DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of claims
Claim 2 is cancelled.
Claims 1,3,7-10,14-16 are amended.
Claims 1, 3-20 are pending.
Applicant’s amendments are entered. Applicant’s remarks are also entered into
the record. A new search was made necessitated by the applicant’s amendments
and remarks. Amendment claims overcome 35 U.S.C. 101 rejection.
Response to arguments
Applicant’s remarks and arguments are respectfully considered but not
persuasive. Applicant’s stands on page 9 that” Bhorkar et al. fails to disclose an application function at a core network conducting….(UE) device”. Bhorkar et al. teaches regarding “application function at a core network” that “It should be understood that the cellular network 902 may additionally include backbone infrastructure that operates on wired communications technologies, including, but not limited to, optical fiber, coaxial cable, twisted pair cable, and the like to transfer data between various systems operating on or in communication with the cellular network 902.” (See para[0096]), backbone infrastructure is same as application function of a core network), which conducting a network health check (see para[0006], para[0045])) and assigning an optimized route (see one or more optimized routes 158, abstract a route optimization system can obtain a quality of service (“QoS”) requirement) and separately, one or more radio access network (see para[0042] The network 116 can include one or more radio access networks (“RANs”).) executing NQ assurance (See abstract an optimized route from the origin location to the destination location that satisfies the quality of service requirement ) and determining network performance associated with an assigned optimized route after it has been acknowledge at a user equipment (UE) device (see abstract The optimized route can be sent to a vehicle-to-everything (“V2X”)-enabled device for use in navigating from the origin location to the destination location while receiving a QoS that satisfies the QoS requirement.).
Therefore, Examiner maintains the 35.U.S.C 102 rejection and repeat the rejection as before with additional citation for the convenience.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 3-20 are rejected under 35 U.S.C. 102 (a)(2) as being anticipated by US 20220136846 A1 to Bhorkar et al. (herein after “Bhorkar”).
Regarding claim 1, Bhorkar discloses A method, comprising: receiving, at an application function(see Bhorkar backbone infrastructure para[0096]) of a core network from a user equipment (UE) device communicatively coupled to an automated vehicle(See Bhorkar para [0006] In some embodiments, the route optimization system can obtain international mobile subscriber identity (“IMSI”)-related information or equivalent user equipment/device-related information.) , a navigation destination for the automated vehicle (see Bhorkar para[0033] Such a design anticipates that the driver will provide destination or navigation input, para[0040] The vehicle system(s) 108 can include one or more systems associated with any aspect of the vehicle 104. For example, the vehicle systems 108 can include the engine, fuel system, ignition system, electrical system, exhaust system, drivetrain system, suspension system, steering system, braking system, parking assistance system (e.g., parking sensors), navigation system,) ; conducting, at the application function of the core network, a network health check (See Bhorkar para [0045] These metrics can be used as part of traffic data collection. The V2I services 134 also can provide data to the V2X-enabled device 102 to inform the vehicle occupant(s) of safety information, accident information, mobility information, weather information, other environment-related condition information, and/or other information.) and route validation process to determine an optimized route (See Bhorkar Abstract The route optimization system can determine, based upon the route optimization model and the key performance indicator, an optimized route from the origin location to the destination location that satisfies the quality of service requirement. ) from a current location of the automated vehicle to the received navigation destination based on communication network traffic data(see Bhorkar para[0045] For example, the V2I services 134 can capture, from the V2X-enabled device 102, data such as the speed and other metrics associated with the vehicle 104. These metrics can be used as part of traffic data collection. );
assigning, at the application function of the core network, an optimized route with network quality (NQ) assurance (see Bhorkar Abstract a route optimization system can obtain a quality of service (“QoS”) requirement,); and
transmitting, to the at least one UE device (See Bhorkar user devices) via one or more radio access networks, an instruction message containing the assigned optimized (See Bhorkar user device) receiving, at the one or more radio access networks from the at least one UE device, an acknowledgement of the assigned optimized route (See Bhorkar para [0030] The concepts and technologies disclosed herein will allow network service providers to deliver their content to autonomous vehicles and to provide optimal routes for users of emergency wireless networks);
executing, at the radio access network apparatus (See Bhorkar para[0042] The network 116 can include one or more radio access networks (“RANs”). ) , NQ assurance (See Bhorkar abstract The optimized route can be sent to a vehicle-to-everything (“V2X”)-enabled device for use in navigating from the origin location to the destination location while receiving a QoS that satisfies the QoS requirement.) and determining network performance associated with the assigned optimized route(see Bhorkar abstract The optimized route can be sent to a vehicle-to-everything (“V2X”)-enabled device for use in navigating from the origin location to the destination location while receiving a QoS that satisfies the QoS requirement).
