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 .
Information Disclosure Statement
The information disclosure statement filed 2/25/2025 and 6/24/2025 fails to comply with 37 CFR 1.98(a)(3)(i) because it does not include a concise explanation of the relevance, as it is presently understood by the individual designated in 37 CFR 1.56(c) most knowledgeable about the content of the information, of each reference listed that is not in the English language. It has been placed in the application file, but the information referred to therein has not been considered. Please see the struck-out references in the IDS filed 2/25/2025 and 6/24/2025.
Claim Interpretation
Regarding claim 6, the limitation “the first render status of the rendering process comprises at least one of a rendering frame rate of the remote rendering device, a rendering time of the remote rendering device, an encoding time of the remote rendering device, an encoding frame rate of the remote rendering device, a decoding rate of the first client device, a decoding time of the first client device, and a client rendering rate of the first client device” uses conjunctive word “and”, and therefore the limitation is interpreted as “the first render status of the rendering process comprises at least one of a rendering frame rate of the remote rendering device, at least one of a rendering time of the remote rendering device, at least one of an encoding time of the remote rendering device, at least one of an encoding frame rate of the remote rendering device, at least one of a decoding rate of the first client device, at least one of a decoding time of the first client device, and at least one of a client rendering rate of the first client device”. See SuperGuide Corp. v. DirecTV Enters., Inc., 358 F.3d 870, 69 U.S.P.Q.2d 1865 (Fed. Cir. 2004).
Claim Objections
Claim 8 is objected to because of the following informalities: on line 4, the limitation “reference filed” appears to be a typo and should be corrected to “reference field”. Appropriate correction is required.
Claim 18 is objected to because of the following informalities: on line 6, the limitation “reference filed” appears to be a typo and should be corrected to “reference field”. Appropriate correction is required.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-4, 7, 9-16 and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cavanaugh et al. (US 2023/0222702, hereinafter Cavanaugh), in view of Adalbjornsson, Stefan (WO 2024/181903, hereinafter Stefan), and further in view of Park (US 2020/0037301).
Regarding claim 1, Cavanaugh teaches a method for visualizing a rendering performance (abstract: generating an aircraft communication visualization map for the target location. The aircraft communication visualization map includes aircraft communication information overlaid upon an image based on the imagery data and the aircraft parking locations at the target location), comprising:
receiving, by a server (server 134, fig. 1), a plurality of (plurality of airport parking locations at an airport) and a plurality of smoothness statuses (plurality of status data such as data transfer rate, cellular and/or Wi-Fi signal connection strength, etc.) respectively associated with the plurality of (devices 142 used within the aircraft 108 corresponds to a first client device; [0013]: a method includes retrieving a plurality of status data associated with aircraft communication at a target location from a database, determining a plurality of geographic location information for a plurality of aircraft parking locations at the target location, accessing a plurality of imagery data associated with a view at the target location; [0031]: The devices 142 can be any type of processing device capable of communicating through the network 135. For instances, the devices 142 can include personal computers, workstations, tablet computers, mobile phones, wearable computing devices, and the like. The devices 142 may connect at a remote location from the server 134 and the ground station 124. Further, the devices 142 may include an electronic flight bag device that can be used within the aircraft 108; [0040]: The server 134 can gather data from multiple data sources which collect wireless communication metrics from previous wireless transfers from aircraft 108 at various locations at each airport. The results can be visually depicted on the aircraft communication visualization map 300 to assist in determining where and when to transfer data stored on the aircraft 108. The aircraft communication visualization map 300 can also assist in predicting how long a data transfer may typically take, where the data transfer location is known. The aircraft communication visualization map 300 may also be used to trigger other actions. For example, aircraft parking location 302 may have twice the data transfer rate as aircraft parking locations 304 and 306, and aircraft parking location 302 may have four times the data transfer rate as aircraft parking location 308. Therefore, an operator of aircraft 108 scheduled to be parked at aircraft parking location 308 may prefer to delay transferring of data until located at a higher transfer rate location or departure scheduling may need to be adjusted to provide adequate time for the data transfer. There may be airport areas, such as airport area 310, where data transfer rates are very low or wireless communication is not possible with the ground station 124 of FIG. 1. When the aircraft 108 is at aircraft parking location 312 in the airport area 310, it may trigger a notification for a maintenance crew to bring a near-wing maintenance computer 126 to the aircraft 108 for data transfer, and the near-wing maintenance computer 126 can be physically moved to a location where the data can be accessed, e.g., closer to one or more network interface components 128; [0046]: The status data can include aircraft information and aircraft communication history of one or more wireless interfaces used to transfer data from an aircraft 108. The aircraft information can include an identifier (e.g., aircraft registration number, aircraft serial number) of the aircraft 108 and a location of performing a transfer of data to/from the aircraft, such as GPS coordinates. The aircraft communication history can include a signal strength, an amount of data transferred, and a duration of transferring the data to/from the aircraft 108. The signal strength can include multiple communication types, such as a cellular signal strength and/or a Wi-Fi signal strength); and
outputting, by the server, a rendering performance map (communication visualization map 300, fig. 3) based on the plurality of (aircraft parking locations/multiple areas of the airport used by a same airline) and the associated plurality of smoothness statuses (average data transfer rate/average wireless signal strength), wherein the rendering performance map comprises a plurality of (visual indictors associated with average data transfer rate; [0030]: The server 134 can include a processing system 136 and a memory system 138 configured to store a plurality of computer executable instructions for execution by the processing system 136 and/or data; [0040]: The aircraft communication visualization map 300 can be generated by the server 134 of FIG. 1 for display on one or more of the devices 142 of FIG. 1; [0049]: The aircraft communication visualization map 300 can include one or more visual indicators associated with an average data transfer rate at the aircraft parking locations; [0050]: the processing system 136 can output to the aircraft communication visualization map 300, an average wireless signal strength for one or more of: an area of an airport, multiple areas of the airport used by a same airline, and a plurality of airports used by the same airline. In some embodiments, the processing system 136 can output to the aircraft communication visualization map 300, an average wireless transfer rate for a plurality of airports used by the same airline. Other types of outputs can be overlaid on the aircraft communication visualization map 300).
Cavanaugh does not explicitly teach a rendering performance map is based on a plurality of smoothness statuses respectively associated with the plurality of poses, and the rendering performance map comprises a plurality of directional smoothness indicators.
