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 .
The following is a Final Office action in response to communications received 02/09/2026.
Response to Amendment
Claims 1, 9, 11, and 19 have been amended.
Claims 1-19 and 21 have been examined.
The rejection of claims 9 and 19 under 35 U.S.C 112 is withdrawn in light of the applicant’s amendments to the claims.
Applicant's arguments filed on 02/09/2026 have been fully considered but they are not persuasive. As per the applicant’s arguments that prior art of record Swanburg does not teach the limitations: “on-device data identifying app-specific usage duration for an installed app associated with the first service”, the examiner respectfully disagrees. Applicant states on page 7 of the Remarks that “Indeed, the clearest usage determination described in Swanburg is not duration-based at all. Swanburg describes identifying particular services/applications as "inactive" because they "have not been accessed during this billing period" (and are therefore candidates for de- provisioning or similar actions). This teaching supports only an access/non-access characterization of usage during a billing interval, i.e., whether the application/service was accessed at least once during the period, and not a computation of how long the application/service was used.” The examiner respectfully disagrees with this assessment of Swanburg since identifying that an application or service has not been accessed during a billing period indicates that the usage duration of the application during that billing period is zero. Swanburg: Column 6, lines 34-41: Similarly, a subscriber may be regularly billed for a service that he has not used in months. The service controller recognizes this pattern, and may offer the subscriber to "de-provision" the service, i.e., the service controller determines that the usage duration of the service is zero and offers to de-provision the service. column 8, lines 41-52: Service Controller 312 has collected information from the Content and Communications Managers and has a record of currently used services 343. Note that two services 345 have registered inactive for the prescribed interval. In this case the applications "Car Search" and "American Idol" have not been accessed during this billing period but remain on the "active" list of applications for which the subscriber is being billed, i.e., service controller determines that the usage duration of "Car Search" and "American Idol" applications is zero for the prescribed interval based on the obtained device usage data.
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.
Claims 1, 2, 7, 8, 10-12, 17, and 18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by prior art of record US 8019683 to Swanburg et al (hereinafter Swanburg).
As per claims 1 and 11, Swanburg teaches:
A computing system, comprising:
a processor; a memory coupled to the processor, the memory storing computer-executable instructions that, when executed by the processor (column 2, lines 22-24: The present invention discloses systems and methods for intelligently providing and charging for services on a network. Implementing the system using a device comprising a memory and processor was well known to one of ordinary skill in the art before the effective filing date of the claimed invention), configure the processor to:
obtain, via a computing device, device usage data associated with a first service that is accessible on the computing device comprising on-device data identifying app-specific usage duration for an installed app associated with the first service (Swanburg: column 3, lines 36-46: The service controller is also in communication with an Intelligent Information Collection Repository (IICR). Additionally, a micro-level IICR (M-IICR) on the subscriber's device may collect usage data locally and submit this data to the arbitrator and the IICR. column 5, line 67-column 6, line 5: IICR 130 holds all historical data from service controller 120 and correlates it in real-time with other information such as market demographics and network service/applications analytics. IICR 130 stores the combined data in a subscriber profile. Column 6, lines 34-41: Similarly, a subscriber may be regularly billed for a service that he has not used in months. The service controller recognizes this pattern, and may offer the subscriber to "de-provision" the service, i.e., the service controller determines that the usage duration of the service is zero and offers to de-provision the service. Also, Column 8, lines 31-53: Service Controller 312 has collected information from the Content and Communications Managers and has a record of currently used services 343. Note that two services 345 have registered inactive for the prescribed interval. In this case the applications "Car Search" and "American Idol" have not been accessed during this billing period but remain on the "active" list of applications for which the subscriber is being billed, i.e., the usage duration of the applications "Car Search" and "American Idol" is determined to be zero for the billing period);
query at least one network node of a first network to obtain network resource usage data associated with the computing device (Swanburg: Column 10, lines 7-30: In another exemplary embodiment, the present invention can be used to control unauthorized use of resources on the network. For instance, if 20 out of 10,000 data users are unlawfully tethering their devices and using a large chunk of bandwidth (network resources), the automatic provisioning/billing system described herein can simply prompt the user with an offer to purchase a broadband card/LAN card or a tethering plan for a subsidized rate, i.e., bandwidth usage of device is obtained. Column 5, lines 9-16: Data can come from a subscriber's interaction with the network. Column 9, lines 44-65: SLAs contain records relating to customer's expectations of service level and quality of service (QoS). Additionally, records of QoS and service levels as delivered, along with network conditions and other information, is also stored either within IICR or generated by MIICR on the subscriber's device and feedback from an application server. When a service or application is accessed by devices 101-103, a data link may be established between the device and an application server. As described herein, this data link is susceptible to variances in quality and scope. QoS (such as bandwidth - network resources) is monitored by the application server, and patterns of QoS are stored in the related SLA. The record of the actual quality and scope of the service is recorded in the SLA database);
