DETAILED ACTION
Claims 1-7 are pending and have been examined.
This application is a CON of 18/125,926, now US 12,206,544.
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 .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-7 are rejected on the ground of nonstatutory double patenting as being unpatentable over Claims 1-5, 10 and 11 of U.S. Patent No. 12,206,544. Although the claims at issue are not identical, they are not patentably distinct from each other because the patent’s claims anticipate the instant application’s claims according to the table below.
Instant Application Patent
1. A computer-implemented method in a network device on an enterprise network that includes a wireless network, for preemptively remediating a wireless network with artificial intelligence based on user behavior to prevent switching from wireless to wired connections, the method comprising: detecting a change of a user device from a wireless connection to the enterprise network to a wired connection to the enterprise network; responsive to the detection, generating a snapshot of network conditions relevant to the user device; performing a health check on the network conditions to identify specific network issues negatively affecting the user device; identifying a remediation associated with the specific network issues; generating a remediation model with AI that a different user change will occur based on a later health check revealing similar network conditions to the earlier health check; and responsive to the prediction, automatically remediating the specific network issues based on the earlier stored remediation the earlier health check.
1. A computer-implemented method in a network device on an enterprise network that includes a wireless network, for preemptively remediating a wireless network with artificial intelligence (AI) based on user behavior to prevent switching from wireless to wired connections, the method comprising: detecting a change of a user device from a wireless connection to the enterprise network to a wired connection to the enterprise network; responsive to the detection, generating a snapshot of network conditions to identify specific network conditions to identify issues negatively affecting the user while on the wireless network, by performing a reactive health check, relevant to the user device; identifying a remediation associated with the specific network issues; generating a remediation model with AI that a different user change will occur based on a later health check revealing similar network conditions to the earlier health check; performing a preventative health check on network conditions to predict a change by the second user device from the wireless network to the wired network, and responsive to the prediction, automatically remediating the specific network issues based on the earlier stored remediation of the earlier health check, prior to an actual change from the wireless network to the wired network by the second user device.
2. The method of claim 1, wherein the snapshot includes conditions of the user device.
2. The method of claim 1, wherein the snapshot includes conditions of the user device.
3. The method of claim 1, wherein the snapshot includes conditions of the access point.
3. The method of claim 1, wherein the snapshot includes conditions of an access point.
4. The method of claim 1, wherein the snapshot includes conditions of a plurality of network devices.
4. The method of claim 1, wherein the snapshot includes conditions of a plurality of network devices.
5. A non-transitory computer-readable medium in a network device on an enterprise network that includes a wireless network for preemptively remediating a wireless network with artificial intelligence based on user behavior to prevent switching from wireless to wired connections, the method comprising: detecting a change of a user device from a wireless connection to the enterprise network to a wired connection to the enterprise network; responsive to the detection, generating a snapshot of network conditions relevant to the user device; performing a health check on the network conditions to identify specific network issues negatively affecting the user device; identifying a remediation associated with the specific network issues; generating a remediation model with AI that a different user change will occur based on a later health check revealing similar network conditions to the earlier health check; and responsive to the prediction, automatically remediating the specific network issues based on the earlier stored remediation the earlier health check.
5. A non-transitory computer-readable medium comprising source code, in a network device on an enterprise network that includes a wireless network for, when the source code is executed by a processor, preemptively remediating a wireless network with artificial intelligence (AI) based on user behavior to prevent switching from wireless to wired connections, the method comprising: detecting a change of a user device from a wireless connection to the enterprise network to a wired connection to the enterprise network; responsive to the detection, generating a snapshot of network conditions to identify specific network conditions to identify issues negatively affecting the user while on the wireless network, by performing a reactive health check, relevant to the user device; identifying a remediation associated with the specific network issues; generating a remediation model with AI that a different user change will occur based on a later health check revealing similar network conditions to the earlier health check; performing a preventative health check on network conditions to predict a change by the second user device from the wireless network to the wired network, and responsive to the prediction, automatically remediating the specific network issues based on the earlier stored remediation of the earlier health check, prior to an actual change from the wireless network to the wired network by the second user device.