; and upon completion of the NQ assurance and network performance determination, transmitting, over the one or more radio access networks to the at least one UE device (See Bhorkar para[0042] Radio access network can utilize the various channel access), a confirmation of the NQ assurance for instructing (See Bhorkar para[0004] an optimized route from the origin location to the destination location that satisfies the quality of service requirement), at the UE device, the automated vehicle to execute the assigned optimized route (See Bhorkar para[0119] the vehicle V2C application 124, the vehicle QoS-based map application 144, the user device V2I application 126, the user device V2C application 128, the user device QoS-based map application 146),).
Regarding claim 3, Bhorkar discloses wherein the network health check and route validation process comprises: obtaining, using an rApp function(see Bhorkar map applications 144/146) at one or more intelligent platforms(See Bhorkar para[0050] The historical database can be used in different future applications and developing machine learning and artificial intelligence models where training data is used.), current network traffic data from at least one of the one or more radio access networks associated with one or more potential routes from the current location of the automated vehicle to the received navigation destination; and processing the obtained current network traffic data (See Bhorkar para[0045] For example, the V2I services 134 can capture, from the V2X-enabled device 102, data such as the speed and other metrics associated with the vehicle 104. These metrics can be used as part of traffic data collection. , see Bhorkar para[0045] For example, the V2I services 134 can capture, from the V2X-enabled device 102, data such as the speed and other metrics associated with the vehicle 104. These metrics can be used as part of traffic data collection. )
Regarding claim 4, Bhorkar discloses wherein the processing is executed using one or more machine learning models trained on historical network congestion data previously obtained from the one or more radio access networks. (See Bhorkar para[0050] the route optimization system 154 can construct a historical database (not shown) to store this information. The historical database can be used in different future applications and developing machine learning and artificial intelligence models where training data is used.)
Regarding claim 5, Bhorkar discloses wherein the historical network congestion data is obtained using the rApp function to at least periodically stream traffic data from the one or more radio access networks and to store the streamed traffic data in one or more databases. (see Bhorkar para[0050] the route optimization system 154 can construct a historical database (not shown) to store this information); para[0047] For example, the user device V2C application 128 may be a video streaming application used by the user device 106 to access a video streaming service embodied as one of the V2C services 130, and as such, the video streaming application may request a specific minimum download speed to ensure that a specific video quality can be achieved as the vehicle 104 travels from the origin location 150 to the destination location 152.)
Regarding claim 6, Bhorkar discloses wherein the one or more machine learning models are trained using an unsupervised training process for identifying one or more patterns of network traffic congestion at the one or more radio access networks (See Bhorkar para [0113] The number of training passes indicates the number of training passes that the machine learning algorithm 1104 makes over the training data set 1106 during the training process).
Regarding claim 7, Bhorkar discloses wherein the current network traffic data is processed to predict network congestion at the one or more at least one radio access networks associated with the one or more potential routes (See Bhorkar para[0008] The route optimization system can predict, based upon a route optimization model, a QoS at each of the locations; para[0073] At operation 510, the route optimization system 154 predicts the QoS at each sample location. This predication can be based upon historical QoS at each sample location).
Regarding claim 8, Bhorkar discloses wherein the optimized route is assigned (see Bhorkar abstract an optimized route from the origin location to the destination location that satisfies the quality of service requirement. ) according to the one or more at least one radio access networks associated (see Bhorkar para[0042] The network 116 can include one or more radio access networks (“RANs”) )with the one or more potential routes meeting one or more network requirements (See Bhorkar one or more QoS requirements 148) as determined by the processing, and said one or more network requirements are associated with the NQ assurance (See Bhorkar para [0069]From operation 408, the method 400 proceeds to operation 410. At operation 410, the route optimization system 154 determines the optimized route(s) 158 from the origin location 150 to the destination location 152 that satisfy the QoS requirement(s) 148).
