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 . 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.
DETAILED ACTION
The following NON-FINAL Office Action is in response to Request for Continued Examination filed on 12/24/2025.
Status of Claims
Claims 1-20 are currently pending.
Claims 1, 11, 16 are currently amended.
Claims 1-20 are currently under examination and have been rejected as follows.
Continued Examination under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/24/2025 has been entered.
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Response to Amendment
The previously pending rejections under 35 USC 101 will be maintained. The 101 rejection is updated in view of the amendments.
The previously pending rejections under 35 USC 102 are withdrawn in view of the amendments.
New grounds for rejection under 35 USC 103 are applied as necessitated by the amendments.
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Response to Arguments
Regarding Applicant’s remarks pertaining to 35 USC 101:
Step 2A Prong 1:
Applicant argues beginning on page 8 of remarks 12/24/2025:
“Applicant respectfully submits that the instant claims, as amended, recite patent-eligible subject matter under 35 U.S.C. § 101 and should not be rejected as directed to an abstract idea.
“…These claim elements describe specific technological operations performed by a device, not abstract concepts divorced from technological implementation.
“The claims further recite "determining, by the device, based on execution of an artificial intelligence (AI) model with the pattern information as input, executable instructions for modifying the execution of the application." This claim language specifies that the AI model receives pattern information as input and produces executable instructions as output, where those instructions are specifically for modifying application execution…. This claim language recites automatic execution of the determined instructions without user input, resulting in specific modifications to both display and functionality during application execution.”
Examiner respectfully disagrees. Although Applicant demonstrates that the claim limitations as amended describe specific technological operations performed by a device, the device is considered an additional element in the 101 analysis of the functions performed amounting to an abstract idea. Monitoring, identifying, analyzing, and influencing user behavior (e.g. Applicant specification ¶ [0003]-[0006], [0031]-[0032]), albeit achieved with technological solutions, still fall within managing personal behavior under the larger abstract grouping of Certain Methods of Organizing Human Activity (MPEP 2106.04(a)(2) II). Accordingly, the claims recite an abstract idea.
Step 2A Prong 2:
Applicant argues on page 9 of remarks 12/24/2025:
“The ordered combination of claim elements as recited provides a practical application of
any purported abstract concept. The claims recite that the identification comprises receiving a detection signal corresponding to execution, that the retrieval is based on the determined application information, that the AI model execution uses the pattern information as input to determine executable instructions, and that the control is based on the determination and occurs
without user input. This ordered sequence ties the claim elements together in a specific technological process where detection signals trigger analysis, analysis drives pattern retrieval, pattern information feeds AI model execution, and AI-generated instructions automatically modify
application execution. The claim language "without user input" and "automatically executing the executable instructions" specifies that the control occurs autonomously based on the technological operations performed by the device, not through human intervention or mental processes.”
Examiner respectfully disagrees. The absence of human intervention or mental process do not preclude a set of claims from subject matter ineligibility. The functions of the additional elements recited include examples such as identifying requests corresponding to applications, detecting signals corresponding to execution of applications, analyzing data related to applications and requests, determining application information, retrieving pattern information related to applications, determining executable instructions for modifying execution of applications, controlling applications, modifying display of application content, modifying management of application features, and modifying functionality of applications. The additional elements are recited at a high level of generality (i.e. as a generic computer performing functions of collecting data, identifying patterns, presenting data, controlling functionality and user access to applications, etc.) such that they amount to no more than mere instructions to apply the exception using generic computer components. Therefore, these functions can be viewed as not meaningfully different than a business method or mathematical algorithm being applied on a general-purpose computer as tested per MPEP 2106.05(f)(2)(i) or requiring the use of software to tailor information and provide it to the user on a generic computer as tested per MPEP 2106.05(f)(2)(v).
Furthermore, the additional element “artificial intelligence (AI) model” language merely requires execution of an algorithm that can be performed by a generic computer component and provides no detail regarding the operation of that algorithm. As such, the claim requirement amounts to mere instructions to implement the abstract idea on a computer, and, therefore, is not sufficient to make the claim patent eligible. See Alice, 573 U.S. at 226 (determining that the claim limitations “data processing system,” “communications controller,” and “data storage unit” were generic computer components that amounted to mere instructions to implement the abstract idea on a computer); October 2019 Guidance Update at 11–12 (recitation of generic computer limitations for implementing the abstract idea “would not be sufficient to demonstrate integration of a judicial exception into a practical application”). Such a generic recitation of “artificial intelligence (AI) model” is insufficient to show a practical application of the recited abstract idea.
Step 2B:
Applicant argues beginning on page 10 of remarks 12/24/2025:
“The claims do not preempt all uses of artificial intelligence or pattern matching but rather claim a specific process where a device receives detection signals, analyzes application data, retrieves patterns, executes an AI model with those patterns, and automatically controls application execution to modify display, feature management, and functionality without user input.
The claim language recites specific structural and functional relationships between the claim elements: the identification comprises receiving a detection signal; the determination is based on the analysis; the retrieval is based on the determined application information; the AI model execution is based on execution with the pattern information as input; and the control is based on the determination and comprises automatically executing the executable instructions. These explicit dependencies and relationships establish that the claims recite an integrated technological process, not a collection of generic computer components performing conventional
functions. The claim language "by the device" appears throughout the claims, tying each operation to device-performed actions rather than abstract mental steps or mathematical calculations divorced from technological implementation.”