Stefan teaches the rendering performance map (building a map) is based on a plurality of smoothness statuses (plurality of key performance indicators, KPIs, related to the quality of signal strength of the communication channel) respectively associated with the plurality of poses (plurality of poses of the mobile device corresponds to the plurality of poses of the first client device; [0027]: storing (i) a plurality of poses of the mobile device, and (ii) a plurality of key performance indicators, KPIs, related to the quality of the communication channel. Respective poses from the plurality of poses are associated with at least one respective KPI related to the quality of the communication channel; [0033]: The plurality of KPIs, in some embodiments, include at least one metric of the quality of the communication channel; [0061]: the computing (operation 206 of Figure 2) includes building a map for the mobile device of a first plurality of poses that satisfy a KPI representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI; claim 9: the failure is identified based on a metric related to signal strength of the link falling below a threshold value; claim 16: building a map for the mobile device of a first plurality of poses that satisfy a key performance indicator, KPI, representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Stefan’s knowledge of building a map for a mobile device based on a plurality of poses of the mobile device and the associated quality of signal strength of the communication channel and modify the process of Cavanaugh because such a process evaluates and displays information for an improved communication channel between the mobile device and a network node ([0007]).
Park teaches the rendering performance map (communication environment map, fig. 14) comprises a plurality of directional smoothness indicators (for each position included in the communication environment map, a corresponding optimal beam direction and signal strength in the corresponding beam direction are also included; plurality of beam direction and signal strength as shown in fig. 14 are functionally analogous to a plurality of directional smoothness indicators; [0298]: The position-dependent beam information here may include positional information and beam-direction information relating to the positional information, and the beam-direction information may include a beam direction in which the strongest signal strength is obtained for each spatial section that results from division by the positional information, and a value of signal strength in the beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information may be configured with a value of a position (coordinates representing a position), a beam index (a beam direction), and a value of signal strength (signal quality) in this order; [0299]: In Step S1310, the vehicle 10 determines the direction of transmitted or received beam based on a drive path for the vehicle 10 and the received communication environment map. For example, the vehicle 10 may acquire an optimal beam direction for a position on a path along which the vehicle 10 is currently driving and signal strength for the corresponding beam direction, from the communication environment map, and may determine a beam that is to be used to transmit or receive a signal, using the optimal beam direction and the signal strength; [0306]: The communication environment map, as illustrated in FIG. 14, includes an optimal beam direction for each position and signal strength in the corresponding beam direction. For example, with reference to FIG. 14, the communication environment map may include an optimal beam direction in which communication with a base station 1230 is possible depending on each position, and signal strength (strong, weak, or communication-unachieved) in the corresponding beam direction). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Park’s knowledge of providing a plurality of beam directions with a corresponding signal strength for each position in the communication environment map as taught and modify the process of Cavanaugh and Stefan because such a process provides wireless communication in a vehicle in an autonomous system that is capable of decreasing path loss ([0021]).
Claims 16 and 20 are similar in scope to claim1, and therefore the examiner provides similar rationale to reject these claims. Moreover, Cavanaugh teaches a server (server 134, fig. 1 and [0030]), comprising a non-transitory storage circuit (memory system 138, fig. 1 and [0030]), storing a program code (to store a plurality of computer executable instructions, [0030]); and a processor (processing system 136, fig. 1 and [0030]), coupled to the non-transitory storage circuit and configured to execute the program code (execution by the processing system 136, [0030]). Further, Cavanaugh teaches a non-transitory computer readable storage medium ([0030], [0033] and [0036]).
Regarding claim 2, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 1, wherein the plurality of poses comprise a first pose (aircraft parking location 302, fig. 3 and [0040]), the plurality of smoothness statuses comprise a first smoothness status (data transfer rate, [0040]) associated with the first pose (data transfer rate associated with aircraft parking location 302, fig. 3 and [0040] - Cavanaugh), and the first smoothness status is detected in a case where the first client device is with the first pose (detecting wireless signal strength/quality of communication at a gate of an airport is functionally analogous to detecting a smoothness status when the first client is with the first pose; Cavanaugh - [0042]: The signal strength displayed with the wireless interface usage distribution 316 can include an average wireless signal strength for one or more of: an area of an airport (e.g., one or more gates/parking locations); Stefan – [0051]: the information related to motion of the mobile device includes motion that resulted in the current pose of the mobile device, the coverage metric signal indicates a lack of coverage, the evaluating (operation 204 of Figure 2) includes deciding whether the lack of coverage occurred at about the time of the motion that resulted in the current pose of the mobile device; Stefan – [0027]: storing (i) a plurality of poses of the mobile device, and (ii) a plurality of key performance indicators, KPIs, related to the quality of the communication channel. Respective poses from the plurality of poses are associated with at least one respective KPI related to the quality of the communication channel; Stefan – [0033]: The plurality of KPIs, in some embodiments, include at least one metric of the quality of the communication channel; Stefan – [0061]: the computing (operation 206 of Figure 2) includes building a map for the mobile device of a first plurality of poses that satisfy a KPI representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI).
Regarding claim 3, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 2, wherein the first smoothness status comprises a first wireless communication quality of the first client device (devices 142 used within the aircraft 108 corresponds to a first client device; Cavanaugh – [0016]: outputting to the aircraft communication visualization map, an average wireless signal strength for one or more of: an area of an airport, multiple areas of the airport used by a same airline, and a plurality of airports used by the same airline; Cavanaugh - [0031]: The devices 142 can be any type of processing device capable of communicating through the network 135. For instances, the devices 142 can include personal computers, workstations, tablet computers, mobile phones, wearable computing devices, and the like. The devices 142 may connect at a remote location from the server 134 and the ground station 124. Further, the devices 142 may include an electronic flight bag device that can be used within the aircraft 108; Cavanaugh – [0046]: The status data can include aircraft information and aircraft communication history of one or more wireless interfaces used to transfer data from an aircraft 108. The aircraft information can include an identifier (e.g., aircraft registration number, aircraft serial number) of the aircraft 108 and a location of performing a transfer of data to/from the aircraft, such as GPS coordinates. The aircraft communication history can include a signal strength, an amount of data transferred, and a duration of transferring the data to/from the aircraft 108. The signal strength can include multiple communication types, such as a cellular signal strength and/or a Wi-Fi signal strength; Stefan – [0027]: a plurality of key performance indicators, KPIs, related to the quality of the communication channel; Park – [0306]: For example, with reference to FIG. 14, the communication environment map may include an optimal beam direction in which communication with a base station 1230 is possible depending on each position, and signal strength (strong, weak, or communication-unachieved) in the corresponding beam direction) communicating with a remote rendering device of the first client device (Cavanaugh – server 134, fig. 1 and [0031]).