Regarding claim 9, Bhorkar discloses A system, comprising:
one or more radio access networks (see para[0042]) communicatively coupled to a core network, said one or more radio access networks (See para[0042] one or more core networks such as a circuit-switched core network)
an interface adapted to communicate with one or more a plurality of user equipment (UE) devices(See Bhorkar para[0087] one or more user interface devices 806); a processor(see Bhorkar para[0059] Computer-readable instructions can be implemented on various system configurations including single-processor or multiprocessor systems, minicomputers, mainframe computers, personal computers, hand-held computing devices, microprocessor-based,); a plurality of processing devices communicatively coupled to the core network and the one or more radio access networks; (See para[0134] the phrase “computer storage medium,” “computer-readable storage medium,” and variations thereof does not include waves or signals per se and/or communication media, and therefore should be construed as being directed to “non-transitory” media only., para[0103] The compute resources 1008 can include one or more central processing units (“CPUs”) configured with one or more processing cores. )
and one or more non-transitory computer-readable memory (See Bhorkar para[0134] para[0087] The computer system 800 includes a processing unit 802, a memory 804, one or more user interface devices 806,) operatively connected to the processor plurality of processing devices and having stored thereon machine-readable instructions that cause, when executed, the processor plurality of processing devices to: receive, at an application function of the core network (See Bhorkar para[0096]) from a user equipment (UE) (See Bhorkar user device) device at least one of the plurality of UE devices (See Bhorkar one or more user interface devices 806 ) that is communicatively coupled to an automated vehicle(see Bhorkar para[0037]The user device 106 can be configured to communicate with the vehicle 104 via a wired connection), a navigation destination for the automated vehicle(See Bhorkar abstract an optimized route from the origin location to the destination location that satisfies the quality of service requirement. ); conduct at the application function of the core network (See para[0096]), a network health check and route validation process to determine an optimized route from a current location of the automated vehicle to the received navigation destination based on communication network traffic data(see Bhorkar para[0045] For example, the V2I services 134 can capture, from the V2X-enabled device 102, data such as the speed and other metrics associated with the vehicle 104. These metrics can be used as part of traffic data collection. ); assign at the application function of the core network (See para[0096]), an optimized route with network quality (NQ) assurance to the automated vehicle; and transmit, to the UE device, an instruction message containing the assigned optimized route(See Bhorkar para[0119] the vehicle V2C application 124, the vehicle QoS-based map application 144, the user device V2I application 126, the user device V2C application 128, the user device QoS-based map application 146),).
transmit, to the at least one UE device (See Bhorkar user device) via the one or more radio access networks, an instruction message containing the assigned optimized route (See Bhorkar user device);
receive, at the one or more radio access networks from the at least one UE device, an acknowledgement of the assigned optimized route (See Bhorkar para [0030] The concepts and technologies disclosed herein will allow network service providers to deliver their content to autonomous vehicles and to provide optimal routes for users of emergency wireless networks);
execute (See Bhorkar para[0042] The network 116 can include one or more radio access networks (“RANs”), at the one or more radio access networks, NQ assurance (See Bhorkar abstract The optimized route can be sent to a vehicle-to-everything (“V2X”)-enabled device for use in navigating from the origin location to the destination location while receiving a QoS that satisfies the QoS requirement.) and determine network performance associated with the assigned optimized route (see Bhorkar abstract The optimized route can be sent to a vehicle-to-everything (“V2X”)-enabled device for use in navigating from the origin location to the destination location while receiving a QoS that satisfies the QoS requirement).
; and
upon completion of the NQ assurance and network performance determination, transmit, over the one or more radio access networks to the at least one UE device (See Bhorkar para[0042] Radio access network can utilize the various channel access), a confirmation of the NQ assurance for instructing (See Bhorkar para[0004] an optimized route from the origin location to the destination location that satisfies the quality of service requirement), the automated vehicle to execute the assigned optimized route See Bhorkar para[0119] the vehicle V2C application 124, the vehicle QoS-based map application 144, the user device V2I application 126, the user device V2C application 128, the user device QoS-based map application 146).