Examiner respectfully disagrees. The absence of mental steps or mathematical calculations do not preclude a set of claims from subject matter ineligibility. Examiner acknowledges that the claims recite a technological process. Eligibility analysis requires demonstration of a specific technological solution to a technological problem (as opposed to a business or entrepreneurial problem) and that the technological solution is specific enough to separate it from a generic computer-based solution merely invoking computers to perform existing processes. The additional elements recited in the independent claims are narrowed to capabilities such as identifying, detecting, analyzing, retrieving, determining, executing, modifying, and managing various forms of data such as requests, signals, instructions, patterns, application content, etc. which, when evaluated per MPEP 2106.05(f)(2) represent mere invocation of computers to perform existing processes. For example, these capabilities are recited at a high level of generality such as “analyze data related to the application and request”, “retrieve, from a datastore, pattern information related to the application”, “determine, based on execution of an artificial intelligence (AI) model with the pattern information as input, executable instructions for modifying the execution of the application”, “the execution of the application comprises”, and “a modified display of application content and modified management of application features”. Examiner submits that insufficient technological detail is provided, for example, as to how data is anlayzed, how and what specific pattern information is received, how or what executable instructions are determined, how the technology modifies application content and features, etc., which would separate them from generic computer-based solutions merely invoking computers to perform existing processes.
Accordingly, the previously pending rejections under 35 USC 101 will be maintained. The 101 rejection is updated in view of the amendments.
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Regarding Applicant’s remarks pertaining to 35 USC 102/103:
Applicant argues on page 11 of remarks 12/24/2025:
“…Bott does not teach or suggest receiving a detection signal corresponding to execution of an application…. Bott teaches retrieving contextual information from sensors and data sources (¶ 0032-0033), but does not teach or suggest receiving a detection signal that corresponds to execution of an application…. Bott' s contextual information gathering is not a detection signal corresponding to execution of an application, as Bott' s system collects environmental and temporal data rather than signals indicating that an application is executing or has been launched.”
Examiner respectfully disagrees. Further support for the disclosure for the claim as amended can be found at Bott ¶ [0081] and ¶ [0114]: “…The request/transaction manager 235 can further include an application behavior detector 236 and/or a prioritization engine 241, the application behavior detector 236 may further include a pattern detector 237 and/or and application profile generator 239”.
Applicant argues on page 11 of remarks 12/24/2025:
“…Bott does not teach or suggest analyzing data related to both the application and the request to determine application information. Bott teaches analyzing contextual information to determine which application settings to apply (¶ 0034-0037), but this is fundamentally different from analyzing data related to the application and the request to determine application information…. Bott's system applies predefined rules to contextual information to select settings, but does not determine application information through analysis of application-related and request-related data as recited in the claims.
Examiner respectfully disagrees. Under the broadest reasonable interpretation of the limitation from claims 1, 11, 16 “determining, based on the analysis, application information”, Bott discloses both analysis of application and request data, as well as determination of the data at Bott ¶ [0161-0162] and ¶ [0168]. Examiner submits that Bott’s analysis function goes beyond content caching, delivery, and setting selection and is in fact used for application analysis (Bott ¶ [0161-0162]), control, modification, and display (Bott ¶ [0369]).
Applicant argues on page 11 of remarks 12/24/2025:
“…Bott does not teach or suggest retrieving pattern information from a datastore based on determined application information. Bott teaches storing and retrieving application settings and
profiles (¶ 0038-0040), but does not teach or suggest pattern information or that retrieval is based
on determined application information…. Bott does not disclose pattern information as recites in the claims; Bott discloses settings and profiles, which are not pattern information related to the application.”
Examiner respectfully disagrees. Under the broadest reasonable interpretation of the limitation from claims 1, 11, 16 “retrieving, by the device, from a datastore, pattern information related to the application, the retrieval being based on the determined application information”, Bott discloses both the retrieval of the application pattern information and that it is based on the determination at Bott ¶ [0168]: “Periodicity can be detected, by the decision engine 246 or the request analyzer 246c, when the request and the other requests generated by the same client occur at a fixed rate or nearly fixed rate, or at a dynamic rate with some identifiable or partially or wholly reproducible changing pattern. If the requests are made with some identifiable pattern (e.g., regular intervals, intervals having a detectable pattern, or trend (e.g., increasing, decreasing, constant, etc.) the timing predictor 246a can determine that the requests made by a given application on a device is predictable and identify it to be potentially appropriate for caching, at least from a timing standpoint.”
Applicant argues on page 12 of remarks 12/24/2025:
“…Bott does not teach or suggest executing an AI model with pattern information as input to determine executable instructions…. Bott does not produce executable instructions for modifying execution; rather, Bott applies settings that change application configuration, which is distinct from determining executable instructions that modify execution.”
Examiner considers Applicant’s argument but finds it moot on new grounds. Examiner presents reference Breaux, III et al. US 20230156569 A1, hereinafter Breaux which, in combination with primary reference Bott, cures the deficiency of the claim limitation as amended: “determine, based on execution of an artificial intelligence (AI) model with the pattern information as input, executable instructions for modifying the execution of the application (Breaux ¶ [0067], [0381] combined with Bott ¶ [0369]). Bott teaches modified execution and control of applications through rule and policy implementation, and Breaux presents the AI/ML component used to enforce an application policy based on analysis of user behavior data.
