connectivity QoE features and uses historical metric data to train the model.”) identify aircraft mission connectivity impact data; (Tonnerre Paragraph 00040: “A set of targeted indicators to provide a more detailed view of the current connectivity QoE performance levels and network performance level (e.g. availability). The indicators may be associated with specific connectivity requirements of the content available to or requested by passengers. For instance, before purchasing a plan the passenger can check if the connectivity system is available, and can also verify the QoE is sufficient for video streaming before starting to watch a movie or look at WebQoE indicators (QoE for web browsing) before surfing the Internet;”) generate aircraft mission connectivity prediction data by applying the aircraft mission connectivity impact data to the aircraft connectivity prediction model; (Tonnerre Paragraph 0034: “Various embodiments of the present disclosure are directed to operations that provide capabilities to predict connectivity QoE metric performances during an ongoing trip or for upcoming travels, and include operations to report and share indications of the predicted connectivity QoE with the passengers and crew.”) (Tonnerre Paragraph 00101: “The training process can be repeated 510 periodically and/or when a threshold amount of new metric data is obtained, in order to refresh the model and improve its prediction accuracy.”) generate an aircraft mission connectivity prediction interface component, wherein the aircraft mission connectivity prediction interface component comprises one or more aircraft connectivity zone representations, wherein each of one or more aircraft connectivity zone representations is associated with one of a plurality of connectivity impact levels; (Tonnerre Paragraph 0040: “A representation of predicted connectivity QoE for the rest of the flight (and optionally an indication of the experienced past connectivity QoE) providing prediction of the availability and expected level of connectivity QoE. For instance, a timeline can be used to indicate the time of major events (e.g. gap of connectivity, sufficient QoE level for web browsing, sufficient QoE level for audio streaming, sufficient QoE level for video streaming, sufficient QoE level for immersive virtual reality, etc. ) and/or a map with color-coded route showing such predicted levels of connectivity QoE.”) (Tonnerre Paragraph 0079: “Some embodiments are directed to multiple ways to determine QoE predictions, which may use relatively less computationally intensive approaches for calculation of the average of QoE scoring in a predefined area to work computationally intensive operations using Machine Learning (ML) algorithms”) cause the aircraft mission connectivity prediction interface component to be rendered to an aircraft operations interface; (Tonnerre Paragraph 0011: “Figure 1 illustrates an example passenger dashboard displayed on a seatback display and a passenger electronic device to indicate present connectivity QoE metrics and predicted connectivity QoE metrics, in accordance with some embodiments;”)
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and initiate performance of one or more aircraft connectivity related actions based on the aircraft mission connectivity prediction data, wherein the one or more aircraft connectivity related actions are performed prior to entry of an aircraft into a geographical region indicated by at least one of the one or more aircraft connectivity zone representations. (Tonnerre Paragraph 0059: “Leading-up to the aircraft entering a region where predicted QoE doesn't satisfy a rule, operations can pre-fetch for buffering information from URLs that are predicted to be likely accessed by passenger(s) while the aircraft is located in another region having sufficient QoE enabling such prefetching. For example, operations can pre-fetch website information obtained from user-selectable links provided on a passenger's currently viewed webpage. In a more detailed example, operations prefetch article links on webpage logically following a current article viewed by a passenger.”) (Tonnerre Paragraph 0062: “Leading-up to regions where predicted connectivity QoE doesn't satisfy a rule, operations can transfer from off-board hosted to on-board application hosted application code having higher QoE requirements. For example, upload code for hosting or activate on-board hosted code and/or data to support certain applications that is otherwise hosted off-board. In one example embodiment, gaming environment data related to a players' game state (e.g., location within an immersive gaming environment) can be transferred on-board.”) (Note: aircraft connectivity related actions = pre-fetch website information obtained from user-selectable links provided on a passenger's currently viewed webpage or transfer from off-board hosted to on-board application hosted application code having higher QoE requirements.)