6. A network device on an enterprise network that includes a wireless network for preemptively remediating a wireless network with artificial intelligence based on user behavior to prevent switching from wireless to wired connections, the network device comprising: a processor; a network interface communicatively coupled to the processor and to the WLAN; and a memory, communicatively coupled to the processor and storing: a user behavior module to detect a change of a user device from a wireless connection to the enterprise network to a wired connection to the enterprise network; a snapshot capture module to, responsive to the detection, generate a snapshot of network conditions relevant to the user device; a health check module to perform a health check on the network conditions to identify specific network issues negatively affecting the user device; a remediation module to identify a remediation associated with the specific network issues; and an AI prediction module to generate a remediation model with AI that a different user change will occur based on a later health check revealing similar network conditions to the earlier health check, wherein the remediation module automatically remediates the specific network issues based on the earlier identified remediation of the earlier health check.
10. A network device on an enterprise network that includes a wireless network for preemptively remediating a wireless network with artificial intelligence (AI) based on user behavior to prevent switching from wireless to wired connections, the network device comprising: a processor; a network interface communicatively coupled to the processor and to the WLAN; and a memory, communicatively coupled to the processor and storing: a user behavior module to detect a change of a user device from a wireless connection to the enterprise network to a wired connection to the enterprise network; a snapshot capture module to, responsive to the detection, generate a snapshot of network conditions relevant to the user device; a health check module to perform a health check on the network conditions to identify specific network issues negatively affecting the user device; a remediation module to identify a remediation associated with the specific network issues; and an AI prediction module to generate a remediation model with AI that a different user change will occur based on a later health check revealing similar network conditions to the earlier health check, wherein the remediation module performs a preventative health check on network conditions to predict a change by the second user device from the wireless network to the wired network, and wherein the remediation module automatically remediates the specific network issues based on the earlier identified remediation of the earlier health check, prior to an actual change from the wireless network to the wired network by the second user device.
7. The method of claim 6, wherein the network device comprises an access point.
11. The network device of claim 10, wherein the network device comprises an access point.
Claim Objections
Claims 1 and 5 are objected to because of the following informalities: There appears to be a missing word (of) between the phrases “the earlier stored remediation” and “the earlier health check” in the last limitation. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 3 and 7 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the prediction" in the last limitation. There is insufficient antecedent basis for this limitation in the claim.
Claim 3 recites the limitation "the access point" in the first limitation. There is insufficient antecedent basis for this limitation in the claim.
Claim 7 recites the limitation "The method of claim 6" in the preamble. There is insufficient antecedent basis for this limitation in the claim. Claim 6 is a network device claim, not a method claim.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-7 are rejected under 35 U.S.C. 103 as being unpatentable over US 2015/0373574 A1 (Gordon et al.), in view of US 2023/0245156 A1 (Cella et al.).
As to Claims 1, 5 and 6, Gordon et al. disclose a computer-implemented method; a non-transitory computer-readable medium; and a network device, respectively, in a network device on an enterprise network that includes a wireless network (Gordon et al. disclose the mobile network operator service {enterprise network 100 – Fig 1. and ¶ [0050]}, for preemptively remediating a wireless network to prevent switching from wireless to wired connections (Gordon et al. disclose whether to switch from a mobile device’s cellular {wireless} connection to an available VOIP {wired} connection based on a variety of factors - ¶ [0154]. If the conditions are not favorable, VOIP connection is prevented), the method comprising:
detecting a change of a user device from a wireless connection to the enterprise network to a wired connection to the enterprise network (Gordon et al. disclose the mobile device checking for available WiFi data network(s), measuring its signal strength {snapshot of VOIP via WiFi} {requires change to wired connection via VOIP, calculating an overall WiFi score, then determining whether to switch the device over to WiFi {VOIP}. If the WiFi score is worse than the cellular score {snapshot of cellular}, cellular remains in use. If WiFi is better, the connection is switched from cellular to WiFi – Fig. 16);
responsive to the detection, generating a snapshot of network conditions relevant to the user device (Gordon et al. disclose the mobile device checking for available WiFi data network(s), measuring its signal strength {snapshot of VOIP via WiFi} {requires change to wired connection via VOIP, calculating an overall WiFi score, then determining whether to switch the device over to WiFi {VOIP}. If the WiFi score is worse than the cellular score {snapshot of cellular}, cellular remains in use. If WiFi is better, the connection is switched from cellular to WiFi – Fig. 16);
performing a health check on the network conditions to identify specific network issues negatively affecting the user device (Gordon et al. disclose whether to switch from a mobile device’s cellular {wireless} connection to an available VOIP {wired} connection based on a variety of factors including relative comparison of both the cellular quality and VOIP quality {health check} - ¶ [0154]. If cellular has better quality, cellular is not switched to VOIP);
identifying a remediation associated with the specific network issues (Gordon et al. disclose whether to switch from a mobile device’s cellular {wireless} connection to an available VOIP {wired} connection based on a variety of factors including relative comparison of both the cellular quality and VOIP quality {health check} - ¶ [0154]. If cellular has better quality, cellular is not switched to VOIP {remediation}).