Applicant argues on page 12 of remarks 12/24/2025:
“…Bott does not teach or suggest automatically executing executable instructions determined by an AI model to achieve modified display of application content and modified management of application features…. The claim language "automatically executing the executable instructions" requires execution of instructions, not merely application of configuration settings.”
Examiner respectfully disagrees. Under the broadest reasonable interpretation of “automatically executing the executable instructions” meaning to implement the function without manual user input or intervention, both Bott and Breaux disclose examples of the above claim limitation as amended. See Bott ¶ [0369]: “The parental control manager 434 can also implement rules and policies [EN: modified management] regarding access characteristics based on timing, frequency, time of day, or total usage”, Breaux ¶ [0067]: “The modeling data 616 may also be used to determine an activity or usage that may result from a current action performed on the mobile device 102 and enforce a policy prior to that determined activity or usage occurring”, and Breaux ¶ [0381]: “In other embodiments, AI (artificial intelligence), machine learning, decision trees, or hard coded logic may be used to adjust the behavior and response based on the user's prior history.”
Applicant argues on page 13 of remarks 12/24/2025:
“Bott teaches changing settings such as ringtone volume, notification preferences, and connectivity options (¶ 0049-0052), but does not teach or suggest that the execution of the application comprises modified display of application content and modified management of application features as recited in the claims.”
Examiner respectfully disagrees. Examiner submits that Bott’s “Parental control of mobile content on a mobile device” (as titled) systems and methods clearly exceed merely changing ringtones, notification preferences, or connectivity options in response to monitoring and analysis of traffic content on a mobile device. Bott discloses a method of monitoring application activities, enforcing policy, controlling usage time and volume, and configuring access limits to offensive sites and inappropriate content, implying by Examiner’s interpretation, control and modification of display of content on the application (see Bott Figs. 25, 26 and related text).
Applicant argues on page 13 of remarks 12/24/2025:
“…Bott does not teach or suggest modifying functionality of an application upon its execution based on executable instructions determined by an AI model. Bott' s system changes settings based on context, but does not modify application functionality upon execution as recited
in the claims.”
Examiner respectfully disagrees. Under the broadest reasonable interpretation of “automatically executing the executable instructions” meaning to implement the function without manual user input or intervention, both Bott and Breaux disclose examples of the above claim limitation as amended. See Bott ¶ [0369]: “The parental control manager 434 can also implement rules and policies [EN: modified functionality] regarding access characteristics based on timing, frequency, time of day, or total usage”, Breaux ¶ [0067]: “The modeling data 616 may also be used to determine an activity or usage [EN: functionality] that may result from a current action performed on the mobile device 102 and enforce a policy [EN: modify] prior to that determined activity or usage occurring”, and Breaux ¶ [0381]: “In other embodiments, AI (artificial intelligence), machine learning, decision trees, or hard coded logic may be used to adjust the behavior and response based on the user's prior history.”
Applicant argues on page 13 of remarks 12/24/2025:
“…Bott does not teach or suggest this ordered sequence where [1] detection signals trigger analysis, [2] analysis produces application information that drives pattern retrieval, [3] pattern information feeds AI model execution, and [4] AI-generated executable instructions are automatically executed to modify application execution.”
Examiner respectfully disagrees. Each of the sequenced claim limitations [1]-[4] above are addressed in the preceding Examiner responses and disclosure is further detailed and cited in the 103 rejection section below.
Accordingly, the rejections of the claims as amended under 35 USC 102 are withdrawn and rejections on new grounds are applied under 35 USC 103 as necessitated by the amendments.
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Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-10 are directed to a method or process which is a statutory category.
Claims 11-15 are directed to a device or machine which is a statutory category.
Claims 16-20 are directed to a non-transitory computer-readable storage medium or article of manufacture which is a statutory category.
Step 2A Prong One: The claims recite, describe, or set forth a judicial exception of an abstract idea (see MPEP 2106.04(a)). Specifically, the claims recite, describe or set forth managing personal behavior, including: “identifying… a request corresponding to an application, the identification comprising receiving a detection signal”, “determining… application information”, “retrieving… pattern information”, “analyzing data related to the application and the request, and determining, based on the analysis, application information”, “retrieving… pattern information related to the application, the retrieval being based on the determined application information”, “modifying the execution of the application”, and “controlling, based on the determination and without user input, the application, the control comprising… modified display of application content and management of application features” (claims 1, 11, 16); “compiling an application notification, the application notification comprising interactive content corresponding to a predicted pattern of activity as indicated by the pattern information”, and “causing display of the application notification” (claims 2, 12, 17); “the display occurs at a time… prior to opening… and upon opening the application” (claims 3, 12, 17); “the application notification comprises information indicating and providing the control” (claims 4, 12, 17); “analyzing activity of a user… for a time period”, and “determining a set of activity patters” (claims 5, 13, 18); “enable access to the application without the control… based on a predicted application usage being below a threshold amount of time” (claims 6, 14, 19); “control… corresponds to… modified access…, modified access time…, denial of access to the application” (claims 7, 15, 20); “the request corresponds to at least one of opening of the application and rendering a page of the application within a foreground of a display of the device” (claim 10). Monitoring, identifying, analyzing, and influencing user behavior fall within managing personal behavior under the larger abstract grouping of Certain Methods of Organizing Human Activity (MPEP 2106.04(a)(2) II). Accordingly, the claims recite an abstract idea.