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Regarding claim 16, Tonnerre discloses The apparatus of claim 15, wherein the aircraft mission connectivity prediction interface component is associated with an in-flight state. (Tonnerre Paragraph 0011: “Figure 1 illustrates an example passenger dashboard displayed on a seatback display and a passenger electronic device to indicate present connectivity QoE metrics and predicted connectivity QoE metrics, in accordance with some embodiments;”)
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Regarding claim 20, Tonnerre discloses A computer program product comprising at least one non-transitory computer-readable storage medium having computer program code stored thereon that, in execution with at least one processor, configures the computer program product for: (Tonnerre Paragraph 00194 : “These computer program instructions may also be stored in a non- transitory computer-readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture”) identifying historical aircraft connectivity data; (Tonnerre Paragraph 00120: “historical connectivity QoE database storing data indicating previously measured connectivity QoE at locations along the vehicle travel route.”) training an aircraft connectivity prediction model using the historical aircraft connectivity data; (Tonnerre Paragraph 0052: “The historical and predicted connectivity QoE may be provided as detailed information determined for individual set locations, for defined groups of seat locations, etc., and/or provided as notifications (e.g., system will become disconnected in 5 minutes).”) (Tonnerre Paragraph 0053: “Depending on the level of information detail provided to the crew, specific training may be defined to ensure the crew can understand, interpret and explain the historical and predicted connectivity QoE.”) (Tonnerre Paragraph 0082: “Referring to Figure 4, some embodiments are directed to a prediction method based on an average of historical data.”) (Tonnerre Paragraph 0084: “In order to calculate the QoE prediction for a flight, the estimated trajectory of the flight is calculated first using historical data and flight route databases (e.g. using service provided by FlightAware Aviation Co.)”) (Tonnerre Paragraph 00101: “An operation creates 504 connectivity QoE features and uses historical metric data to train the model.”) identifying aircraft mission connectivity impact data; (Tonnerre Paragraph 00040: “A set of targeted indicators to provide a more detailed view of the current connectivity QoE performance levels and network performance level (e.g. availability). The indicators may be associated with specific connectivity requirements of the content available to or requested by passengers. For instance, before purchasing a plan the passenger can check if the connectivity system is available, and can also verify the QoE is sufficient for video streaming before starting to watch a movie or look at WebQoE indicators (QoE for web browsing) before surfing the Internet;”) generating aircraft mission connectivity prediction data by applying the aircraft mission connectivity impact data to the aircraft connectivity prediction model; (Tonnerre Paragraph 0034: “Various embodiments of the present disclosure are directed to operations that provide capabilities to predict connectivity QoE metric performances during an ongoing trip or for upcoming travels, and include operations to report and share indications of the predicted connectivity QoE with the passengers and crew.”) (Tonnerre Paragraph 00101: “The training process can be repeated 510 periodically and/or when a threshold amount of new metric data is obtained, in order to refresh the model and improve its prediction accuracy.”) generating an aircraft mission connectivity prediction interface component, wherein the aircraft mission connectivity prediction interface component comprises one or more aircraft connectivity zone representations, wherein each of one or more aircraft connectivity zone representations is associated with one of a plurality of connectivity impact levels; (Tonnerre Paragraph 0040: “A representation of predicted connectivity QoE for the rest of the flight (and optionally an indication of the experienced past connectivity QoE) providing prediction of the availability and expected level of connectivity QoE. For instance, a timeline can be used to indicate the time of major events (e.g. gap of connectivity, sufficient QoE level for web browsing, sufficient QoE level for audio streaming, sufficient QoE level for video streaming, sufficient QoE level for immersive virtual reality, etc. ) and/or a map with color-coded route showing such predicted levels of connectivity QoE.”) (Tonnerre Paragraph 0079: “Some embodiments are directed to multiple ways to determine QoE predictions, which may use relatively less computationally intensive approaches for calculation of the average of QoE scoring in a predefined area to work computationally intensive operations using Machine Learning (ML) algorithms”) causing the aircraft mission connectivity prediction interface component to be rendered to an aircraft operations interface; (Tonnerre Paragraph 0011: “Figure 1 illustrates an example passenger dashboard displayed on a seatback display and a passenger electronic device to indicate present connectivity QoE metrics and predicted connectivity QoE metrics, in accordance with some embodiments;”)