generate recommendation data comprising a plurality of data records corresponding to usage instances for the first service based on the device usage data and the network resource usage data (Swanburg: column 2, lines 33-37: Services are dynamically provisioned and de-provisioned in real-time based on the subscriber's usage of the services, along with demographics and network conditions. Column 6, lines 34-41: Similarly, a subscriber may be regularly billed for a service that he has not used in months. The service controller recognizes this pattern, and may offer the subscriber to "de-provision" the service. Column 8, line 41-53: subscriber 301 is offered a recommendation based on his historical profile of Average Revenue Per Month (ARPU) and services he is using or has used in the past. A "recommendations" page 349 is sent to subscriber 301. Column 9 lines 1-10: subscriber 301 is offered a recommendation based on his historical profile of Average Revenue Per Month (ARPU) and services he is using or has used in the past. A "recommendations" page 349 is sent to subscriber 301. Column 10, lines 7-30: In another exemplary embodiment, the present invention can be used to control unauthorized use of resources on the network. For instance, many subscribers with data plans are able to connect or "tether" their mobile devices to their computers, and use the data plan to access the Internet from the computer. However, tethering consumes large amounts of bandwidth on the network. Thus, subscribers who wish to tether their devices are typically required to provision and pay for a tethering plan (service). For instance, if 20 out of 10,000 data users are unlawfully tethering their devices (usage of a service) and using a large chunk of bandwidth (network resources), the automatic provisioning/billing system described herein can simply prompt the user with an offer (recommendation) to purchase a broadband card/LAN card or a tethering plan for a subsidized rate); and
cause to be modified at least one device setting of the computing device based on the generated recommendation data (Swanburg: column 9, lines 3-14: The recommendation is to discard the "Car Search" and "American Idol" applications and add "NFL" in their place. The subscriber has the option to act on the recommendation. It was well known to one of ordinary skill in the art before the effective filing date of the claimed invention that discarding existing applications and/or adding new applications in a device will change the device settings).
As per claims 2 and 12, Swanburg teaches:
The computing system of claim 1, wherein the device usage data associated with the first service is obtained based on tracking at least one of: sensor data of sensors associated with the computing device, the sensor data corresponding to defined device actions associated with the first service; or device interaction events associated with the first service comprising input for interacting with the computing device (Swanburg: column 5, lines 7-15: Data can come from a subscriber's interaction with the network, with applications on a subscriber's mobile device).
As per claims 7 and 17, Swanburg teaches:
The computing system of claim 1, wherein the instructions, when executed, further configure the processor to obtain output of custom software for collecting at least one of connection usage time or browser application usage time (Swanburg: column 3, lines 36-46: Additionally, a micro-level IICR (M-IICR) (custom software) on the subscriber's device may collect usage data locally and submit this data to the arbitrator and the IICR).
As per claim 8, Swanburg teaches:
The computing system of claim 1, wherein causing the at least one device setting to be modified comprises enabling a restriction on usage of a first application (Swanburg: column 2, lines 31-42: Services are dynamically provisioned and de-provisioned in real-time based on the subscriber's usage of the services, along with demographics and network conditions. Column 6, lines 34-38: Similarly, a subscriber may be regularly billed for a service that he has not used in months. The service controller recognizes this pattern, and may offer the subscriber to "de-provision" the service, i.e., deprovisioning the service will make the service unavailable to the subscriber which is a restriction on the usage of the service).
As per claims 10, Swanburg teaches:
The computing system of claim 1, wherein the at least one network node comprises a computer server associated with a connection service provider (CSP) (Swanburg: column 5, lines 9-16: Data can come from a subscriber's interaction with the network. Column 9, lines 53-65: When a service or application is accessed by devices 101-103, a data link may be established between the device and an application server. As described herein, this data link is susc88eptible to variances in quality and scope. QoS is monitored by the application server, and patterns of QoS are stored in the related SLA. The record of the actual quality and scope of the service is recorded in the SLA database.).
As per claim 18, Swanburg teaches:
The method of claim 11, further comprising causing a message containing the generated recommendation data to be presented via the computing device (Swanburg: Column 6, lines 34-38: Similarly, a subscriber may be regularly billed for a service that he has not used in months. The service controller recognizes this pattern, and may offer the subscriber to "de-provision" the service. Column 8, line 64-column 9, line 8: Subscriber 301 is being billed for applications he does not use and is about to see a substantial increase in his upcoming bill based on the addition of another application. However, because of the Intelligent Charging system, subscriber 301 is offered a recommendation based on his historical profile of Average Revenue Per Month (ARPU) and services he is using or has used in the past. A "recommendations" page 349 is sent to subscriber 301, outlining a potential billing plan that will maintain his ARPU and optimize his usage. The recommendation is to discard the "Car Search" and "American Idol" applications and add "NFL" in their place).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 3, 6, 13, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Swanburg and prior art of record US 9075883 to Verkasalo (hereinafter Verkasalo).