Step 2A Prong Two: Independent claims 1, 11, 16 recite the following additional elements: “device”, “application”, “datastore”, “processor”, “artificial intelligence (AI) model”, and “non-transitory computer-readable storage medium encoded with computer-executable instructions”. The functions of these additional elements include examples such as identifying requests corresponding to applications, detecting signals corresponding to execution of applications, analyzing data related to applications and requests, determining application information, retrieving pattern information related to applications, determining executable instructions for modifying execution of applications, controlling applications, modifying display of application content, modifying management of application features, and modifying functionality of applications. The additional elements are recited at a high level of generality (i.e. as a generic computer performing functions of collecting data, identifying patterns, presenting data, controlling functionality and user access to applications, etc.) such that they amount to no more than mere instructions to apply the exception using generic computer components. Therefore, these functions can be viewed as not meaningfully different than a business method or mathematical algorithm being applied on a general-purpose computer as tested per MPEP 2106.05(f)(2)(i) or requiring the use of software to tailor information and provide it to the user on a generic computer as tested per MPEP 2106.05(f)(2)(v). The claims are directed to an abstract idea and the judicial exception does not integrate the abstract idea into a practical application.
Furthermore, the additional element “artificial intelligence (AI) model” language merely requires execution of an algorithm that can be performed by a generic computer component and provides no detail regarding the operation of that algorithm. As such, the claim requirement amounts to mere instructions to implement the abstract idea on a computer, and, therefore, is not sufficient to make the claim patent eligible. See Alice, 573 U.S. at 226 (determining that the claim limitations “data processing system,” “communications controller,” and “data storage unit” were generic computer components that amounted to mere instructions to implement the abstract idea on a computer); October 2019 Guidance Update at 11–12 (recitation of generic computer limitations for implementing the abstract idea “would not be sufficient to demonstrate integration of a judicial exception into a practical application”). Such a generic recitation of “artificial intelligence (AI) model” is insufficient to show a practical application of the recited abstract idea.
Step 2B: According to MPEP 2106.05(f)(1), considering whether the claim recites only the idea of a solution or outcome i.e., the claims fail to recite the technological details of how the actual technological solution to the actual technological problem is accomplished. The recitation of claim limitations that attempt to cover an entrepreneurial and thus abstract solution to an entrepreneurial problem with no technological details on how the technological result is accomplished and no description of the mechanism for accomplishing the result do not provide significantly more than the judicial exception.
The dependent claims do not appear to provide any additional computer-based elements, let alone for such additional computer-based elements to integrate the abstract idea into practical application (Step 2A prong two) or providing significantly more (Step 2B).
Further, dependent claims 2-10, 12-15, 17-20 merely incorporate the additional elements recited in claims 1, 10 along with further narrowing of the abstract idea of claims 1, 20 along with their execution of the abstract idea. Specifically, dependent claims narrow the device, application, datastore, processor, AI model, and non-transitory computer-readable storage medium encoded with computer-executable instructions to capabilities such as analyzing, compiling, displaying, comprising, determining, storing, enabling access to, modifying access to, and rendering various forms of data such as pattern information, notifications, application information, times, time periods, activity patterns, application usage, identifiers, dates, users, pages, etc. which, when evaluated per MPEP 2106.05(f)(2) represent mere invocation of computers to perform existing processes. Therefore, the additional elements recited in the claimed invention individually and in combination fail to integrate a judicial exception into a practical application (Step 2A prong two) and for the same reasons they also fail to provide significantly more (Step 2B). Thus, claims 1-20 are reasoned to be patent ineligible.
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REJECTIONS BASED ON PRIOR ART
Examiner Note: Some rejections will contain bracketed comments preceded by an “EN” that will denote an examiner note. This will be placed to further explain a rejection.
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Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, 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, 5-11, 13-16, 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over:
Bott US 20130031601 A1 hereinafter Bott, in view of.