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and initiating performance of one or more aircraft connectivity related actions based on the aircraft mission connectivity prediction data, wherein the one or more aircraft connectivity related actions are performed prior to entry of an aircraft into a geographical region indicated by at least one of the one or more aircraft connectivity zone representations. (Tonnerre Paragraph 0059: “Leading-up to the aircraft entering a region where predicted QoE doesn't satisfy a rule, operations can pre-fetch for buffering information from URLs that are predicted to be likely accessed by passenger(s) while the aircraft is located in another region having sufficient QoE enabling such prefetching. For example, operations can pre-fetch website information obtained from user-selectable links provided on a passenger's currently viewed webpage. In a more detailed example, operations prefetch article links on webpage logically following a current article viewed by a passenger.”) (Tonnerre Paragraph 0062: “Leading-up to regions where predicted connectivity QoE doesn't satisfy a rule, operations can transfer from off-board hosted to on-board application hosted application code having higher QoE requirements. For example, upload code for hosting or activate on-board hosted code and/or data to support certain applications that is otherwise hosted off-board. In one example embodiment, gaming environment data related to a players' game state (e.g., location within an immersive gaming environment) can be transferred on-board.”) (Note: aircraft connectivity related actions = pre-fetch website information obtained from user-selectable links provided on a passenger's currently viewed webpage or transfer from off-board hosted to on-board application hosted application code having higher QoE requirements.)
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Regarding claim 21, Tonnerre discloses The computer program product of claim 20, wherein the aircraft mission connectivity prediction interface component is associated with an in-flight state. (Tonnerre Paragraph 0011: “Figure 1 illustrates an example passenger dashboard displayed on a seatback display and a passenger electronic device to indicate present connectivity QoE metrics and predicted connectivity QoE metrics, in accordance with some embodiments;”)
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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.
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.
6. Claim(s) 3, 17, and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tonnerre (WO 2024263703 A1) in view of (US 11398158 B2) to Halsey et al. (hereinafter Halsey).
Regarding claim 3, Tonnerre does disclose The method of claim 1, wherein the aircraft mission connectivity prediction interface component (Tonnerre Paragraph 0011: “Figure 1 illustrates an example passenger dashboard displayed on a seatback display and a passenger electronic device to indicate present connectivity QoE metrics and predicted connectivity QoE metrics, in accordance with some embodiments;”)
Tonnerre does not disclose […] is associated with an airport state.
However, Halsey does teach […] is associated with an airport state. (Halsey Column 6, line number 17-19: “The starting point 101 may be an airport from which aircraft departs, and the ending point 102 may be a destination airport.”)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include […] is associated with an airport state taught by Halsey. This would have been for the benefit to provide a connectivity forecast system to provide users aboard aircraft with status of network services. The connectivity forecast system communicates with one or more service providers. [Halsey Column 1, line number 62-65]
Regarding claim 17, Tonnerre does disclose The apparatus of claim 15, wherein the aircraft mission connectivity prediction interface component (Tonnerre Paragraph 0011: “Figure 1 illustrates an example passenger dashboard displayed on a seatback display and a passenger electronic device to indicate present connectivity QoE metrics and predicted connectivity QoE metrics, in accordance with some embodiments;”)
Tonnerre does not disclose […] is associated with an airport state.