Regarding claim 4, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 3, wherein the server (server 134, fig. 1 - Cavanaugh) is the remote rendering device of the first client device (device 142, fig. 1 Cavanaugh; Cavanaugh – [0031]: The devices 142 can be any type of processing device capable of communicating through the network 135. For instances, the devices 142 can include personal computers, workstations, tablet computers, mobile phones, wearable computing devices, and the like. The devices 142 may connect at a remote location from the server 134 and the ground station 124. Further, the devices 142 may include an electronic flight bag device that can be used within the aircraft 108; Cavanaugh – [0040]: The aircraft communication visualization map 300 can be generated by the server 134 of FIG. 1 for display on one or more of the devices 142 of FIG. 1. For instance, when airline support personnel or a flight crew of the aircraft 108 of Fig. 1 determine that a wireless transfer of data should occur for the aircraft 108 at a particular airport, an application or web page on one of the devices 142 can display the aircraft communication visualization map 300 as generated by the server 134; Cavanaugh – [0050]: the processing system 136 can output to the aircraft communication visualization map 300, an average wireless signal strength for one or more of: an area of an airport, multiple areas of the airport used by a same airline, and a plurality of airports used by the same airline. In some embodiments, the processing system 136 can output to the aircraft communication visualization map 300, an average wireless transfer rate for a plurality of airports used by the same airline. Other types of outputs can be overlaid on the aircraft communication visualization map 300).
Regarding claim 7, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 1, wherein the plurality of poses (Cavanaugh - plurality of airport parking locations at an airport; Stefan - plurality of poses of the mobile device corresponds to the plurality of poses of the first client device) and the associated plurality of smoothness statuses (Cavanaugh - plurality of status data such as data transfer rate, cellular and/or Wi-Fi signal connection strength, etc.; Stefan - plurality of key performance indicators, KPIs, related to the quality of signal strength of the communication channel) are detected by the first client device (Cavanaugh - device 142; Stefan - first client device) in a reference field (airport corresponds to a reference field; Cavanaugh - [0013]: a method includes retrieving a plurality of status data associated with aircraft communication at a target location from a database, determining a plurality of geographic location information for a plurality of aircraft parking locations at the target location, accessing a plurality of imagery data associated with a view at the target location; Cavanaugh - [0040]: The server 134 can gather data from multiple data sources which collect wireless communication metrics from previous wireless transfers from aircraft 108 at various locations at each airport. The results can be visually depicted on the aircraft communication visualization map 300 to assist in determining where and when to transfer data stored on the aircraft 108. The aircraft communication visualization map 300 can also assist in predicting how long a data transfer may typically take, where the data transfer location is known. The aircraft communication visualization map 300 may also be used to trigger other actions. For example, aircraft parking location 302 may have twice the data transfer rate as aircraft parking locations 304 and 306, and aircraft parking location 302 may have four times the data transfer rate as aircraft parking location 308. Therefore, an operator of aircraft 108 scheduled to be parked at aircraft parking location 308 may prefer to delay transferring of data until located at a higher transfer rate location or departure scheduling may need to be adjusted to provide adequate time for the data transfer. There may be airport areas, such as airport area 310, where data transfer rates are very low or wireless communication is not possible with the ground station 124 of FIG. 1. When the aircraft 108 is at aircraft parking location 312 in the airport area 310, it may trigger a notification for a maintenance crew to bring a near-wing maintenance computer 126 to the aircraft 108 for data transfer, and the near-wing maintenance computer 126 can be physically moved to a location where the data can be accessed, e.g., closer to one or more network interface components 128; Cavanaugh - [0042]: The signal strength displayed with the wireless interface usage distribution 316 can include an average wireless signal strength for one or more of: an area of an airport (e.g., one or more gates/parking locations), multiple areas of the airport used by a same airline (e.g., all locations used by the airline at the same airport); Cavanaugh - [0046]: The status data can include aircraft information and aircraft communication history of one or more wireless interfaces used to transfer data from an aircraft 108. The aircraft information can include an identifier (e.g., aircraft registration number, aircraft serial number) of the aircraft 108 and a location of performing a transfer of data to/from the aircraft, such as GPS coordinates. The aircraft communication history can include a signal strength, an amount of data transferred, and a duration of transferring the data to/from the aircraft 108. The signal strength can include multiple communication types, such as a cellular signal strength and/or a Wi-Fi signal strength; Stefan - [0027]: storing (i) a plurality of poses of the mobile device, and (ii) a plurality of key performance indicators, KPIs, related to the quality of the communication channel. Respective poses from the plurality of poses are associated with at least one respective KPI related to the quality of the communication channel; Stefan - [0033]: The plurality of KPIs, in some embodiments, include at least one metric of the quality of the communication channel; Stefan - [0061]: the computing (operation 206 of Figure 2) includes building a map for the mobile device of a first plurality of poses that satisfy a KPI representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI; Stefan - claim 9: the failure is identified based on a metric related to signal strength of the link falling below a threshold value; Stefan - claim 16: building a map for the mobile device of a first plurality of poses that satisfy a key performance indicator, KPI, representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI).