Breaux, III et al. US 20230156569 A1 hereinafter Breaux. As per,
Regarding Claims 1, 11, 16: Bott teaches
“A method comprising: (claim 1)
“A device comprising: a processor configured to: (claim 11)
“A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by a device, perform a method comprising: (claim 16) (Bott ¶ [0086])
“identifying (claims 1, 16) / identify (claim 11), by a device (claims 1, 16), a request corresponding to an application, the identification comprising receiving a detection signal corresponding to execution of the application” (Bott ¶ [0164]: In one embodiment, the decision engine 246, for example, via the request analyzer 246c, collects information about an application or client request generated at the mobile device 250. [Also see Fig. 10 and related text]. Mid-¶ [0081]: If the screen light is 'on, further detection can be made to determine whether it is a background application or for other indicators that local cache entries can or cannot be used to satisfy the request. When identified, the requests for which local entries can be used may be processed identically to the screen light off situation. End-¶ [0114]: The request/transaction manager 235 can further include an application behavior detector 236 and/or a prioritization engine 241, the application behavior detector 236 may further include a pattern detector 237 and/or and application profile generator 239);
“analyzing (claims 1, 16) / analyze (claim 11), by the device (claims 1, 16), data related to the application and the request, and determining, based on the analysis, application information” (Bott mid-¶ [0161]: …In one embodiment, the application behavior detector 236 includes a pattern detector 237 [EN: analysis], a poll interval detector 238 [EN: analysis], an application profile generator 239 [EN: analysis], and/or a priority engine 241. The poll interval detector 238 may further include a long poll detector 238a having a response/request tracking engine 238b…. ¶ [0162]: The pattern detector 237, application profile generator 239, and the priority engine 241 were also described in association with the description of the pattern detector shown in the example of FIG. 2A. One embodiment further includes an application profile repository 242 which can be used by the local proxy 275 to store information or metadata regarding application profiles (e.g., behavior, patterns, type of HTTP requests, etc.));
“retrieving (claims 1, 16) / retrieve (claim 11), by the device (claims 1, 16) / from a datastore (claim 11), from a datastore, pattern information related to the application, the retrieval being based on the determined application information” (Bott ¶ [0168]: Periodicity can be detected, by the decision engine 246 or the request analyzer 246c, when the request and the other requests generated by the same client occur at a fixed rate or nearly fixed rate, or at a dynamic rate with some identifiable or partially or wholly reproducible changing pattern [EN: analysis]. If the requests are made with some identifiable pattern (e.g., regular intervals, intervals having a detectable pattern, or trend (e.g., increasing, decreasing, constant, etc.) the timing predictor 246a can determine that the requests made by a given application on a device is predictable and identify [EN: determine] it to be potentially appropriate for caching [EN: retrieved], at least from a timing standpoint);
determining, by the device [..] executable instructions for modifying the execution of the application (Bott ¶ [0369]: The parental control manager 434 can also implement rules and policies [EN: modified management] regarding access characteristics based on timing, frequency, time of day, or total usage. For example, the parental control manager 434 can control access of certain sites or use of certain applications [EN: execution] on the device to certain number of hours in a day, or only on certain days of the week, or use of a certain number of minutes for voice calls, certain number of MMS or SMS. The parental control manager 434 can control or limit the calling of certain numbers, accessing [EN: display] of certain URLs, texting of certain numbers, use of certain applications, and/or the delivery [EN: display] of content or any incoming correspondences from these flagged sources as identified by for example, phone numbers, URLs, IP addresses, etc.); “and
“controlling (claims 1, 16) / control (claim 11), by the device (claims 1, 16), based on the determination and without user input, the application, the control comprising automatically executing the executable instructions, such that, the execution of the application comprises a modified display of application content and modified management of application features, the control further comprising modified functionality of the application upon the execution of the application” (Bott ¶ [0369]: The parental control manager 434 can also implement rules and policies [EN: modified management] regarding access characteristics based on timing, frequency, time of day, or total usage. For example, the parental control manager 434 can control access of certain sites or use of certain applications [EN: display] on the device to certain number of hours in a day, or only on certain days of the week, or use of a certain number of minutes for voice calls, certain number of MMS or SMS. The parental control manager 434 can control or limit the calling of certain numbers, accessing [EN: display] of certain URLs, texting of certain numbers, use of certain applications, and/or the delivery [EN: display] of content or any incoming correspondences from these flagged sources as identified by for example, phone numbers, URLs, IP addresses, etc.).
Although Bott teaches analyzing pattern information of the usage of an application and controlling the application thus, Bott does not specifically teach the incorporation of artificial intelligence in analyzing user behavior to control the application.
However, Breaux in analogous art of mobile device control based on usage data teaches or suggests:
determining, by the device, based on execution of an artificial intelligence (AI) model with
the pattern information as input, executable instructions for modifying the execution of the application (Breaux ¶ [0067]: The context modeling service 118 may use the contextual data 614 as input to generate modeling data 616. The modeling data 616 may include one or more machine learning models, classifiers, training sets, and the like generated from the contextual data 614. The management service 116 may send the modeling data 616 to the control application 114, control devices 108, and the networked beacons 110. Doing so allows these devices to use the modeling data 616 to more efficiently identify a usage context. For example, as a mobile device 102 may input currently observed data to a generated model and receive, as output, a usage context. The modeling data 616 may also be used to determine an activity or usage that may result from a current action performed on the mobile device 102 and enforce a policy prior to that determined activity or usage occurring. ¶ [0381]: In other embodiments, AI (artificial intelligence), machine learning, decision trees, or hard coded logic may be used to adjust the behavior and response based on the user's prior history. For example, the user can begin in one mode, such as pure audit (where one or more functions are available to be used) or pure blocking (where nothing can be used) and adjust the blocking policy to be more or less restrictive based on the user reaching certain driving score thresholds, or other incentive based systems).