As per claims 3 and 13, Swanburg teaches:
The computing system of claim 2, wherein the memory stores a first application associated with the first service (Swanburg: column 5, lines 7-15: Data can come from a subscriber's interaction with the network, with applications on a subscriber's mobile device. It was well known to one of ordinary skill in the art that applications on a mobile device will be stored in the memory of the mobile device).
Swanburg does not teach: wherein obtaining the device usage data comprises tracking sensor data of the sensors during periods of usage of the first application. However, Verkasalo teaches:
wherein obtaining the device usage data comprises tracking sensor data of the sensors during periods of usage of the first application (Verkasalo: column 11, lines 38-67: Different embodiments of the present invention are thus partially enabled by the wireless devices 102, 104, and 106, which preferably automatically collect, via software and optionally hardware (e.g. sensors) sensing functionalities, a considerable amount of behavioural, technical and/or contextual data, i.e. observation data, and further automatically transmit at least part of the gathered data to one or more servers 112 at optimal time instants. The wireless devices 102, 104, 106, such as smartphones or communications-enabled PDAs (personal digital assistant), capable of providing data to the server arrangement 112 may especially comprise an observation logic for conducting observations relative to the wireless device. Column 12, lines 9-24: The observation logic may collect data points based on communication actions (for instance, initiating a call, answering a call, sending a message such as an SMS (Short Message Service), MMS (Multimedia Message Service), or e-mail message, receiving a corresponding message, etc.), sensor data (e.g. temperature, acceleration, position (orientation and/or location via e.g. GPS (Global Positioning System)/cell identification/triangulation), light intensity), application usage, etc.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to employ the teachings of Verkasalo in the invention of Swanburg to include the above limitations. The motivation to do so would be to provide an intelligent, flexible, effective and adaptive centralized alternative for monitoring and analyzing the usage and context of wireless devices (Verkasalo: column 2, lines 20-23).
As per claims 6 and 16, Swanburg in view of Verkasalo teaches:
The computing system of claim 3, wherein obtaining the device usage data comprises querying the computing device for device screen time associated with periods of usage of the first application (Verkasalo: column 11, lines 38-67: The wireless devices 102, 104, 106, such as smartphones or communications-enabled PDAs (personal digital assistant), capable of providing data to the server arrangement 112 may especially comprise an observation logic for conducting observations relative to the wireless device. Column 17, line 66-column 18, line 8: The data processing engine may be configured to compare, for example, execution initiation times of applications and/or to calculate the run times of applications. For most other applications, for example calendar and document viewing applications, the nature of the application states that it is natural to measure duration from user interface level activation logs (screen time logs)).
The examiner provides the same rationale to combine prior arts Swanburg and Verkasalo as in claims 3 and 13 above.
Claims 4, 5, 14, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Swanburg and prior art of record US 20200153855 to Kirti et al (hereinafter Kirti).
As per claims 4 and 14, Swanburg does not teach the limitations of claim 4. However, Kirti teaches:
wherein generating the recommendation data comprises identifying duplicated data among the plurality of data records for merging into a single data record (Kirti: [0168] In some embodiments, data about network activity may be collected from multiple data sources. Log files may be obtained by to security monitoring and control system 102 to ingest and process to identify information about network activity, such as application usage. Log files may be obtained using techniques disclosed in FIG. 8. [0169]: The data may be processed for deduplication to identify unique instances of network activity to identify information about network activity, such as application usage, i.e., duplicate data is identified from the received information. [0170] At step 1104, the information obtained about the network activity is used to determine one or more applications that have been accessed).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to employ the teachings of Kirti in the invention of Swanburg to include the above limitations. The motivation to do so would be to discover and manage applications in a computing environment of an organization (Kirti: [0007]).