Regarding claim 9, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 2, wherein the plurality of the directional smoothness indicators (Cavanaugh - visual indictors associated with average data transfer rate; Park - plurality of beam direction and signal strength as shown in fig. 14 are functionally analogous to a plurality of directional smoothness indicators) comprise a first directional smoothness indicator (Cavanaugh - visual indictor associated with average data transfer rate for a first airport parking location 302; Park - for each position included in the communication environment map, a corresponding optimal beam direction and signal strength in the corresponding beam direction are also included; Park - beam direction and signal strength for a first position is functionally analogous to a first directional smoothness indicator) determined based on the first pose (data transfer rate associated with aircraft parking location 302, fig. 3 and [0040] – Cavanaugh; Stefan - current pose corresponds to a first pose; vehicle orientation data and position data related to current position of the vehicle is functionally analogous to a first pose of the vehicle, Park – [0171], [0173] and [0237]) and the associated first smoothness status (data transfer rate, [0040] – Cavanaugh; wireless signal strength, [0042]- Cavanaugh; Cavanaugh – detecting wireless signal strength/quality of communication at a gate of an airport is functionally analogous to detecting a smoothness status when the first client is with the first pose; Cavanaugh - [0030]: The server 134 can include a processing system 136 and a memory system 138 configured to store a plurality of computer executable instructions for execution by the processing system 136 and/or data; Cavanaugh - [0040]: The aircraft communication visualization map 300 can be generated by the server 134 of FIG. 1 for display on one or more of the devices 142 of FIG. 1; Cavanaugh - [0042]: The signal strength displayed with the wireless interface usage distribution 316 can include an average wireless signal strength for one or more of: an area of an airport (e.g., one or more gates/parking locations); Cavanaugh - [0049]: The aircraft communication visualization map 300 can include one or more visual indicators associated with an average data transfer rate at the aircraft parking locations; Cavanaugh - [0050]: the processing system 136 can output to the aircraft communication visualization map 300, an average wireless signal strength for one or more of: an area of an airport, multiple areas of the airport used by a same airline, and a plurality of airports used by the same airline. In some embodiments, the processing system 136 can output to the aircraft communication visualization map 300, an average wireless transfer rate for a plurality of airports used by the same airline. Other types of outputs can be overlaid on the aircraft communication visualization map 300; Stefan – [0051]: the information related to motion of the mobile device includes motion that resulted in the current pose of the mobile device, the coverage metric signal indicates a lack of coverage, the evaluating (operation 204 of Figure 2) includes deciding whether the lack of coverage occurred at about the time of the motion that resulted in the current pose of the mobile device; Stefan – [0027]: storing (i) a plurality of poses of the mobile device, and (ii) a plurality of key performance indicators, KPIs, related to the quality of the communication channel. Respective poses from the plurality of poses are associated with at least one respective KPI related to the quality of the communication channel; Stefan – [0033]: The plurality of KPIs, in some embodiments, include at least one metric of the quality of the communication channel; Stefan – [0061]: the computing (operation 206 of Figure 2) includes building a map for the mobile device of a first plurality of poses that satisfy a KPI representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI; Park – [0171]: the sensing unit 270 generates vehicle orientation data; Park – [0173]: The position data generation device 280 can generate position data of the vehicle 10 on the basis of a signal generated from at least one of the GPS and the DGPS; Park – [0237]: navigation information includes information on the current position of the vehicle and vehicle state information includes vehicle orientation; Park - [0298]: The position-dependent beam information here may include positional information and beam-direction information relating to the positional information, and the beam-direction information may include a beam direction in which the strongest signal strength is obtained for each spatial section that results from division by the positional information, and a value of signal strength in the beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information may be configured with a value of a position (coordinates representing a position), a beam index (a beam direction), and a value of signal strength (signal quality) in this order; Park - [0299]: In Step S1310, the vehicle 10 determines the direction of transmitted or received beam based on a drive path for the vehicle 10 and the received communication environment map. For example, the vehicle 10 may acquire an optimal beam direction for a position on a path along which the vehicle 10 is currently driving and signal strength for the corresponding beam direction, from the communication environment map, and may determine a beam that is to be used to transmit or receive a signal, using the optimal beam direction and the signal strength; Park - [0306]: The communication environment map, as illustrated in FIG. 14, includes an optimal beam direction for each position and signal strength in the corresponding beam direction. For example, with reference to FIG. 14, the communication environment map may include an optimal beam direction in which communication with a base station 1230 is possible depending on each position, and signal strength (strong, weak, or communication-unachieved) in the corresponding beam direction).
Regarding claim 10, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 9, wherein the first pose (data transfer rate associated with aircraft parking location 302, fig. 3 and [0040] – Cavanaugh; Stefan - current pose corresponds to a first pose; vehicle orientation data and position data related to current position of the vehicle is functionally analogous to a first pose of the vehicle, Park – [0171], [0173] and [0237]) comprises a position (aircraft parking location 302, fig. 3 and [0040] - Cavanaugh; Park – [0173]: The position data generation device 280 can generate position data of the vehicle 10 on the basis of a signal generated from at least one of the GPS and the DGPS;) and an orientation (Park – [0171]: the sensing unit 270 generates vehicle orientation data), the first directional smoothness indicator (Cavanaugh - visual indictor associated with average data transfer rate for a first airport parking location 302; Park - for each position included in the communication environment map, a corresponding optimal beam direction and signal strength in the corresponding beam direction are also included; Park - beam direction and signal strength for a first position is functionally analogous to a first directional smoothness indicator) comprises a first smoothness indicator (Cavanaugh - visual indictor associated with average data transfer rate for a first airport parking location 302; Park - for each position included in the communication environment map, a signal strength in the corresponding beam direction is also included; fig. 14 of Park shows indicators such as “Strong”, “Weak” or “Communication Unachieved” for indicating signal strength (signal quality) in corresponding beam direction; Park – [0298]: the position-dependent beam information, as described in FIG. 14, may include signal strength (signal quality) in the corresponding beam direction) and a first directional indicator (Park - for each position included in the communication environment map, a corresponding optimal beam direction is also included; fig. 14 of Park shows the optimal beam direction (a beam angle) as directional indicators representing each position; Park – [0298]: the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position); wherein the first smoothness indicator corresponds to the first smoothness status (Cavanaugh - visual indictor associated with average data transfer rate for a first airport parking location 302; Cavanaugh – [0049]: The aircraft communication visualization map 300 can include one or more visual indicators associated with an average data transfer rate at the aircraft parking locations; Park - for each position included in the communication environment map, a signal strength in the corresponding beam direction is also included; fig. 14 of Park shows indicators such as “Strong”, “Weak” or “Communication Unachieved” for indicating signal strength (signal quality) in corresponding beam direction; Park – [0298]: the position-dependent beam information, as described in FIG. 14, may include signal strength (signal quality) in the corresponding beam direction), a first position of the first smoothness indicator (Cavanaugh – as shown in fig. 3, at a first airport parking location 302, the circular shape with patterns inside shows the data transfer rate at that location; Cavanaugh – [0041]: data transfer and/or connection strength information summarized in shapes, colors, and/or patterns for an airline; Cavanaugh – [0043]: the key 320 may indicate how various shapes, colors, and/or patterns map to data transfer rate, signal strength and/or communication method, such as