Breaux and Bott are found as analogous art of mobile device control based on usage data. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified Bott’s parental mobile device control system and method to have included Breaux’s teachings around the incorporation of artificial intelligence in analyzing user behavior to control mobile applications. The benefit of these additional features would have enabled more accurate assessment of user behavior and usage patterns while controlling mobile devices (Breaux ¶ [0004]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by Bott in view of Breaux (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of mobile device control based on usage data. In such combination each element would have merely performed same organizational and managerial function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by Bott in view of Breaux above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding Claims 5, 13, 18: Bott teaches all the limitations of claim 1 above.
Bott further teaches “analyzing (claims 5, 18) / analyze (claim 13) activity of a user related to the application for a time period” (Bott ¶ [0122]: In one embodiment, the user activity module 215 interacts with the context API 206 to identify, determine, infer, detect, compute, predict, and/or anticipate, characteristics of user activity on the device 250….For instance, user activity profile can be generated in real-time for a given instant to provide a view of what the user is doing or not doing at a given time (e.g., defined by a time window, in the last minute, in the last 30 seconds, etc.), a user activity profile can also be generated for a session defined by an application or web page that describes the characteristics of user behavior with respect to a specific task they are engaged in on the device 250, or for a specific time period (e.g., for the last 2 hours, for the last 5 hours));
“determining (claims 5, 18) / determine (claim 13) a set of activity patterns” (Bott ¶ [0122]: …Various inputs collected by the context API 206 can be aggregated by the user activity module 215 to generate a profile for characteristics of user activity. Such a profile can be generated by the user activity module 215 with various temporal characteristics. ¶ [0123]: Additionally, characteristic profiles can be generated by the user activity module 215 to depict a historical trend for user activity and behavior (e.g., 1 week, 1 mo., 2 mo., etc.). Such historical profiles can also be used to deduce trends of user behavior, for example, access frequency at different times of day, trends for certain days of the week (weekends or weekdays), user activity trends based on location data (e.g., IP address, GPS, or cell tower coordinate data) or changes in location data (e.g., user activity based on user location, or user activity based on whether the user is on the go, or traveling outside a home region, etc.) to obtain user activity characteristics); “and
“storing (claims 5, 18) / store (claim 13) the set of activity patterns in the datastore, wherein the pattern information is retrieved from the set of activity patterns” (See Bott Fig. 2A where User Activity Module 215 within Local Proxy 375 is connected to Cache 285 [datastore]. Bott ¶ [0114]: Device 250 can further include client-side components of the distributed proxy and cache system which can include, a local proxy 275 (e.g., a mobile client of a mobile device) and a cache 285).
Regarding Claims 6, 14, 19: Bott teaches all the limitations of claim 1 above.
Bott further teaches “determining (claims 6, 19) / determine (claim 14), upon analysis of the pattern information, to enable access to the application without the control, the enabled access determination based on a predicted application usage being below a threshold amount of time” (Bott ¶ [0519]: FIG. 26 depicts a diagram showing examples of the types of usage controls that can be performed at a mobile device. ¶ [0520]: One type of control includes usage limits 2600 which pertain to, for example, number of minutes [EN: threshold] used by a device or across devices (on a family plan or for a given subscription) 2606, number of SMS/MMS messages 2604, international call limits or data roaming restrictions 2608). Another type of control limit pertains to access limits to offensive sites or inappropriate site or application content 2650, including but not limited to, gambling sites/application/content 2652, pornographic sites/apps/content 2654, violent sites/content/apps 2656, and/or other age-inappropriate sites/content/apps 2658. The selector inappropriate sites/destination can be identified by flagged sources indicated by, one or more of, a phone number, a URI/URL or an IP address, etc. [Also see ¶ [0244-0249] and Fig. 25 and related text]).
Regarding Claims 7, 15, 20: Bott teaches all the limitations of claim 1 above.
Bott further teaches “wherein the control of the application corresponds to at least one of modified access to application features, modified access time to the application and denial of access to the application” (Bott ¶ [0369]: The parental control manager 434 can also implement rules and policies regarding access characteristics based on timing, frequency, time of day, or total usage. For example, the parental control manager 434 can control access of certain sites or use of certain applications on the device to certain number of hours in a day, or only on certain days of the week, or use of a certain number of minutes for voice calls, certain number of MMS or SMS. The parental control manager 434 can control or limit the calling of certain numbers, accessing of certain URLs, texting of certain numbers, use of certain applications, and/or the delivery of content or any incoming correspondences from these flagged sources as identified by for example, phone numbers, URLs, IP addresses, etc.).
Regarding Claim 8: Bott teaches all the limitations of claim 1 above.
Bott further teaches “wherein the determined application information comprises at least one of a type of application, identifier (ID) of the application, ID of a user and ID of the device” (Bott ¶ [0129]: One embodiment of the local proxy 275 further includes a request/transaction manager 235, which can detect, identify, intercept, process, manage, data requests initiated on the device 250, for example, by applications 210 and/or 220, and/or directly/indirectly by a user request. The request/transaction manager 235 can determine how and when to process a given request or transaction, or a set of requests/transactions, based on transaction characteristics).
Regarding Claim 9: Bott teaches all the limitations of claim 1 above.