Gordon et al. are silent on the use of AI to create connection switching models. However Cella et al. disclose
artificial intelligence based on user behavior (Cella et al. disclose the network enhancement chip using AI to analyze, predict, optimize and reconfigure communication networks based on, inter alia, historical device information related to network flows, bandwidth metrics, traffic types, network types used, etc. - ¶ [1342]);
generating a remediation model with AI that a different user change will occur based on a later health check revealing similar network conditions to the earlier health check (Cella et al. disclose the digital twin factoring in past connections used to predict with configurations will optimize communications - ¶ [1342]); and
responsive to the prediction, automatically remediating the specific network issues based on the earlier stored remediation [of] the earlier health check (Cella et al. disclose the digital twin factoring in past connections used to predict with configurations will optimize communications - ¶ [1342]).
It would have been obvious to one of ordinary skill in the art to combine artificial intelligence based on user behavior; generating a remediation model with AI that a different user change will occur based on a later health check revealing similar network conditions to the earlier health check; and responsive to the prediction, automatically remediating the specific network issues based on the earlier stored remediation [of] the earlier health check, taught by Cella et al., with performing a health check on the network conditions to identify specific network issues negatively affecting the user device and determining whether to switch from a mobile device’s cellular {wireless} connection to an available VOIP {wired} connection, taught by Gordon et al., in order to configure a device for optimal communication conditions (Cella et al. - ¶ [1342]).
As to Claim 2, the combination of Gordon et al. and Cella et al. discloses the method of claim 1,
wherein the snapshot includes conditions of the user device (Gordon et al. disclose the mobile device checking for available WiFi data network(s), measuring its signal strength {snapshot of VOIP via WiFi} {requires change to wired connection via VOIP, calculating an overall WiFi score, then determining whether to switch the device over to WiFi {VOIP}. If the WiFi score is worse than the cellular score {snapshot of cellular}, cellular remains in use. If WiFi is better, the connection is switched from cellular to WiFi – Fig. 16. Cella et al. disclose the digital twin factoring in past connections used to predict with configurations will optimize communications - ¶ [1342]).
The motivation and obviousness arguments are the same as in Claim1.
As to Claim 3, the combination of Gordon et al. and Cella et al. discloses the method of claim 1,
wherein the snapshot includes conditions of the access point (Gordon et al. disclose the mobile device checking for available WiFi data network(s), measuring its signal strength {snapshot of VOIP via WiFi which is a wireless access point} {requires change to wired connection via VOIP, calculating an overall WiFi score, then determining whether to switch the device over to WiFi {VOIP}. If the WiFi score is worse than the cellular score {snapshot of cellular}, cellular remains in use. If WiFi is better, the connection is switched from cellular to WiFi – Fig. 16).
As to Claim 4, the combination of Gordon et al. and Cella et al. discloses the method of claim 1,
wherein the snapshot includes conditions of a plurality of network devices (Cella et al. recites “A network digital twin can provide a virtual representation of the physical communication network(s) that a network device has access to and the current state of those network(s) and/or network devices, as explained in more detail below.” - ¶ [1342]).
The motivation and obviousness arguments are the same as in Claim1.
As to Claim 7, the combination of Gordon et al. and Cella et al. discloses the method of claim 6,
wherein the network device comprises an access point (Gordon et al. disclose the mobile device checking for available WiFi data network(s), measuring its signal strength {snapshot of VOIP via WiFi which is a wireless access point} {requires change to wired connection via VOIP, calculating an overall WiFi score, then determining whether to switch the device over to WiFi {VOIP}. If the WiFi score is worse than the cellular score {snapshot of cellular}, cellular remains in use. If WiFi is better, the connection is switched from cellular to WiFi – Fig. 16).
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Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See Form PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RICHARD G KEEHN whose telephone number is (571)270-5007. The examiner can normally be reached M-F 9:00am - 5:00pm Eastern.
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/RICHARD G KEEHN/Primary Examiner, Art Unit 2444