WIFI or cellular; Park – signal strength indicator as shown in fig. 14; fig. 14 of Park shows indicators such as “Strong”, “Weak” or “Communication Unachieved” for indicating signal strength (signal quality) in corresponding beam direction) in the rendering performance map (communication visualization map 300, fig. 3 - Cavanaugh; Park - communication environment map) corresponds to the position of the first pose (airport parking location 302, fig. 3 – Cavanaugh; Park - for each position included in the communication environment map, a signal strength in the corresponding beam direction is also included; fig. 14 of Park shows indicators such as “Strong”, “Weak” or “Communication Unachieved” for indicating signal strength (signal quality) in corresponding beam direction; Park – [0298]: the position-dependent beam information, as described in FIG. 14, may include signal strength (signal quality) in the corresponding beam direction), and the first directional indicator corresponds to the orientation of the first pose (Park - for each position included in the communication environment map, a corresponding optimal beam direction is also included; fig. 14 of Park shows the optimal beam direction (a beam angle) as directional indicators representing each position; data transfer rate, [0040] – Cavanaugh; wireless signal strength, [0042]- Cavanaugh; Cavanaugh – detecting wireless signal strength/quality of communication at a gate of an airport is functionally analogous to detecting a smoothness status when the first client is with the first pose; Cavanaugh - [0030]: The server 134 can include a processing system 136 and a memory system 138 configured to store a plurality of computer executable instructions for execution by the processing system 136 and/or data; Cavanaugh - [0040]: The aircraft communication visualization map 300 can be generated by the server 134 of FIG. 1 for display on one or more of the devices 142 of FIG. 1; Cavanaugh - [0042]: The signal strength displayed with the wireless interface usage distribution 316 can include an average wireless signal strength for one or more of: an area of an airport (e.g., one or more gates/parking locations); Cavanaugh - [0049]: The aircraft communication visualization map 300 can include one or more visual indicators associated with an average data transfer rate at the aircraft parking locations; Cavanaugh - [0050]: the processing system 136 can output to the aircraft communication visualization map 300, an average wireless signal strength for one or more of: an area of an airport, multiple areas of the airport used by a same airline, and a plurality of airports used by the same airline. In some embodiments, the processing system 136 can output to the aircraft communication visualization map 300, an average wireless transfer rate for a plurality of airports used by the same airline. Other types of outputs can be overlaid on the aircraft communication visualization map 300; Stefan – [0051]: the information related to motion of the mobile device includes motion that resulted in the current pose of the mobile device, the coverage metric signal indicates a lack of coverage, the evaluating (operation 204 of Figure 2) includes deciding whether the lack of coverage occurred at about the time of the motion that resulted in the current pose of the mobile device; Stefan – [0027]: storing (i) a plurality of poses of the mobile device, and (ii) a plurality of key performance indicators, KPIs, related to the quality of the communication channel. Respective poses from the plurality of poses are associated with at least one respective KPI related to the quality of the communication channel; Stefan – [0033]: The plurality of KPIs, in some embodiments, include at least one metric of the quality of the communication channel; Stefan – [0061]: the computing (operation 206 of Figure 2) includes building a map for the mobile device of a first plurality of poses that satisfy a KPI representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI; Park – [0171]: the sensing unit 270 generates vehicle orientation data; Park – [0173]: The position data generation device 280 can generate position data of the vehicle 10 on the basis of a signal generated from at least one of the GPS and the DGPS; Park – [0237]: navigation information includes information on the current position of the vehicle and vehicle state information includes vehicle orientation; Park - [0298]: The position-dependent beam information here may include positional information and beam-direction information relating to the positional information, and the beam-direction information may include a beam direction in which the strongest signal strength is obtained for each spatial section that results from division by the positional information, and a value of signal strength in the beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information may be configured with a value of a position (coordinates representing a position), a beam index (a beam direction), and a value of signal strength (signal quality) in this order; Park - [0299]: In Step S1310, the vehicle 10 determines the direction of transmitted or received beam based on a drive path for the vehicle 10 and the received communication environment map. For example, the vehicle 10 may acquire an optimal beam direction for a position on a path along which the vehicle 10 is currently driving and signal strength for the corresponding beam direction, from the communication environment map, and may determine a beam that is to be used to transmit or receive a signal, using the optimal beam direction and the signal strength; Park - [0306]: The communication environment map, as illustrated in FIG. 14, includes an optimal beam direction for each position and signal strength in the corresponding beam direction. For example, with reference to FIG. 14, the communication environment map may include an optimal beam direction in which communication with a base station 1230 is possible depending on each position, and signal strength (strong, weak, or communication-unachieved) in the corresponding beam direction).
Regarding claim 11, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 10, wherein a visual type (Cavanaugh – as shown in fig. 3, the circular shapes with patterns indicating the data transfer rate at the airport parking locations are displayed differently for parking location 302, 304 and 308 as they indicate different data transfer rate; Park – as shown in fig. 14, the ) of the first smoothness indicator is determined based on the first smoothness status (Cavanaugh – as shown in fig. 3, at a first airport parking location 302, the circular shape with patterns inside shows the data transfer rate at that location; Cavanaugh – [0041]: data transfer and/or connection strength information summarized in shapes, colors, and/or patterns for an airline; Cavanaugh – [0043]: the key 320 may indicate how various shapes, colors, and/or patterns map to data transfer rate, signal strength and/or communication method, such as WiFi or cellular; Park – signal strength indicator as shown in fig. 14; fig. 14 of Park shows indicators such as “Strong”, “Weak” or “Communication Unachieved” for indicating signal strength (signal quality) in corresponding beam direction), and a direction where the first directional indicator points is determined based on the orientation of the first pose (Park - for each position included in the communication environment map, a corresponding optimal beam direction is also included; fig. 14 of Park shows the optimal beam direction (a beam angle) as directional indicators representing each position based on the orientation of the vehicle; Park – [0173]: The position data generation device 280 can generate position data of the vehicle 10 on the basis of a signal generated from at least one of the GPS and the DGPS; Park – [0237]: navigation information includes information on the current position of the vehicle and vehicle state information includes vehicle orientation; Park - [0298]: The position-dependent beam information here may include positional information and beam-direction information relating to the positional information, and the beam-direction information may include a beam direction in which the strongest signal strength is obtained for each spatial section that results from division by the positional information, and a value of signal strength in the beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information may be configured with a value of a position (coordinates representing a position), a beam index (a beam direction), and a value of signal strength (signal quality) in this order; Park - [0299]: In Step S1310, the vehicle 10 determines the direction of transmitted or received beam based on a drive path for the vehicle 10 and the received communication environment map. For example, the vehicle 10 may acquire an optimal beam direction for a position on a path along which the vehicle 10 is currently driving and signal strength for the corresponding beam direction, from the communication environment map, and may determine a beam that is to be used to transmit or receive a signal, using the optimal beam direction and the signal strength; Park - [0306]: The communication environment map, as illustrated in FIG. 14, includes an optimal beam direction for each position and signal strength in the corresponding beam direction. For example, with reference to FIG. 14, the communication environment map may include an optimal beam direction in which communication with a base station 1230 is possible depending on each position, and signal strength (strong, weak, or communication-unachieved) in the corresponding beam direction).