Regarding claim 10, Bhorkar discloses wherein the network health check and route validation process comprises machine-readable instructions that cause, when executed, the processor one or more processing devices to further: obtain, using an rApp function (see Bhorkar map applications 144/146) at one or more intelligent platforms, (See Bhorkar para[0050] The historical database can be used in different future applications and developing machine learning and artificial intelligence models where training data is used.), current network traffic data from at least one of the one or more radio access networks associated with one or more potential routes from the current location of the automated vehicle to the received navigation destination; and process the obtained current network traffic data (See Bhorkar para[0045] For example, the V2I services 134 can capture, from the V2X-enabled device 102, data such as the speed and other metrics associated with the vehicle 104. These metrics can be used as part of traffic data collection. , see Bhorkar para[0045] For example, the V2I services 134 can capture, from the V2X-enabled device 102, data such as the speed and other metrics associated with the vehicle 104. These metrics can be used as part of traffic data collection. ).
Regarding claim 11, Bhorkar discloses wherein the obtained current network traffic data is processed using one or more machine learning models trained on historical network congestion data previously obtained from the one or more radio access networks (See Bhorkar para [0113] The number of training passes indicates the number of training passes that the machine learning algorithm 1104 makes over the training data set 1106 during the training process).
Regarding claim 12, Bhorkar discloses wherein the historical network congestion data is obtained using the rApp function to at least periodically stream traffic data from the one or more radio access networks and to store the streamed traffic data in one or more databases. (see Bhorkar para[0050] the route optimization system 154 can construct a historical database (not shown) to store this information); para[0047] For example, the user device V2C application 128 may be a video streaming application used by the user device 106 to access a video streaming service embodied as one of the V2C services 130, and as such, the video streaming application may request a specific minimum download speed to ensure that a specific video quality can be achieved as the vehicle 104 travels from the origin location 150 to the destination location 152.)
Regarding claim 13, Bhorkar discloses wherein the one or more machine learning models are trained using an unsupervised training process for identifying one or more patterns of network traffic congestion at the one or more radio access networks. (See Bhorkar para [0113] The number of training passes indicates the number of training passes that the machine learning algorithm 1104 makes over the training data set 1106 during the training process).
Regarding claim 14, Bhorkar discloses wherein the current network traffic data is processed at the processor one or more processing devices to predict network congestion at the one or more processing devices one or more radio access networks associated with the one or more potential routes (See Bhorkar para[0008] The route optimization system can predict, based upon a route optimization model, a QoS at each of the locations; para[0073] At operation 510, the route optimization system 154 predicts the QoS at each sample location. This predication can be based upon historical QoS at each sample location).
Regarding claim 15, Bhorkar discloses wherein the optimized route is assigned (see Bhorkar abstract an optimized route from the origin location to the destination location that satisfies the quality of service requirement. ) according to the one or more at least one radio access networks associated (see Bhorkar para[0042] The network 116 can include one or more radio access networks (“RANs”) with the one or more potential routes meeting one or more network requirements(See Bhorkar one or more QoS requirements 148) as determined by the processing, and said one or more network requirements are associated with the NQ assurance (See Bhorkar para [0069]From operation 408, the method 400 proceeds to operation 410. At operation 410, the route optimization system 154 determines the optimized route(s) 158 from the origin location 150 to the destination location 152 that satisfy the QoS requirement(s) 148).