Bott further teaches “wherein the data related to the application comprises indictors of at least one of an application type, application identifier (ID) and application status” (Bott ¶ [0190]: The network configuration that is selected can be determined based on information gathered by the application behavior module 236 regarding application activity state [EN: status] (e.g., background or foreground traffic), application traffic category (e.g., interactive or maintenance traffic), any priorities of the data/content, time sensitivity/criticality.), “and
“wherein the data related to the request comprises at least one of a time, date and ID of a user” (Bott ¶ [0260]: In one embodiment, the application behavior detector 236 includes a pattern detector 237, a poll interval detector 238, an application profile generator 239, and/or a priority engine 241. The pattern detector 237 can further include a cache defeat parameter detector 223 having also, for example, a random parameter detector 233 and/or a time/date parameter detector 234).
Claim 10: Bott teaches all of the limitations of claim 1 above.
Bott further teaches “wherein the request corresponds to at least one of opening of the application and rendering a page of the application within a foreground of a display of the device” (Bott ¶ [0124]: In one embodiment, user activity module 215 can detect and track user activity with respect to applications, documents, files, windows, icons, and folders on the device 250. For example, the user activity module 215 can detect when an application or window (e.g., a web browser or any other type of application) has been exited, closed, minimized, maximized, opened, moved into the foreground, or into the background, multimedia content playback, etc.).
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Claims 2-4, 12, 17 are rejected under 35 U.S.C. 103 as being unpatentable over:
Bott / Breaux as applied above, in further view of
Momtahan US 9203629 B2 hereinafter Momtahan. As per,
Regarding Claim 2: Bott / Breaux teaches all the limitations of claim 1 above.
Bott further teaches:
“analyzing the pattern information” (Bott ¶ [0153]: In one embodiment, the pattern detector 237 can detect recurrences in application requests made by the multiple applications, for example, by tracking patterns in application behavior. A tracked pattern can include, detecting that certain applications, as a background process, poll an application server regularly, at certain times of day, on certain days of the week, periodically in a predictable fashion, with a certain frequency, with a certain frequency in response to a certain type of event, in response to a certain type user query, frequency that requested content is the same, frequency with which a same request is made, interval between requests, applications making a request, or any combination of the above, for example.)
Although Bott teaches analyzing pattern information of the usage of an application and controlling the application thus, Bott falls short of providing an interactive notification to the user about the data.
However, Momtahan in analogous art of mobile device control based on usage data teaches or suggests:
“compiling an application notification, the application notification comprising interactive content corresponding to a predicted pattern of activity as indicated by the pattern information” (Momtahan col. 7 line 50: Usage policy server 160 uses the per-application usage data from prior sessions to inform the subscriber about which applications running on user equipment 102 have consumed the most bandwidth or databased on previous behavior patterns. Col. 6 line 28: Upon reaching a notification threshold (i.e., 400MBs in the example embodiment depicted in FIG. 7), a subscriber will receive a notification on user equipment 102. At that point, the subscriber can optionally set a new, higher usage limit in mobile usage policy application 104, or choose to curtail data usage. Col. 11 line 63: In an embodiment, upon the authorization of a session, a usage breach probability is calculated by a breach probability calculation module (not shown) within quota manager 144. The usage breach probability represents the probability that the subscriber will breach his or her usage quota during the session); “and
“causing display of the application notification (Momtahan col. 4 line 64: FIGS. 7-11 depict a graphical user interface (GUI) for a mobile device to display data usage, edit usage limits, define tariffs, and accept offers to change service tiers, according to embodiments of the invention).
Momtahan, Breaux and Bott are found as analogous art of mobile device control based on usage data. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified Bott / Breaux’s parental mobile device control system and method to have included Momtahan’s teachings around providing interactive notifications regarding usage information. The benefit of these additional features would have provided subscribers additional insight into real-time data usage to make spending decisions (Momtahan col. 3 lines 13-26). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by Bott in view of Breaux and Momtahan (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of mobile device control based on usage data. In such combination each element would have merely performed same organizational and managerial function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by Bott in view of Breaux and Momtahan above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding Claim 3: Bott / Breaux / Momtahan teaches all the limitations of claim 2 above.
Bott does not teach a user notification about usage information, as noted above in claim 2, and thus also falls short of specifying a time at which the notification is to be displayed.
However, Momtahan in analogous art of mobile device control based on usage data teaches or suggests: “wherein the display of the application notification occurs at a time related to one of a time prior to opening of the application and upon opening the application” (Momtahan col. 11 line 63: In an embodiment, upon the authorization of a session, a usage breach probability is calculated by a breach probability calculation module (not shown) within quota manager 144. The usage breach probability represents the probability that the Subscriber will breach his or her usage quota during the session. The usage breach probability can be based on any information and network usage statistics available at the time the session begins. Abstract: The method receives a notification at the subscriber's mobile device when a pre-determined quota is exceeded during the Subscriber session to control data usage).
Rationales to have combined/modified Bott / Breaux / Momtahan are above in claim 2 and reincorporated.
Regarding Claim 4: Bott / Breaux / Momtahan teaches all the limitations of claim 2 above.
Bott does not teach a user notification about usage information, as noted above in claim 2, and thus also falls short of including an indication and provision of control in the notification.