Regarding claim 12, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 1, further comprising: receiving, by the server (Cavanaugh - server 134, fig. 1), a plurality of other poses (Cavanaugh - plurality of airport parking locations at multiple airports; Stefan - plurality of poses of the mobile device) and a plurality of other smoothness statuses (Cavanaugh - plurality of status data such as data transfer rate, cellular and/or Wi-Fi signal connection strength, etc.; Stefan - plurality of key performance indicators, KPIs, related to the quality of signal strength of the communication channel) respectively associated with the plurality of other poses from a second client device (Cavanaugh – a sever can gather data from multiple data sources such as a second device 142 used within the aircraft 108 at a different airport, wherein the second device 142 used within aircraft 108 at a different airport corresponds to a second client device; Cavanaugh - [0013]: a method includes retrieving a plurality of status data associated with aircraft communication at a target location from a database, determining a plurality of geographic location information for a plurality of aircraft parking locations at the target location, accessing a plurality of imagery data associated with a view at the target location; Cavanaugh - [0031]: The devices 142 can be any type of processing device capable of communicating through the network 135. For instances, the devices 142 can include personal computers, workstations, tablet computers, mobile phones, wearable computing devices, and the like. The devices 142 may connect at a remote location from the server 134 and the ground station 124. Further, the devices 142 may include an electronic flight bag device that can be used within the aircraft 108; Cavanaugh - [0040]: The server 134 can gather data from multiple data sources which collect wireless communication metrics from previous wireless transfers from aircraft 108 at various locations at each airport. The results can be visually depicted on the aircraft communication visualization map 300 to assist in determining where and when to transfer data stored on the aircraft 108. The aircraft communication visualization map 300 can also assist in predicting how long a data transfer may typically take, where the data transfer location is known. The aircraft communication visualization map 300 may also be used to trigger other actions. For example, aircraft parking location 302 may have twice the data transfer rate as aircraft parking locations 304 and 306, and aircraft parking location 302 may have four times the data transfer rate as aircraft parking location 308. Therefore, an operator of aircraft 108 scheduled to be parked at aircraft parking location 308 may prefer to delay transferring of data until located at a higher transfer rate location or departure scheduling may need to be adjusted to provide adequate time for the data transfer. There may be airport areas, such as airport area 310, where data transfer rates are very low or wireless communication is not possible with the ground station 124 of FIG. 1. When the aircraft 108 is at aircraft parking location 312 in the airport area 310, it may trigger a notification for a maintenance crew to bring a near-wing maintenance computer 126 to the aircraft 108 for data transfer, and the near-wing maintenance computer 126 can be physically moved to a location where the data can be accessed, e.g., closer to one or more network interface components 128; [0046]: The status data can include aircraft information and aircraft communication history of one or more wireless interfaces used to transfer data from an aircraft 108. The aircraft information can include an identifier (e.g., aircraft registration number, aircraft serial number) of the aircraft 108 and a location of performing a transfer of data to/from the aircraft, such as GPS coordinates. The aircraft communication history can include a signal strength, an amount of data transferred, and a duration of transferring the data to/from the aircraft 108. The signal strength can include multiple communication types, such as a cellular signal strength and/or a Wi-Fi signal strength); and modifying (Cavanaugh – customizing the communication visualization map 300 to display data gathered from multiple data sources which collect wireless communication metrics from the aircraft 108 at various locations at multiple airports is functionally analogous to modifying the communication visualization map 300 to display data indicating wireless communication metrics gathered by multiple devices at different airports), by the server, the rendering performance map (communication visualization map 300, fig. 3 – Cavanaugh; building a map - Stefan) based on the plurality of other poses (aircraft parking locations/multiple areas of a different airport used by a same airline, [0040] – Cavanaugh; Stefan - plurality of poses of the mobile device) and the associated plurality of other smoothness statuses (Cavanaugh - visual indictors associated with average data transfer rate correspond to other smoothness statuses; Stefan - plurality of key performance indicators, KPIs, related to the quality of signal strength of the communication channel; Cavanaugh - [0030]: The server 134 can include a processing system 136 and a memory system 138 configured to store a plurality of computer executable instructions for execution by the processing system 136 and/or data; Cavanaugh - [0040]: The aircraft communication visualization map 300 can be generated by the server 134 of FIG. 1 for display on one or more of the devices 142 of FIG. 1. For instance, when airline support personnel or a flight crew of the aircraft 108 of FIG. 1 determine that a wireless transfer of data should occur for the aircraft 108 at a particular airport, an application or web page on one of the devices 142 can display the aircraft communication visualization map 300 as generated by the server 134. The aircraft communication visualization map 300 can be customized to view data specific to an airline fleet at airports where the airline operates. The server 134 can gather data from multiple data sources which collect wireless communication metrics from previous wireless transfers from aircraft 108 at various locations at each airport. The results can be visually depicted on the aircraft communication visualization map 300 to assist in determining where and when to transfer data stored on the aircraft 108; Cavanaugh - [0049]: The aircraft communication visualization map 300 can include one or more visual indicators associated with an average data transfer rate at the aircraft parking locations; Cavanaugh - [0050]: the processing system 136 can output to the aircraft communication visualization map 300, an average wireless signal strength for one or more of: an area of an airport, multiple areas of the airport used by a same airline, and a plurality of airports used by the same airline. In some embodiments, the processing system 136 can output to the aircraft communication visualization map 300, an average wireless transfer rate for a plurality of airports used by the same airline. Other types of outputs can be overlaid on the aircraft communication visualization map 300; Stefan - [0027]: storing (i) a plurality of poses of the mobile device, and (ii) a plurality of key performance indicators, KPIs, related to the quality of the communication channel. Respective poses from the plurality of poses are associated with at least one respective KPI related to the quality of the communication channel; [0033]: The plurality of KPIs, in some embodiments, include at least one metric of the quality of the communication channel; [0061]: the computing (operation 206 of Figure 2) includes building a map for the mobile device of a first plurality of poses that satisfy a KPI representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI; claim 9: the failure is identified based on a metric related to signal strength of the link falling below a threshold value; claim 16: building a map for the mobile device of a first plurality of poses that satisfy a key performance indicator, KPI, representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI)).
Regarding claim 13, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 1, further comprising: transmitting, by the server (server 134), the rendering performance map (communication visualization map 300) to the first client device (device 142; communication visualization map 300 is generated by the server 134 and displayed by device 142 inherently involves the transmitting the data before it can be displayed on device 142; Cavanaugh – [0040]: when airline support personnel or a flight crew of the aircraft 108 of FIG. 1 determine that a wireless transfer of data should occur for the aircraft 108 at a particular airport, an application or web page on one of the devices 142 can display the aircraft communication visualization map 300 as generated by the server 134).