However, Halsey does teach […] is associated with an airport state. (Halsey Column 6, line number 17-19: “The starting point 101 may be an airport from which aircraft departs, and the ending point 102 may be a destination airport.”)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include […] is associated with an airport state taught by Halsey. This would have been for the benefit to provide a connectivity forecast system to provide users aboard aircraft with status of network services. The connectivity forecast system communicates with one or more service providers. [Halsey Column 1, line number 62-65]
Regarding claim 22, Tonnerre does disclose The computer program product of claim 20, wherein the aircraft mission connectivity prediction interface component (Tonnerre Paragraph 0011: “Figure 1 illustrates an example passenger dashboard displayed on a seatback display and a passenger electronic device to indicate present connectivity QoE metrics and predicted connectivity QoE metrics, in accordance with some embodiments;”)
Tonnerre does not disclose […] is associated with an airport state.
However, Halsey does teach […] is associated with an airport state. (Halsey Column 6, line number 17-19: “The starting point 101 may be an airport from which aircraft departs, and the ending point 102 may be a destination airport.”)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include […] is associated with an airport state taught by Halsey. This would have been for the benefit to provide a connectivity forecast system to provide users aboard aircraft with status of network services. The connectivity forecast system communicates with one or more service providers. [Halsey Column 1, line number 62-65]
7. Claim(s) 5 and 8-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tonnerre (WO 2024263703 A1) in view of (US 9858824 B1) to Zogg et al. (hereinafter Zogg).
Regarding claim 5, Tonnerre discloses claim 1, accordingly, the rejection of claim 1 is incorporated above.
Tonnerre does not disclose The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: modifying an aircraft mission associated with an aircraft.
However, Zogg does teach The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: modifying an aircraft mission associated with an aircraft. (Zogg Column 6, line number 60-Column 7, line number 3: “For example, a passenger expecting to attend a meeting/web-conference/teleconference during a particular time period when the aircraft is in flight may provide an input to the flight plan optimization system 300 (e.g., using the UI elements 22) specifying the time period when internet connectivity is a critical priority, and the flight plan optimization system 300 may ensure that the passenger has internet connectivity during the specified time period by adjusting the aircraft's planned route. In some embodiments, a user (e.g., an operator of an aircraft) is able to select a flight plan to be followed.”)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: modifying an aircraft mission associated with an aircraft taught by Zogg. This would have been for the benefit to provide a navigation system linked to a communications system of an aircraft to provide flight planning capabilities for optimizing internet connectivity during a flight. [Zogg Column 1, line number 26-29]
Regarding claim 8, Tonnerre discloses claim 1, accordingly, the rejection of claim 1 is incorporated above.
Tonnerre does not disclose The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: performing an optimal altitude simulation for an aircraft.
However, Zogg does teach The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: performing an optimal altitude simulation for an aircraft. (Zogg Column 12, line number 1-7: “As shown in FIGS. 4A-4B, edges are provided between nodes, such as edge 430 representing a path between node 420 and node 434. While edges such as edge 430 are illustrated as straight lines, it will be appreciated that various embodiments may include edges having curved shapes, changes in altitude, or edges that require other aviation maneuvers.”) (Zogg Column 15, line number 34-42: “Referring now to FIG. 6, a flow diagram of a method 600 for optimizing a flight plan for an aircraft based on internet connectivity is shown according to an exemplary embodiment of the inventive concepts disclosed herein. The method 600 may be implemented using any of the systems/apparatuses disclosed herein, such as on the aircraft 30, using the flight plan optimization system 300, the aircraft navigation system 380, and/or the flight plan 501 displayed by the display screen 500 as shown in FIG. 5.”) (Zogg Column 16, line number 9-15: “In some embodiments, the flight plan is optimized based on edge weights as discussed above in relation to FIGS. 4A-4B. For example, flight paths having edges associated with internet connections having high data transfer rates may be assigned high edge weights, and the flight path with the highest total edge weight sum may be determined to be the optimal flight plan.”) (Note: Because the flight plan is optimized based on edge weights the altitude is also determined corresponding to the flight plan)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: performing an optimal altitude simulation for an aircraft taught by Zogg. This would have been for the benefit to provide a navigation system linked to a communications system of an aircraft to provide flight planning capabilities for optimizing internet connectivity during a flight. [Zogg Column 1, line number 26-29]
Regarding claim 9, Tonnerre in view of Zogg teaches claim 8, accordingly, the rejection of claim 8 is incorporated above.
