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 .
DETAILED ACTION
Response to Applicant’s Remarks
1a. Applicant’s arguments and remarks, filed on 3/12/2026 (hereinafter Remarks), are acknowledged, and have been fully considered.
1b. Regarding Applicant’s remark, the Examiner summarizes the Examiner’s comments correspond to Applicant’ remarks in the following tables for ease of discussion. The third column is the page number of Remarks where the Applicant’s remarks are taken from. All Applicant’ remarks and Examiner’s comments are labeled with numbers in the first column.
Row
Claim
Page
Applicant’s Remarks
Examiner’s Responses
R.0
1
Applicant’s Claim 1:
A method comprising:
detecting, over a network at a location, an event corresponding to a time period, the event comprising data related to real-world and/or digital activities at the location;
identifying, from a database, at least one pattern of activity for the location, the at least one pattern of activity comprising information indicating real-world and/or digital activities from a previous time period;
analyzing the event based at least in part on the at least one pattern of activity;
determining, based on the analysis, a type of activity for the event and time period; and
executing, based on the determination, electronic controls of devices associated with the network.
The Examiner lists Applicant’s Claim 1 for the ease of discussion.
Claim 1 mainly discloses detecting, identifying, analyzing, an event during a time period at a location in a typical network, and determining a type of activity based on the event.
The claimed limitations network, event related digital activity are pretty broad terms, and are interpreted broadly.
R.1
1
7
Turning first to the rejections based on Wang, Applicant respectfully traverses. Wang is
directed exclusively to detecting network performance degradation events - specifically,
degradation in Service Level Expectation (SLE) metrics such as signal strength, roaming success
rates, and throughput within a wireless access network.
Wang’s disclosure about network performance degradation events is patentably equivalent to Applicant’s “event” related digital activity.
R.2
7
Wang's events are purely network-centric
metrics and are not events "comprising data related to real-world and/or digital activities at the
location" as claimed.
Wang may not agree with Applicant’s remarks.
Wang’s “network performance degradation events” is truly data related real-world and digital activities.
R.3
7
Wang has no mechanism for detecting or characterizing real-world activities
such as physical presence, behavioral patterns, occupancy, or other physical-world events at a
location, nor does it address digital activities beyond raw wireless performance metrics.
Applicant’s claim does not disclose real-world activities as “physical presence, behavioral patterns, occupancy, or other physical-world events” IN THE CLAIM. Hence, real-world activities are interpreted as any event in the real world, including, for example, electrical pulse in a network.
R.4
7
The
claimed "event" is therefore fundamentally different in character from the network performance
degradation trigger disclosed in Wang.
The claimed limitation “event” is broadly disclosed in the claim. Hence, it is interpreted broadly. Applicant may need to narrow down the scope of “event” IN THE CLAIM, to differentiate with Wang’s disclosures.
R.5
7
Wang further does not teach determining a type of activity for the event and time period
based on any analysis. Wang's determination is limited to classifying an access point as either an
edge AP or a non-edge AP based on the AP's position in wireless network topology. This is a
classification of a network device, not a determination of what type of activity is occurring at a
location during a given time period
Applicant’s claim does not specify the network characteristics IN THE CLAIM.
Wang’s AP based network in a network that operates according to Applicant’s claim.
Wang discloses analyzing various type of activities, see Fig 9, Step 906, Event based on SLE metric; see also Table 1 for metric of various acvity type.
R.6
7
The claimed step recites analyzing an event in conjunction
with identified historical patterns of real-world and digital activity to characterize the nature of
activity at the location, which is entirely absent from Wang's disclosure, as conceded by the
Examiner on page 4 of the Office Action.
Applicant’s claims do not disclose “historical patterns” IN THE CLAIM, thus, Applicant’s remark is irrelevant.
R.7
7
Applicant further submits that Wang does not teach executing electronic controls of
devices associated with the network based on any such activity-type determination. Wang's
network management actions are limited to either bypassing remediation for edge APs or resetting
and restarting non-edge APs - internal fault-mitigation actions directed at restoring wireless
performance. The claimed subject matter involves executing controls over devices associated with the network based on what kind of activity has been determined to be taking place at the location.
Wang may not agree with Applicant’s remarks. Network is a very complex system, to make the system operates properly, a plurality of electronic controls must work synchronously, as implied.
R.8
7-8
Wang's remediation actions are predicated solely on network fault root cause and AP
classification, not on any activity-type determination, and are directed only at the access point
itself rather than at devices associated with the network in a location-activity context.