Regarding claim 14, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 13, further comprising: rendering, by the first client device (Stefan – fig. 3: mobile device 100; Park – first display device 410), a mixed reality visual content (Stefan – claim 19: the mobile device comprises at least one of (i) an extended reality, XR, device, (ii) an augmented reality, AR, device, and (iii) a virtual reality, VR device; Park – [0237]: the first area 411 may display at least one of graphic objects corresponding to can display entertainment content (e.g., movies, sports, shopping, food, etc.), video conferences, food menu and augmented reality screens) based on a field of view of the first client device (Stefan - [0064]: operation 208 indicates to a wearer of the mobile device 100 how to change position and orientation to achieve a better KPI for the mobile device 100. If the desirable position is within the field of view of the mobile device 100, an indicator such as an “x” marking is rendered on ground where the user should stand, for example. If a set of desirable/candidate poses includes many points, a colored area, e.g., “green”, can be used to indicate an area to which the mobile device 100 can be moved, for example; Stefan – [0065]: To indicate a correct orientation, a marking can be displayed on a user interface of the mobile device 100 relative to the current position of the mobile device 100, but with the desirable/candidate orientation being marked at a corresponding azimuth and elevation angles; Stefan - [0066]: If the markings are not in the field of view of the mobile device 100, the indicator can be shown projected to the edge of the field of view, e.g., as a green light, to indicate in which direction to move the mobile device 100/look with the mobile device 100) and the plurality of directional smoothness indicators (Park - for each position included in the communication environment map, a corresponding optimal beam direction and signal strength in the corresponding beam direction are also included; Park - plurality of beam direction and signal strength as shown in fig. 14 are functionally analogous to a plurality of directional smoothness indicators) in the rendering performance map (Cavanaugh – fig. 3: communication visualization map 300; Stefan – [0061]: a map for the mobile device of a first plurality of poses that satisfy a KPI representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI; Park – fig. 14: communication environment map), wherein the mixed reality visual content comprises a plurality of virtual objects (Cavanaugh – [0042]: Various types of icons and overlays can be available for display on the aircraft communication visualization map 300; Stefan – [0063]: virtual object) rendered based on the plurality of directional smoothness indicators (Stefan – [0063]: a virtual object can be placed in a position so that a user of the mobile device 100 needs to move to obtain access; Cavanaugh – visual indictors associated with average data transfer rate) respectively associated with the plurality of poses (Cavanaugh - aircraft parking locations/multiple areas of the airport used by a same airline correspond to the plurality of poses; Stefan - plurality of poses of the mobile device corresponds to the plurality of poses of the first client device; Cavanaugh - [0030]: The server 134 can include a processing system 136 and a memory system 138 configured to store a plurality of computer executable instructions for execution by the processing system 136 and/or data; Cavanaugh - [0040]: The aircraft communication visualization map 300 can be generated by the server 134 of FIG. 1 for display on one or more of the devices 142 of FIG. 1; Cavanaugh - [0049]: The aircraft communication visualization map 300 can include one or more visual indicators associated with an average data transfer rate at the aircraft parking locations; Cavanaugh - [0050]: the processing system 136 can output to the aircraft communication visualization map 300, an average wireless signal strength for one or more of: an area of an airport, multiple areas of the airport used by a same airline, and a plurality of airports used by the same airline. In some embodiments, the processing system 136 can output to the aircraft communication visualization map 300, an average wireless transfer rate for a plurality of airports used by the same airline. Other types of outputs can be overlaid on the aircraft communication visualization map 300; Stefan - [0027]: storing (i) a plurality of poses of the mobile device, and (ii) a plurality of key performance indicators, KPIs, related to the quality of the communication channel. Respective poses from the plurality of poses are associated with at least one respective KPI related to the quality of the communication channel; Stefan - [0033]: The plurality of KPIs, in some embodiments, include at least one metric of the quality of the communication channel; Stefan - [0061]: the computing (operation 206 of Figure 2) includes building a map for the mobile device of a first plurality of poses that satisfy a KPI representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI; Stefan - claim 9: the failure is identified based on a metric related to signal strength of the link falling below a threshold value; Stefan - claim 16: building a map for the mobile device of a first plurality of poses that satisfy a key performance indicator, KPI, representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI; Park - [0298]: The position-dependent beam information here may include positional information and beam-direction information relating to the positional information, and the beam-direction information may include a beam direction in which the strongest signal strength is obtained for each spatial section that results from division by the positional information, and a value of signal strength in the beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information, as described in FIG. 14, may include an optimal beam direction (a beam angle) on a basis of coordinates representing each position, and signal strength (signal quality) in the corresponding beam direction. For example, the position-dependent beam information may be configured with a value of a position (coordinates representing a position), a beam index (a beam direction), and a value of signal strength (signal quality) in this order; Park - [0299]: In Step S1310, the vehicle 10 determines the direction of transmitted or received beam based on a drive path for the vehicle 10 and the received communication environment map. For example, the vehicle 10 may acquire an optimal beam direction for a position on a path along which the vehicle 10 is currently driving and signal strength for the corresponding beam direction, from the communication environment map, and may determine a beam that is to be used to transmit or receive a signal, using the optimal beam direction and the signal strength; Park - [0306]: The communication environment map, as illustrated in FIG. 14, includes an optimal beam direction for each position and signal strength in the corresponding beam direction. For example, with reference to FIG. 14, the communication environment map may include an optimal beam direction in which communication with a base station 1230 is possible depending on each position, and signal strength (strong, weak, or communication-unachieved) in the corresponding beam direction).
Regarding claim 15, the combination of Cavanaugh, Stefan and Park teaches the method according to claim 1, wherein outputting the rendering performance map based on the plurality of poses and the associated plurality of smoothness statuses comprises: displaying, by the server, the rendering performance map ([0040]: The aircraft communication visualization map 300 can be generated by the server 134 of FIG. 1 for display on one or more of the devices 142 of FIG. 1. For instance, when airline support personnel or a flight crew of the aircraft 108 of Fig. 1 determine that a wireless transfer of data should occur for the aircraft 108 at a particular airport, an application or web page on one of the devices 142 can display the aircraft communication visualization map 300 as generated by the server 134; [0050]: the processing system 136 can output to the aircraft communication visualization map 300, an average wireless signal strength for one or more of: an area of an airport, multiple areas of the airport used by a same airline, and a plurality of airports used by the same airline. In some embodiments, the processing system 136 can output to the aircraft communication visualization map 300, an average wireless transfer rate for a plurality of airports used by the same airline. Other types of outputs can be overlaid on the aircraft communication visualization map 300).
Claim 19 is similar in scope to claims 2 and 9, and therefore the examiner provides similar rationale to reject claim 19.
Claim(s) 5 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cavanaugh, in view of Stefan, in view of Park, and further in view of Itsumi et al. (US 2026/0065441, hereinafter Itsumi).