However, Momtahan in analogous art of mobile device control based on usage data teaches or suggests:
“wherein the application notification comprises information indicating and providing the control” (Momtahan col. 6 line 26: Subscribers can also set data usage notification and stop thresholds in mobile usage policy application 104. Upon reaching a notification threshold (i.e., 400MBs in the example embodiment depicted in FIG. 7), a subscriber will receive a notification on user equipment 102. At that point, the subscriber can optionally set a new, higher usage limit in mobile usage policy application 104, or choose to curtail data usage. Upon reaching a stop threshold (i.e., 600MBs in the example embodiment depicted in FIG. 7), a subscriber will be unable to use additional data services on user equipment 102 until a higher usage limit is set in mobile usage policy application 104 or server-side usage policy application 164).
Rationales to have combined/modified Bott / Breaux / Momtahan are above in claim 2 and reincorporated.
Regarding Claims 12, 17: Bott / Breaux teaches all the limitations of claims 11, 16 above.
Although Bott teaches analyzing pattern information of the usage of an application and controlling the application thus, Bott falls short of providing an interactive notification to the user about the data, specifying a time at which the notification is to be displayed, and including an indication and provision of control in the notification
However, Momtahan in analogous art of mobile device control based on usage data teaches or suggests:
“analyzing (claim 12) / analyze (claim 17) the pattern information” (Momtahan col. 3 line 61: In embodiments, both dynamic and static subscriber characteristics relative to a current usage session can be used to allow a Subscriber to proactively manage data usage. Dynamic characteristics can be dynamic relative to the start of a usage session or relative to the usage session generally. An example of a dynamic characteristic relative to the start of a usage session is the type of data requested and the mobile applications requesting data. An example of a dynamic characteristic relative to the usage session is the total amount of data usage. Col. 4 line 4: In a further embodiment, a subscriber characteristic used in data usage calculations includes knowledge of peak usage patterns (e.g., on peak/off-peak, weekdays). Col. 7 line 50: Usage policy server 160 uses the per-application usage data from prior sessions to inform the subscriber about which applications running on user equipment 102 have consumed the most bandwidth or databased on previous behavior patterns);
“compiling (claim 12) / compile (claim 17) an application notification, the application notification comprising interactive content corresponding to a predicted pattern of activity as indicated by the pattern information” (Momtahan col. 6 line 28: Upon reaching a notification threshold (i.e., 400MBs in the example embodiment depicted in FIG. 7), a subscriber will receive a notification on user equipment 102. At that point, the subscriber can optionally set a new, higher usage limit in mobile usage policy application 104, or choose to curtail data usage. Col. 11 line 63: In an embodiment, upon the authorization of a session, a usage breach probability is calculated by a breach probability calculation module (not shown) within quota manager 144. The usage breach probability represents the probability that the subscriber will breach his or her usage quota during the session); “and
“causing (claim 12) / cause (claim 17) display of the application notification” (Momtahan col. 4 line 64: FIGS. 7-11 depict a graphical user interface (GUI) for a mobile device to display data usage, edit usage limits, define tariffs, and accept offers to change service tiers, according to embodiments of the invention),
“wherein the display of the application notification occurs at a time related to one of a time prior to opening of the application and upon opening the application” (Momtahan col. 11 line 63: In an embodiment, upon the authorization of a session, a usage breach probability is calculated by a breach probability calculation module (not shown) within quota manager 144. The usage breach probability represents the probability that the Subscriber will breach his or her usage quota during the session. The usage breach probability can be based on any information and network usage statistics available at the time the session begins. Abstract: The method receives a notification at the subscriber's mobile device when a pre-determined quota is exceeded during the Subscriber session to control data usage), “and
“wherein the application notification comprises information indicating and providing the control” (Momtahan col. 6 line 26: Subscribers can also set data usage notification and stop thresholds in mobile usage policy application 104. Upon reaching a notification threshold (i.e., 400MBs in the example embodiment depicted in FIG. 7), a subscriber will receive a notification on user equipment 102. At that point, the subscriber can optionally set a new, higher usage limit in mobile usage policy application 104, or choose to curtail data usage. Upon reaching a stop threshold (i.e., 600MBs in the example embodiment depicted in FIG. 7), a subscriber will be unable to use additional data services on user equipment 102 until a higher usage limit is set in mobile usage policy application 104 or server-side usage policy application 164).
Rationales to have combined/modified Bott / Breaux / Momtahan are above in claim 2 and reincorporated.
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Conclusion
The following art is made of record and considered pertinent to Applicant’s disclosure:
Andreev et al. US 20160294962 A1, Methods and systems for management and control of mobile devices.
Day, II et al. US 20210286889 A1, Management and control of mobile computing device using local and remote software agents.
Garg et al. US 20220132208 A1, Predictive parental controls for networked devices.
James, M. JP 5866007 B2, Intelligent parental control for wireless devices
Park et al. US 20240272596 A1, Electronic device and control method therefor.
Shebaro et al. Context-Based Access Control Systems for Mobile Devices, in IEEE Transactions on Dependable and Secure Computing, vol. 12, no. 2, pp. 150-163, 1 March-April 2015, doi: 10.1109/TDSC.2014.2320731. https://ieeexplore.ieee.org/abstract/document/6807727
Vetaal et al. US 20150099483 A1, System and method for data usage management in an electronic device.
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/REED M. BOND/Examiner, Art Unit 3624
February 16, 2026
/HAMZEH OBAID/Primary Examiner, Art Unit 3624 February 17, 2026