Wang’s disclosures, part or whole, operate according to Applicant’s broad claims, regardless Wang’s applications.
Applicant may need to narrow down the scopes of the claims, to differentiate with Wang’s disclosures.
R.9
8
Accordingly, in view of the foregoing, Wang operates entirely within the domain of
network health monitoring and device topology management. None of Wang's teachings are
directed to detecting events tied to real-world or digital activities at a location, identifying
historical activity patterns for a location, determining a type of activity occurring during a time
period, or executing device controls based on such a determination. These are fundamental
distinctions, and Applicant respectfully requests that the rejection be withdrawn.
See R.9 above.
Wang’s disclosures, part or whole, operate according to Applicant’s broad claims, regardless Wang’s applications.
R.10
8
Turning to the rejections based on Muddu, Applicant respectfully traverses the contention
that Muddu cures the deficiencies in Wang. See page 4 of the Office Action.
Muddu is cited mainly for disclosures of pattern of activities or behavior.
R.11
8
Applicant submits that the claims subject matter recites, inter alia, identifying, from a
database, at least one pattern of activity for a location, where that pattern comprises information
indicating real-world and/or digital activities from a previous time period, and then analyzing a
detected event based at least in part on that pattern. Muddu's disclosure is directed to an entirely
different framework and fails to teach these limitations for the following reasons.
See R.10 above
1c. Thus, Wang and Muddu have fully discloses Applicant’s claims. The Examiner maintains the same grounds of rejections, and this office action is made final.
Claim Rejections - 35 USC § 103
2. 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.
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 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.
2a. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wang (US 20250023767 A1) in view of Muddu (US 20170063900 A1).
2b. Summary of the Cited Prior Art
Wang discloses a method for network management action base on network activities.
Muddu discloses a method for monitoring network activities.
2c. Claim Analysis
Regarding Claim 1, Wang discloses:
A method comprising (Figs 9-10):
Detecting (Fig 9, NETWORK EVENT DETECT? 905), over a network at a location (see: the AP is located near a location where client devices transition on and off a wireless network, in [0025]), an event corresponding to a time period (Fig 9, DETERMINE TIME SERIES 904), the event comprising data related to real-world and/or digital activities at the location (Fig 9, Step 906; see: the network events may include, for example, memory status, reboot events, crash events, Ethernet port status, upgrade failure events, ….., in [0047),
identifying, from a database (Fig 1, Network Data 152; see: The network data may be received as time series data that is monitored at one or more periodic intervals, in [0038]), at least one pattern of activity for the location, the at least one pattern of activity comprising information indicating real-world and/or digital activities from a previous time period (Table 1; see: determine, based on the time series of the SLE metrics, whether a network event has occurred, in [0008]; Examiner’s Note: time series is network data monitored and collected from previous periods),
analyzing the event based at least in part on the at least one pattern of activity
(Fig 3, VNA/AI ENGINE 350; see: VNA/AI engine 350 analyzes network data received from APs 142, 200 as well as its own data to monitor performance of wireless networks 106A-106N, in [0073]),
determining, based on the analysis, a type of activity for the event and time period; and (Fig 9, Steps 905-906; see: If a network event is detected, the one or more processor(s) further determine a root cause for the network event based on the time series of SLE metrics (906), in [0099]),
executing, based on the determination, electronic controls of devices associated with the network (Fig 9, Steps 912 and 914; see: the network management system may perform mitigation actions to remediate the root cause of the network event, in [0102]),
Wang does not use the term pattern.
However, Muddu discloses:
the at least one pattern of activity comprising information indicating real-world and/or digital activities from a previous time period (see: Figs 25-26; see: by searching for patterns of behavior that are abnormal or otherwise vary from the expected use pattern of a particular entity, in [0005]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to integrate Wang’s method for network management action base on network activities with Muddu’s method for monitoring network activities with the motivation being to improve the machine learning models employed to perform the evaluation (Muddu, [0150]).
Regarding Claim 2, Wang discloses:
wherein the electronic controls correspond to at least one of energy availability, network availability and capacity, and device operability (see: monitor the coverage and capacity SLE metrics for a wireless network, …, may monitor events, power, channel, bandwidth, in [0059]).