Regarding claim 16, Bhorkar discloses A method, comprising: transmitting, from a user equipment (UE) device (See Bhorkar user device) to one or more radio access network(See Bhorkar para[0042]), a request for a route to a navigation destination(see Para[0081] One or more of the optimized routes 158 with optimized costs between the origin and destination locations can be computed using different algorithms such as Dijkstra algorithm. Each of the optimized routes 158 can satisfy a single QoS requirement 148 such as the QoS requested by the user.), said UE device being communicatively coupled to an automated vehicle(See Bhorkar para [0006] In some embodiments, the route optimization system can obtain international mobile subscriber identity (“IMSI”)-related information or equivalent user equipment/device-related information.); receiving, at the UE device from a core network via the one or more the radio access network, an assigned optimized route with network quality (NQ) assurance from the radio access network(see Bhorkar abstract The optimized route can be sent to a vehicle-to-everything (“V2X”)-enabled device for use in navigating from the origin location to the destination location while receiving a QoS that satisfies the QoS requirement);
transmitting, at the UE device (See Bhorkar user device) to the one or more radio access network apparatuses, an acknowledgement of the assigned optimized route to initiate an execution of NQ assurance (See Bhorkar para [0030] The concepts and technologies disclosed herein will allow network service providers to deliver their content to autonomous vehicles and to provide optimal routes for users of emergency wireless networks);
and instructing, at the UE device, the automated vehicle to navigate according to the assigned optimized route (See Bhorkar para[0119] the vehicle V2C application 124, the vehicle QoS-based map application 144, the user device V2I application 126, the user device V2C application 128, the user device QoS-based map application 146),para[0103] The compute resources 1008 can include one or more graphics processing unit (“GPU”) configured to accelerate operations performed by one or more CPUs, and/or to perform computations to process data, and/or to execute computer-executable instructions of one or more application programs, operating systems, and/or other software that may or may not include instructions particular to graphics computations.)
upon receiving a confirmation from the radio access network that a NQ assurance has been completed (see Bhorkar Abstract a route optimization system can obtain a quality of service (“QoS”) requirement,).
Regarding claim 17, Bhorkar discloses further comprising: after the receiving, acknowledging, at the UE device to the radio access network apparatus, the assigned optimized route(see Bhorkar abstract an optimized route from the origin location to the destination location that satisfies the quality of service requirement. ); and performing the instructing upon receiving a NQ assurance and network performance determination from the radio access network apparatus(See Bhorkar para[0119] the vehicle V2C application 124, the vehicle QoS-based map application 144, the user device V2I application 126, the user device V2C application 128, the user device QoS-based map application 146),para[0103] The compute resources 1008 can include one or more graphics processing unit (“GPU”) configured to accelerate operations performed by one or more CPUs, and/or to perform computations to process data, and/or to execute computer-executable instructions of one or more application programs, operating systems, and/or other software that may or may not include instructions particular to graphics computations.).
Regarding claim 18, Bhorkar discloses wherein the optimized route is assigned (see Bhorkar abstract an optimized route from the origin location to the destination location that satisfies the quality of service requirement. ) according to a network health check and route validation process that comprises processing current network traffic data(See Bhorkar para[0045] For example, the V2I services 134 can capture, from the V2X-enabled device 102, data such as the speed and other metrics associated with the vehicle 104. These metrics can be used as part of traffic data collection. , see Bhorkar para[0045] For example, the V2I services 134 can capture, from the V2X-enabled device 102, data such as the speed and other metrics associated with the vehicle 104. These metrics can be used as part of traffic data collection).
obtained from one or more radio access networks associated (see Bhorkar para[0042] The network 116 can include one or more radio access networks (“RANs”)with one or more potential routes from a current location of the automated vehicle to the navigation destination(See Bhorkar one or more QoS requirements 148).
Regarding claim 19, Bhorkar discloses wherein the current network traffic data is processed to predict network congestion at the one or more radio access networks associated with the one or more potential routes (See Bhorkar para[0008] The route optimization system can predict, based upon a route optimization model, a QoS at each of the locations; para[0073] At operation 510, the route optimization system 154 predicts the QoS at each sample location. This predication can be based upon historical QoS at each sample location).
Regarding claim 20, Bhorkar discloses wherein the optimized route is assigned (see Bhorkar abstract an optimized route from the origin location to the destination location that satisfies the quality of service requirement. ) according to the one or more radio access networks associated with the one or more potential routes meeting See Bhorkar one or more QoS requirements 148) one or more network requirements as determined by the processing(see Bhorkar para[0042] The network 116 can include one or more radio access networks (“RANs”) , and said one or more network requirements are associated with the NQ assurance(See Bhorkar para [0069]From operation 408, the method 400 proceeds to operation 410. At operation 410, the route optimization system 154 determines the optimized route(s) 158 from the origin location 150 to the destination location 152 that satisfy the QoS requirement(s) 148).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/NAZIA AFRIN/ Examiner, Art Unit 3666
/SCOTT A BROWNE/ Supervisory Patent Examiner, Art Unit 3666