DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 7-24-2026 have been fully considered but they are not persuasive.
Regarding the 101 rejection, please note that the newly amended limitation describe instead of the method or device, the configurable settings with intended use and not necessarily is part of the method or device. Also, the plain meaning of “associated” only require a relationship or reason to say that there is a connection between the items (see MPEP 2111.01). Thereby, the claims are not tied to a cellular network, but it has a relation to a cellular network, and the amendment does not change much the scope and fails to integrate or tie the mental process and/or mathematical formula. Applicant submits that a human cannot practically perform the steps in the human mind, but the argument fails to articulate why. The input is a vector which is a value with direction and can be easily performed with just observation such as looking at somebody walking to know where the person is moving and can make or output recommendations such as determining that the person is going to a restroom and configuring something such as a light, paper, etc. Please note that the output of the model such as the values is never used in the configuration, the configuration is for the intended use of applying the values; however, the claims do not require them to apply the values. The rest of the arguments for the 101 rejection are directed to tie the claims to a cellular network, but as previously stated, only an abstract relationship is required; thereby, no cellular network is required.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., details of machine learning, cellular network, wireless emergency alert via a cell site) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Please note that abstract and relative limitations that suggest but does not require such as associations will fail to differentiate from the prior art, since they only require a reason for the relationship rather than actual modification. Also, statements reciting the purpose or intended use of the claimed invention must be evaluated to determine whether or not the recited purpose or intended use results in a structural difference, in the present claims the intended use results in no structural difference (see MPEP 2103 I.C. and 2111.02). A possible interpretation of the configuring step may just be turning on something and then the element is ready to apply the first plurality of values, but the method or device never recite that the values were applied, much less used nor that any broadcast was ever performed, only that some values are desirable to be used as such. A simple structure of a configurable setting could be a binary value, such as 0 or 1, and any of the intended uses of the configurable setting fail to change the structure of the binary values. Therefore, the intended use results in no structural difference.
Since applicant challenged the official notice, see below the Li reference for claim 16; please note, there is no rejection of Hegde in view of official notice as stated in the remarks.
The rest of the arguments fall for the same reasons as shown above. The rejection of record stands.
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, 5-16 and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to mental process/mathematical concept without significantly more. The claim(s) recite(s) applying an input to a mathematical formula, obtaining values of the mathematical formula and configuring a network element with the value. These steps are akin to mental process and/or mathematical formula which was at issue in Alice Corp and has been identified among non-limiting examples of an abstract idea, which is capable of being performed mentally or using a pen and paper, which the court in Dietgoal Innovations identified as an abstract idea. This judicial exception is not integrated into a practical application because the claimed invention is not directed to improvements in computer-related technology (e.g., improvements in computer capabilities) as was the case in Enfish, but rather on processing data. The claim(s) recite the additional element of a cell site, processor; however, the additional element is not sufficient to amount to significantly more than the judicial exception because the recited limitations are not necessarily rooted in the computer arts, nor do they improve the functionality computer itself or another technical field, the element is only used to describe an abstract relationship or association. The rest of the claims further define further description of inputs, mathematical formulas, extra solution activity and intended use. Therefore, when viewed either as individual limitations or as an ordered combination, the claim as a whole does not add significantly more to the abstract idea (STEP 2B: NO). Therefore, the claims are directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Hegde 20250097664.
As to claim 1, Hegde discloses a method comprising: applying, by a processing system [150] including at least one processor (see par. 0089), an input to a location-based services recommendation module comprising at least one location-based service prediction model [152] (receiving time data and location data), the input comprising first characteristics [geographic information of the first cell site] associated with a first cell site of a cellular network (see abstract; par. 0063); obtaining, by the processing system, an output of the location-based services recommendation module in response to the applying of the input vector [determining the predicted density includes predicting the foot traffic or number of users in different location areas of the cell. The predicted density is determined using one or more machine learning models] (see par. 0063), wherein the location-based services recommendation module is implemented by the processing system (see par. 0026-0027), and wherein the output comprises a first plurality of values for a plurality of configurable settings of at least a first network element associated with the first cell site (see fig. 2; par. 00036, 0064); and configuring, by the processing system, the at least the first network element associated with the first cell site to apply at least one of the first plurality of values for at least one of the plurality of configurable settings, wherein the at least one of the plurality of configurable settings for a wireless emergency alert broadcast via the at least the first cell site (see par. 0045-0050, 0066-0069). Hegde does not disclose the word vector. However, since the only thing known for the input vector is that it has a first characteristics and according claim 5, the characteristics can be geographic information of the first cell site and Hegde disclose the limitation in par. 0029 and include location and direction (see abstract), it would be obvious that Hegde’s location is equivalent to the input vector. Therefore, it would have been obvious to one of the ordinary skills in the art before the effective filing date of the present invention that Hegde location information is equivalent to the input vector since it is going to bring the same predictable result of obtaining an output of the location-based services in response to the applying of the input and send alerts, instructions, etc.; thereby, potentially saving lives.