Regarding Claim 3, Wang discloses:
wherein the type of activity for the event corresponds to idle activity
(see: If a metric does not meet the configured SLE threshold value for the site, failure, that is idle, may occur, in [0057]), wherein the electronic controls correspond to a conservation of energy for the devices (see: adjust/modify the transmit power of a specific radio in a specific AP, in [0073]),
Regarding Claim 4, Wang discloses:
wherein the type of activity for the event corresponds to activity at or above a threshold level (see: A network management system can generate a network event in response to one or more of the thresholds being crossed, in 0023]), wherein the devices are monitored for a subsequent time period
Regarding Claim 5, Wang discloses:
analyzing the event and determining, based on the event analysis, attributes for the event;
determining, based on the attributes of the event and the information of the at least one pattern of activity, a set of scoring parameters; and
(see: the edges can be weighted based on capacity, cost, etc. In this case, the network device classifier 370 can determine the shortest path as the path that minimizes the sum of the weights of the paths, in [0062]; Examiner’s Note:
Wang does not elaborate about scoring parameters.
However, Muddu discloses:
computing a recommendation score based on the set of scoring parameters (Fig 25, Step 2506; see: Process 2500 continues at step 2506 with assigning an anomaly score based on the processing of the event data 2302 through the anomaly model in [0360]),
wherein the determination of the type of activity is based on the recommendation score (see: the analyst recommendation is automatically generated by the system based on the feature scores and or the anomaly score, in [0639]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to integrate Wang’s method for network management action base on network activities with Muddu’s method for monitoring network activities with the motivation being to improve the machine learning models employed to perform the evaluation (Muddu, [0150]).
Regarding Claim 6, Wang does not elaborate about scoring parameters.
However, Muddu discloses:
wherein the recommendation score is based on at least two components (Fig 71; see: a recommended response 7106 based on the plurality of feature scores, in [0639]) that correspond to a differing set of time periods for activities at the location (Fig 21, Step 2101-2104; see: to compute a score associated with the most recent time slice in [0316]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to integrate Wang’s method for network management action base on network activities with Muddu’s method for monitoring network activities with the motivation being to improve the machine learning models employed to perform the evaluation (Muddu, [0150]).
Regarding Claim 7, Wang discloses:
wherein the attributes comprise information related to at least one of network data, network usage data, application data, usage patterns, motion detection, presence data (see: Network device classifier 370 may analyze bandwidth usage of UEs where UE bandwidth usage is below a threshold value, in [0066]).
Regarding Claim 8, Wang discloses:
collecting activity data from a plurality of devices operating on the network (see: may collect network data to monitor wireless network behavior, in [0023]),
analyzing the activity data (Fig 3, VNA/AI ENGINE 350; see: VNA/AI engine 350 analyzes network data received from APs 142, 200 as well as its own data to monitor performance of wireless networks 106A-106N, in [0073]),
determining a plurality of patterns of behavior for the network; and (see: determine a time series of SLE metrics based on the received network data (904), in [0097]; Examiner’s Note: the network behavior patterns are collected as time series data),
storing (see: The network data may be stored in a database associated with NMS 150, in [0032]) the determined plurality of patterns of behavior, wherein the at least one pattern of activity is a stored pattern of behavior (see: The network data may be received as time series data that is monitored at one or more periodic intervals, in [0038]).
Regarding Claim 9, Wang discloses:
identifying a set of activity patterns (see: may collect network data to monitor wireless network behavior, in [0023]), wherein the set of activity patterns correspond to previous activities occurring at previous time periods that are similar to the time period (see: The network data may be received as time series data that is monitored at one or more periodic intervals, in [0038]),
wherein the analysis of the event is based on the set of activity patterns (Table 1; see: determine, based on the time series of the SLE metrics, whether a network event has occurred, in [0008]; Examiner’s Note: time series is network data monitored and collected from previous period activity patterns).
Regarding Claim 10, Wang discloses:
wherein the event comprises a set of events for the time period (see: The network data may be received as time series data that is monitored at one or more periodic intervals, in [0038]).
Regarding Claims 11-15, the device claims disclose similar features as of Claims 1, 3, 5, 7 and 9, and are rejected accordingly.
Regarding Claims 16-20, the method claims disclose similar features as of Claims 1, 3, 5, 7 and 9, and are rejected accordingly.
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 extension fee 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 Jung-Jen Liu whose telephone number is 571-270-7643. The examiner can normally be reached on Monday to Friday, 9:00 AM to 5:00 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kwang B. Yao can be reached on 571-272-31823182. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JUNG LIU/ Primary Examiner, Art Unit 2473