As per claims 5 and 15, Swanburg in view of Kirti teaches:
The computing system of claim 4, wherein the duplicated data is identified based on comparing values in data fields comprising at least one of usage period, subscription name, or usage duration associated with the data records (Kirti: [0131] Security monitoring and control system 102 may perform processing to discover application usage and a measure of security for applications and users of those applications. At 822, logs may be obtained through a staging process. At 824, logs may be processed for parsing to identify unique network activity. [0132] At 826, the logs may be used to determine unique information identifying each application. Event details about application usage may be determined based on the logs. Event details may include a timestamp, a third-party appname (link->app details), an IP address, a geolocation, user information (e.g., a username or email ID), and/or an address of a source device requesting the application (e.g., a MAC address). [0169]: The data may be processed for deduplication to identify unique instances of network activity to identify information about network activity, such as application usage. It was well known to one of ordinary skill in the art that identifying duplicate data involves comparing information in the received logs such as timestamp, appname, etc.).
The examiner provides the same rationale to combine prior arts Swanburg and Kirti as in claims 4 and 14 above.
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Swanburg and prior art of record US 20250098960 to Neitzell et al (hereinafter Neitzell).
As per claims 9 and 19, Swanburg does not teach the limitations of claim 9. However, Neitzell teaches:
wherein the instructions, when executed, further configure the processor to obtain tracking data of a health tracking service for a user of computing device, wherein the recommendation data includes recommended subscriptions usage information based on the tracking data and usage patterns associated with the first service (Neitzell: [0029]: Computing devices 12 may be configured for wireless communication with IMD 10. Computing devices 12 may retrieve or receive event data and other sensed physiological data from IMD 10 that was collected and stored by the IMD. In some examples, computing devices 12 take the form of personal computing devices of patient 4. In some examples, only one of computing devices 12, e.g., computing device 12A, is configured for communication with IMD 10, e.g., due to execution of software (e.g., part of a health monitoring application as described herein) enabling communication and interaction with IMD 10. In some examples, computing device(s) 12 may be configured to receive an indication of an acute health event of patient 4 from IMD 10. [0107] Patient risk analyzer 242 may determine a patient risk based on physiological parameters sensed by IMD 10 and/or other devices within system 2 (both of FIG. 1) that include sensors. [0108] Patient risk analyzer 244 may generate an indication 246 of a recommended subscription service level to patient 4. Interface layer 200 may transmit indication 246 to system 2. For example, interface layer 200 may transmit indication 246 to computing device 12A, such as through a short message service (SMS) message, an email, a voicemail, or another indication. Computing device 12A may in turn display or play the indication to inform patient 4 of the recommended subscription service level. This may be performed based on a change in health status of patient 4, based on an acute health event of patient 4, upon a request of patient 4 for a recommended subscription service level, or periodically).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to employ the teachings of Neitzell in the invention of Swanburg to include the above limitations. The motivation to do so would be to determine the patient risk (Neitzell: [0107]).
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Swanburg and prior art of record US 20240135327 to Yembari et al (hereinafter Yembari).
As per claims 21, Swanburg does not teach the limitations of claim 21. However, Yembari teaches:
wherein the recommendation data is generated by a recommendation engine that is implemented as an artificial intelligence (AI)- powered assistant (Yembari: [0006] Subsequently, one or more insights for each application may be derived based on the employee data and application data. The insights may be derived using machine learning algorithms. The insights may comprise a category assigned to each application, access rights and application usage pattern. The machine learning algorithms are trained to identify a category of an application that is unlabelled, application usage pattern for an employee based on application data, access rights of an application for an employee based on the application data and the employee data. [0044] Further to deriving insights for the one or more applications in the list of applications used by the employee, the system may determine a set of actions for the one or more applications. The action may be removal of the application).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to employ the teachings of Yembari in the invention of Swanburg to include the above limitations. The claim would have been obvious because a particular known technique was recognized as part of the ordinary capabilities of one skilled in the art (see KSR Int’l Co. v. Teleflex Inc. 550 U.S. ___, 82 USPQ2d 1385 (Supreme Court 2007) (KSR)).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 20150261754 to Bai et al: A method and system for recommending applications to users of in-vehicle infotainment systems are disclosed. Application rating data from many road vehicle infotainment system users are collected on a central server, including both explicit ratings and implicit ratings. Implicit ratings may be calculated based on application usage data. The user/application rating data is filtered for relevance, and then analyzed to determine inferred ratings for user/application relationships where no rating exists. The inferred ratings are calculated using both a user-driven consensus rating calculation and an application-driven consensus rating calculation. The inferred ratings, along with optional cyberspace-based external inputs, are used to synthesize application recommendations for users. The synthesized recommendations for application consideration are provided to the appropriate user via downloading from the central server to the infotainment system in the user's vehicle.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MADHURI R HERZOG whose telephone number is (571)270-3359. The examiner can normally be reached 8:30AM-4:30PM.
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, Taghi Arani can be reached at (571)272-3787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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MADHURI R. HERZOG
Primary Examiner
Art Unit 2438
/MADHURI R HERZOG/Primary Examiner, Art Unit 2438
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