Tonnerre does not disclose The method of claim 8, wherein the optimal altitude simulation is performed when the aircraft is associated with a minimal connectivity impact level of the plurality of connectivity impact levels.
However, Zogg does teach The method of claim 8, wherein the optimal altitude simulation is performed when the aircraft is associated with a minimal connectivity impact level of the plurality of connectivity impact levels. (Zogg Column 12, line number 1-7: “As shown in FIGS. 4A-4B, edges are provided between nodes, such as edge 430 representing a path between node 420 and node 434. While edges such as edge 430 are illustrated as straight lines, it will be appreciated that various embodiments may include edges having curved shapes, changes in altitude, or edges that require other aviation maneuvers.”) (Zogg Column 15, line number 34-42: “Referring now to FIG. 6, a flow diagram of a method 600 for optimizing a flight plan for an aircraft based on internet connectivity is shown according to an exemplary embodiment of the inventive concepts disclosed herein. The method 600 may be implemented using any of the systems/apparatuses disclosed herein, such as on the aircraft 30, using the flight plan optimization system 300, the aircraft navigation system 380, and/or the flight plan 501 displayed by the display screen 500 as shown in FIG. 5.”) (Zogg Column 16, line number 9-15: “In some embodiments, the flight plan is optimized based on edge weights as discussed above in relation to FIGS. 4A-4B. For example, flight paths having edges associated with internet connections having high data transfer rates may be assigned high edge weights, and the flight path with the highest total edge weight sum may be determined to be the optimal flight plan.”) (Note: Because the flight plan is optimized based on edge weights the altitude is also determined corresponding to the flight plan)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include The method of claim 8, wherein the optimal altitude simulation is performed when the aircraft is associated with a minimal connectivity impact level of the plurality of connectivity impact levels taught by Zogg. This would have been for the benefit to provide a navigation system linked to a communications system of an aircraft to provide flight planning capabilities for optimizing internet connectivity during a flight. [Zogg Column 1, line number 26-29]
Regarding claim 10, Tonnerre claim 1, accordingly, the rejection of claim 1 is incorporated above.
Tonnerre does not disclose The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: causing operation of one or more aircraft components associated with an aircraft.
However, Zogg does teach The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: causing operation of one or more aircraft components associated with an aircraft. (Zogg Column 7, line number 51-56: “The memory 390 is shown to include various modules for determining properties related to optimizing flight plans for internet connectivity, including a communications module 391, a weather radar module 392, an air traffic control module 393, a display module 394, an avionics module 395, and a flight plan module 396.”)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: causing operation of one or more aircraft components associated with an aircraft taught by Zogg. This would have been for the benefit to provide a navigation system linked to a communications system of an aircraft to provide flight planning capabilities for optimizing internet connectivity during a flight. [Zogg Column 1, line number 26-29]
Regarding claim 11, Tonnerre discloses claim 1, accordingly, the rejection of claim 1 is incorporated above.
Tonnerre does not disclose The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: causing an aircraft connectivity alert to be provided to an operator of an aircraft.
However, Zogg does teach The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: causing an aircraft connectivity alert to be provided to an operator of an aircraft. (Zogg Column 9, line number 28-33: “As another example, aircraft crew and/or passengers may be alerted of an internet service outage from a ground-based tower on the original route. In some embodiments, the flight plan optimization system 300 may determine a new optimal flight plan based on receiving an internet service outage alert.”) (Note: A pilot is a part of a crew)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: causing an aircraft connectivity alert to be provided to an operator of an aircraft taught by Zogg. This would have been for the benefit to provide a navigation system linked to a communications system of an aircraft to provide flight planning capabilities for optimizing internet connectivity during a flight. [Zogg Column 1, line number 26-29]
8. Claim(s) 6 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tonnerre (WO 2024263703 A1) in view of Wiegman (US 20230084918 A1).