Regarding claim 5, the combination of Cavanaugh, Stefan and Park does not explicitly teach the method according to claim 3, wherein the first smoothness status further comprises a first render status of a rendering process performed on at least one of the first client device and the remote rendering device of the first client device.
Itsumi teaches the first smoothness status (communication quality) further comprises a first render status of a rendering process performed (encoding the input video at a bit rate) on at least one of the first client device (terminal 100) and the remote rendering device (central server 200) of the first client device ([0079]: the terminal 100 encodes the input video on the basis of the determined sharpening region (S114). The image quality control unit 140 encodes the input video by a predetermined video encoding system. For example, the image quality control unit 140 may encode the input video at a bit rate allocated from the compression bit rate control function 401 of the MEC 400, or may encode the input video at a bit rate corresponding to the communication quality between the terminal 100 and the center server 200. The image quality control unit 140 encodes the input video in a range of the allocated bit rate or the bit rate corresponding to the communication quality). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Itsumi’s knowledge of encoding the input video at a bit rate corresponding to the communication quality between the terminal 100 and the central server 200 as taught and modify the process of Cavanaugh, Stefan and Park because such a process improves the image quality of the sharpening region ([0079]).
Regarding claim 17, the combination of Cavanaugh, Stefan and Park teaches the server according to claim 16, wherein the plurality of poses comprise a first pose (aircraft parking location 302, fig. 3 and [0040]), the plurality of smoothness statuses comprise a first smoothness status (data transfer rate, [0040]) associated with the first pose (data transfer rate associated with aircraft parking location 302, fig. 3 and [0040] - Cavanaugh), and the first smoothness status is detected in a case where the first client device is with the first pose (detecting wireless signal strength/quality of communication at a gate of an airport is functionally analogous to detecting a smoothness status when the first client is with the first pose; Cavanaugh - [0042]: The signal strength displayed with the wireless interface usage distribution 316 can include an average wireless signal strength for one or more of: an area of an airport (e.g., one or more gates/parking locations); Stefan – [0051]: the information related to motion of the mobile device includes motion that resulted in the current pose of the mobile device, the coverage metric signal indicates a lack of coverage, the evaluating (operation 204 of Figure 2) includes deciding whether the lack of coverage occurred at about the time of the motion that resulted in the current pose of the mobile device; Stefan – [0027]: storing (i) a plurality of poses of the mobile device, and (ii) a plurality of key performance indicators, KPIs, related to the quality of the communication channel. Respective poses from the plurality of poses are associated with at least one respective KPI related to the quality of the communication channel; Stefan – [0033]: The plurality of KPIs, in some embodiments, include at least one metric of the quality of the communication channel; Stefan – [0061]: the computing (operation 206 of Figure 2) includes building a map for the mobile device of a first plurality of poses that satisfy a KPI representing the quality of the communication channel and a plurality of poses of that fail to satisfy the KPI);
wherein the first smoothness status comprises a first wireless communication quality of the first client device (devices 142 used within the aircraft 108 corresponds to a first client device; Cavanaugh – [0016]: outputting to the aircraft communication visualization map, an average wireless signal strength for one or more of: an area of an airport, multiple areas of the airport used by a same airline, and a plurality of airports used by the same airline; Cavanaugh - [0031]: The devices 142 can be any type of processing device capable of communicating through the network 135. For instances, the devices 142 can include personal computers, workstations, tablet computers, mobile phones, wearable computing devices, and the like. The devices 142 may connect at a remote location from the server 134 and the ground station 124. Further, the devices 142 may include an electronic flight bag device that can be used within the aircraft 108; Cavanaugh – [0046]: The status data can include aircraft information and aircraft communication history of one or more wireless interfaces used to transfer data from an aircraft 108. The aircraft information can include an identifier (e.g., aircraft registration number, aircraft serial number) of the aircraft 108 and a location of performing a transfer of data to/from the aircraft, such as GPS coordinates. The aircraft communication history can include a signal strength, an amount of data transferred, and a duration of transferring the data to/from the aircraft 108. The signal strength can include multiple communication types, such as a cellular signal strength and/or a Wi-Fi signal strength; Stefan – [0027]: a plurality of key performance indicators, KPIs, related to the quality of the communication channel; Park – [0306]: For example, with reference to FIG. 14, the communication environment map may include an optimal beam direction in which communication with a base station 1230 is possible depending on each position, and signal strength (strong, weak, or communication-unachieved) in the corresponding beam direction) communicating with a remote rendering device of the first client device (Cavanaugh – server 134, fig. 1 and [0031]).
The combination of Cavanaugh, Stefan and Park does not explicitly teach wherein the first smoothness status further comprises a first render status of a rendering process performed on at least one of the first client device and the remote rendering device of the first client device.
Itsumi teaches the first smoothness status (communication quality) further comprises a first render status of a rendering process performed (encoding the input video at a bit rate) on at least one of the first client device (terminal 100) and the remote rendering device (central server 200) of the first client device ([0079]: the terminal 100 encodes the input video on the basis of the determined sharpening region (S114). The image quality control unit 140 encodes the input video by a predetermined video encoding system. For example, the image quality control unit 140 may encode the input video at a bit rate allocated from the compression bit rate control function 401 of the MEC 400, or may encode the input video at a bit rate corresponding to the communication quality between the terminal 100 and the center server 200. The image quality control unit 140 encodes the input video in a range of the allocated bit rate or the bit rate corresponding to the communication quality). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Itsumi’s knowledge of encoding the input video at a bit rate corresponding to the communication quality between the terminal 100 and the central server 200 as taught and modify the system of Cavanaugh, Stefan and Park because such a system improves the image quality of the sharpening region ([0079]).
Allowable Subject Matter
Claims 6, 8 and 18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 6, none of the cited prior art references of record, teach either individually or in combination, the limitation “the first render status of the rendering process comprises at least one of a rendering frame rate of the remote rendering device, a rendering time of the remote rendering device, an encoding time of the remote rendering device, an encoding frame rate of the remote rendering device, a decoding rate of the first client device, a decoding time of the first client device, and a client rendering rate of the first client device”.
Regarding claims 8 and 18, none of the cited prior art references of record, teach either individually or in combination, the limitation “the plurality of poses and the associated plurality of smoothness statuses are detected by the first client device in a case where the first client device is displaying a virtual environment of a reality service application in the reference filed, and a corresponding relationship between the virtual environment and the reference field is fixed”.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JWALANT B AMIN whose telephone number is (571)272-2455. The examiner can normally be reached Monday-Friday 10am - 630pm CST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Said Broome can be reached at 571-272-2931. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JWALANT AMIN/Primary Examiner, Art Unit 2612