As to claim 5, Hegde discloses the method of claim 1, wherein the first characteristics associated with the first cell site comprise at least one of:
characteristics of the at least the first network element associated with the first cell site of the cellular network;
geographic information of the first cell site (see par. 0029); or
demographic information of the first cell site.
Regarding claim 19 is the corresponding non-transitory computer-readable medium claim of method claim 1. Therefore, claim 19 is rejected for the same reasons as shown above.
Regarding claim 20 is the corresponding apparatus claim of method claim 1. Therefore, claim 20 is rejected for the same reasons as shown above.
Claim(s) 6-15 are rejected under 35 U.S.C. 103 as being unpatentable over Hegde 20250097664 in view of Pachigar 20240403741.
As to claims 6-7, Hegde discloses the method of claim 1, further comprising:
training the at least one location-based service prediction model with a training data set comprises a plurality of training samples and wherein each training comprises: a set of predictor values [the machine learning model 152 is trained in order to determine the weights/coefficients using supervised learning prior to operation. In some examples, synthetic (non-real world) time data and location data is generated for the independent variables and synthetic density data for the location areas is generated for dependent variables] (see par. 0031, 0037) wherein each set of predictor values comprises characteristics associated with a respective cell site (see par. 0031-0032). Hegde fails to disclose a set of labels. In an analogous art, Pachigar discloses wherein the training data set comprises a plurality of training samples and wherein each set of labels comprises a respective set of values for the plurality of configurable settings that are implemented via one or more network elements [supervised learning may include providing training data and labels corresponding to the training data] (see par. 0035, 0084). Therefore, it would have been obvious to one of the ordinary skills in the art before the effective filing date of the present invention to use labels for the simple purpose of identifying data easily.
As to claim 8, Hegde discloses the method of claim 6, further comprising:
detecting an adjustment to the at least one of the first plurality of values for the at least one of the plurality[ies] of configurable settings (see par. 0031,0040).
As to claim 9, Hegde discloses the method of claim 8, further comprising: updating the at least one location-based service prediction model in accordance with the adjustment to the at least one of the first plurality of values for the at least one of the plurality[ies] of configurable settings [predictor function is associated with a specific weight/coefficient determined via training and the weights/coefficients can be updated during operation of the system] (see par. 0031, 0037, 0040).
As to claim 10, Hegde discloses the method of claim 9, wherein the updating comprises retraining the at least one location-based service prediction model with an additional training sample comprising the first characteristics associated with the first cell site and a set of values for the plurality of configurable settings that are implemented at the first cell site, the set of values including at least one adjusted value in accordance with the adjustment to the at least one of the first plurality of values for the at least one of the plurality of configurable settings [the machine learning computing system 150 is configured to perform additional learning during operation and adapt the weights/coefficients based on real world time data, location data, and/or density data] (see par. 0038).
As to claim 11, Hegde discloses the method of claim 6, wherein the at least one location-based service prediction model is associated with at least one location-based service [learning during operation and adapt the weights/coefficients based on real world time data, location data, and/or density data (for example, estimated number of UEs 108 in a location area).] (see par. 0038).
As to claim 12, Hegde discloses the method of claim 11, further comprising: obtaining at least one performance indicator associated with the first cell site and associated with the at least one location-based service [performance parameters can also be used for the additional learning during operation] (see par. 0038).
As to claim 13, Hegde discloses the method of claim 12, further comprising: updating the at least one location-based service prediction model in accordance with the at least one performance indicator (see par. 0038).
As to claim 14, Hegde discloses the method of claim 12, wherein the at least one performance indicator comprises at least one of:
a wireless emergency alert accuracy [the number of independent variables of the machine learning model 152 can be selected during training based on the desired level of accuracy] (see par. 0039, 0066);
a wireless emergency alert latency; or
a wireless emergency alert reliability.
As to claim 15, Hegde discloses the method of claim 12, wherein the at least one performance indicator comprises at least one of:
a call success rate associated with emergency services calls;
a location accuracy associated with an emergency services call (see par. 0041);
a call location-based route success rate; or a
text-to-911 service message success rate.
Claim(s) 16 is rejected under 35 U.S.C. 103 as being unpatentable over Hegde 20250097664 in view of Pachigar 20240403741 and further in view of Li 20200187295.
As to claim 16, the previous references fail to disclose wherein the at least one performance indicator comprises a call defect rate. In an analogous art, Li discloses disclose wherein the at least one performance indicator comprises a call defect rate (see par. 0014). Therefore, it would have been obvious to one of the ordinary skills in the art before the effective filing date of the present invention to use call defect rate for the simple purpose of monitoring the success rate of the calls to improve and/or maintain the quality of the calls.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARCOS L TORRES whose telephone number is (571)272-7926. The examiner can normally be reached 10:00 AM - 6:00 PM M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alison Slater can be reached at (571)270-0375. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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MARCOS L. TORRES
Primary Examiner
Art Unit 2647
/MARCOS L TORRES/Primary Examiner, Art Unit 2647
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