Regarding claim 6, Tonnerre discloses claim 1, accordingly, the rejection of claim 1 is incorporated above.
Tonnerre does not disclose The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: performing a runway landing simulation for an aircraft.
However, Wiegman does teach The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: performing a runway landing simulation for an aircraft. (Wiegman Paragraph 0004: “In another aspect, a method for transmitting and storing data based on a connection for a vehicle is presented.”) (Wiegman Paragraph 0051: “With continued reference to FIG. 1, the vehicle simulator may be configured to simulate a virtual representation. The virtual representation may represent a virtualization of vehicle model output 120 and/or the expected vehicle model output. As described in this disclosure, a “virtual representation” includes any model or simulation accessible by computing device 112”) (Wiegman Paragraph 0051: “The virtual representation may include an electric aircraft and/or one or more actuator of the electric aircraft. In some cases, at least electric aircraft may include an electric vertical take-off and landing (eVTOL) aircraft”) (Wiegman Paragraph 0119: “Further, an energy source may be capable of providing sufficient power for controlled descent and landing protocols, including, without limitation, hovering descent or runway landing.”)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include The method of claim 1, wherein initiating performance of the one or more aircraft connectivity related actions further comprises: performing a runway landing simulation for an aircraft taught by Wiegman. This would have been for the benefit to provide a method for transmitting and storing data based on a connection for a vehicle is presented. The method includes receiving, by a computing device, a vehicle data, communicatively connecting the computing device to a second device as a function of a mesh network, authenticating a second device as a function of an authentication module, generating a vehicle collection datum as a function of the vehicle data, communicating the vehicle collection datum to the second device as a function of the mesh network, and storing the vehicle collection datum in a recorder database as a function of a lack of identification of the mesh network. [Wiegman Paragraph 0004]
Regarding claim 7, Tonnerre discloses […] is performed when the aircraft is associated with a minimal connectivity impact level of the plurality of connectivity impact levels. (Tonnerre Paragraph 0040: “A representation of predicted connectivity QoE for the rest of the flight (and optionally an indication of the experienced past connectivity QoE) providing prediction of the availability and expected level of connectivity QoE. For instance, a timeline can be used to indicate the time of major events (e.g. gap of connectivity, sufficient QoE level for web browsing, sufficient QoE level for audio streaming, sufficient QoE level for video streaming, sufficient QoE level for immersive virtual reality, etc. ) and/or a map with color-coded route showing such predicted levels of connectivity QoE.”) (Tonnerre Paragraph 0079: “Some embodiments are directed to multiple ways to determine QoE predictions, which may use relatively less computationally intensive approaches for calculation of the average of QoE scoring in a predefined area to work computationally intensive operations using Machine Learning (ML) algorithms”)
Tonnerre does not disclose The method of claim 6, wherein the runway landing simulation
However, Wiegman The method of claim 6, wherein the runway landing simulation (Wiegman Paragraph 0004: “In another aspect, a method for transmitting and storing data based on a connection for a vehicle is presented.”) (Wiegman Paragraph 0051: “With continued reference to FIG. 1, the vehicle simulator may be configured to simulate a virtual representation. The virtual representation may represent a virtualization of vehicle model output 120 and/or the expected vehicle model output. As described in this disclosure, a “virtual representation” includes any model or simulation accessible by computing device 112”) (Wiegman Paragraph 0051: “The virtual representation may include an electric aircraft and/or one or more actuator of the electric aircraft. In some cases, at least electric aircraft may include an electric vertical take-off and landing (eVTOL) aircraft”) (Wiegman Paragraph 0119: “Further, an energy source may be capable of providing sufficient power for controlled descent and landing protocols, including, without limitation, hovering descent or runway landing.”)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include The method of claim 6, wherein the runway landing simulation taught by Wiegman. This would have been for the benefit to provide a method for transmitting and storing data based on a connection for a vehicle is presented. The method includes receiving, by a computing device, a vehicle data, communicatively connecting the computing device to a second device as a function of a mesh network, authenticating a second device as a function of an authentication module, generating a vehicle collection datum as a function of the vehicle data, communicating the vehicle collection datum to the second device as a function of the mesh network, and storing the vehicle collection datum in a recorder database as a function of a lack of identification of the mesh network. [Wiegman Paragraph 0004]
9. Claim(s) 12 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tonnerre (WO 2024263703 A1) in view of (US 20240025545 A1) to Hayot et al. (hereinafter Hayot).
Regarding claim 12, Tonnerre discloses claim 1, accordingly, the rejection of claim 1 is incorporated above.
Tonnerre does not disclose The method of claim 1, wherein the aircraft connectivity prediction model further comprises a regression learning model.
However, Hayot does teach The method of claim 1, wherein the aircraft connectivity prediction model further comprises a regression learning model. (Hayot Paragraph 0012: “In further embodiments of the invention, each predictive model comprises one or more of a Random Forest algorithm, a Neural Network algorithm, a ridge regression algorithm, a Generalized Linear Model using a quasi-Poisson distribution, and/or a Gradient Boosting Machine algorithm.”) (Hayot Paragraph 0112: “These sets of outcome values may be used to predict an estimated demand for internet connectivity services during a flight and to recommend a particular configuration of internet connectivity settings”) (Hayot Paragraph 0114: “First, outcome values can be determined based on a mathematical formula having weighted variables based on the features above. Algorithms that use mathematical formula include Generalized Linear Models and Ridge Regression. Different algorithms may use different mathematical formulae, for example linear, polynomial, or sinusoidal functions. In a training phase, the machine learning model identifies the weighting coefficients which minimize the error between the predictions of the machine learning model and the actual values of the training dataset.”)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include The method of claim 1, wherein the aircraft connectivity prediction model further comprises a regression learning model taught by Hayot. This would have been for the benefit to provide a computer implemented method for training a machine learning model to identify an optimised internet connectivity configuration for an internet service provided to a user during a journey. [Hayot Paragraph 0007]
Regarding claim 19, Tonnerre discloses claim 15, accordingly, the rejection of claim 15 is incorporated above.
Tonnerre does not disclose The apparatus of claim 15, wherein the aircraft connectivity prediction model further comprises a regression learning model.
However, Hayot does teach The apparatus of claim 15, wherein the aircraft connectivity prediction model further comprises a regression learning model. (Hayot Paragraph 0012: “In further embodiments of the invention, each predictive model comprises one or more of a Random Forest algorithm, a Neural Network algorithm, a ridge regression algorithm, a Generalized Linear Model using a quasi-Poisson distribution, and/or a Gradient Boosting Machine algorithm.”) (Hayot Paragraph 0112: “These sets of outcome values may be used to predict an estimated demand for internet connectivity services during a flight and to recommend a particular configuration of internet connectivity settings”) (Hayot Paragraph 0114: “First, outcome values can be determined based on a mathematical formula having weighted variables based on the features above. Algorithms that use mathematical formula include Generalized Linear Models and Ridge Regression. Different algorithms may use different mathematical formulae, for example linear, polynomial, or sinusoidal functions. In a training phase, the machine learning model identifies the weighting coefficients which minimize the error between the predictions of the machine learning model and the actual values of the training dataset.”)
Therefore, it would have been obvious to one of ordinary skill in art before the effective filing date of the claimed invention to have modified Tonnerre to include The apparatus of claim 15, wherein the aircraft connectivity prediction model further comprises a regression learning model taught by Hayot. This would have been for the benefit to provide a computer implemented method for training a machine learning model to identify an optimised internet connectivity configuration for an internet service provided to a user during a journey. [Hayot Paragraph 0007]
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEVIN J HARVEY whose telephone number is 571-272-5327. The examiner can normally be reached 8:00AM-5:00PM M-Th, 8:00AM-4:00PM F.
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/K.J.H./Junior Patent Examiner, Art Unit 3664
/KITO R ROBINSON/Supervisory Patent Examiner, Art Unit 3664
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