Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination under 37 CFR §1.114
2. A request for continued examination under 37 CFR §1.114, including the fee set forth in 37 CFR §1.17(e), was filed on July 8, 2026 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forth in 37 CFR §1.17(e) has been timely paid, the finality of the previous Office action dated May 15, 2026 has been withdrawn pursuant to 37 CFR §1.114 and the submission filed on June 17, 2026 has been entered. Claims 1-19 are pending and are rejected for the reasons set forth below.
Claim Rejections - 35 USC § 101
3. 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.
4. Claims 1-19 are rejected under 35 U.S.C. §101 because the claimed invention recites and is directed to a judicial exception to patentability (i.e., a law of nature, a natural phenomenon, or an abstract idea) and does not include an inventive concept that is “significantly more” than the judicial exception under the January 2019 and October 2019 patentable subject matter eligibility guidance (2019 PEG) analysis which follows.
Step 1
5. Under the 2019 PEG step 1 analysis, it must first be determined whether the claims are directed to one of the four statutory categories of invention (i.e., process, machine, manufacture, or composition of matter). Applying step 1 of the analysis for patentable subject matter to the claims, it is determined that the claims are directed to the statutory category of a process (claims 12-19) and a machine (claims 1-11); where the machine is substantially directed to the subject matter of the process (See e.g., MPEP §2106.03). Therefore, we proceed to step 2A, Prong 1.
Step 2A, Prong 1
6. Under the 2019 PEG step 2A, Prong 1 analysis, it must be determined whether the claims recite an abstract idea that falls within one or more designated categories of patent ineligible subject matter (i.e., organizing human activity, mathematical concepts, and mental processes) that amount to a judicial exception to patentability.
Claim 1 recites the abstract idea of:
receive a request to generate a message, wherein the request to generate a message comprises recipient data, including a location data identified in [[a location-based service selected from the group comprising of global positioning system tracking service, cellular triangulation service or cell tower identification service]], and message information specifying a query for user response information;
identify a plurality of recipients, based at least in part on the recipient data by filtering potential recipients according to geolocation processing of the location data contained in the recipient data;
generate a message, based at least in part on the message information;
receive a set of responses, [[via said wireless network]], from at least a portion of said [electronic communication devices of said]] plurality of recipients, wherein each response includes embedded location metadata from said [[electronic communication devices]]; and
validate the veracity of each response of said set of responses by cross-referencing the embedded location metadata with the location data by confirming the embedded location metadata… resulting in a set of validated responses;
extract data points for zoning from the set of validated responses, wherein the data points comprise content from the user response information comprising answers to the query for user response information and associated embedded location metadata;
identify, from content in each validated response in said set of validated responses, data points for generation of a zone map; and
generate a zone map, based at least in part on the data points for generation of a zone map.
Here, the recited abstract idea falls within one or more of the three enumerated 2019 PEG categories of patent ineligible subject matter, to wit: certain methods of organizing human activity, which includes fundamental economic practices and/or commercial interactions (e.g., zoning geographic regions for insurance/commercial purposes). As discussed in paragraphs 2-5 of the applicant’s specification, the zoning of geographic regions is a common practice used for various financial and commercial purposes. For example, zoning is an important practice when determining insurance rates for various policies and determining the best location for new businesses. As noted above, the claims recite limitations for engaging individuals to collect information relevant to these zoning decisions and generating zone maps. Such limitations fall under the category of organizing human activity as noted above.
Step 2A, Prong 2
7. Under the 2019 PEG step 2A, Prong 2 analysis, the identified abstract idea to which claim 1 is directed does not include limitations or additional elements that integrate the abstract idea into a practical application.
Besides reciting the abstract idea, the limitations of claim 1 also recite generic computer components (e.g., one or more hardware processors configured by machine readable instructions; a location-based service selected from the group comprising of global positioning system tracking service, cellular triangulation service or cell tower identification service; wireless network; natural language processing; a machine learning model; a first graphical user interface on a display component of an electronic communication devices; and a second graphical user interface on a display component of a secondary electronic communication device). In particular, the recited features of the abstract idea are merely being applied on a computer or computing device or via software programming that is simply being used as a tool (“apply it”) to implement the abstract idea. (See e.g., MPEP §2106.05(f)). Therefore, these additional elements are recited at a high level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components. In other words, the additional elements are simply used as tools to perform the abstract idea.
Claim 1 also recites the limitation, “the embedded location metadata being identified via said location-based service comprising at least one of global positioning system tracking, cellular triangulation, or cell tower identification.” This limitation simply states that the location metadata is identified based on at least one of various location tracking technologies (e.g., global positioning system tracking, cellular triangulation, or cell tower identification). However, the claim does not provide significant technical detail regarding how these technologies are implemented to perform the claimed functions. Therefore, such limitations amount to no more than merely applying generic location tracking technology to facilitate the abstract idea.
Claim 1 also recites the limitation, “requiring login to a system in order to provide a response, two-factor authentication, or geolocation/geo-fencing methods to ensure the recipient is in the geographic region associated with the geolocation processing.” This limitation simply states that the user must log in to verify that they are in the geographic region identified in the location metadata. The examiner notes that the broadest reasonable interpretation of this limitation simply requires the user to log into the system and provide a response verifying this information. The claim does not provide significant technical detail regarding how this response, and/or two-factor authentication of geolocation/geo-fencing methods, are implemented to perform the validation process. Therefore, such limitations amount to no more than merely applying generic computer-related components (e.g., a system that the user logs into) in order to facilitate the abstract idea.
Claim 1 also recites the limitation, “apply a machine learning model trained on previous communications and responses received by the system, and on information provided to the system about results of prior zoning, in order to optimize and improve performance of automated zone creation, to cluster the data points for zoning into zones based on similarity of the data points and proximity of a zone to the location metadata.” This limitation simply states that the system uses a machine learning model to cluster the data points and update the zone boundaries. However, the claim does not provide significant technical detail regarding how the machine learning model is trained and/or implemented to provide the desired output. While this limitation provides detail regarding the type of data used to train the model (e.g., previous communications and responses received by the system, and information corresponding to results of prior zoning), such detail does not functionally define how the model is trained. Similarly, simply stating that the training is performed “in order to improve performance of automated zone creation” does not provide any indication of an improvement to the functioning of machine learning model itself. Such limitations do not provide any technical detail regarding how the model is trained and/or implemented to perform the claimed functions. Rather, this simply claims the desired result of the training process. Therefore, such limitations amount to no more than merely applying generic machine learning technology to implement the abstract idea on a computer.
Claim 1 also recites the following limitations:
transmit said message in a machine readable format, via a wireless network to be displayed on a first graphical user interface on a display component of an electronic communication devices of said plurality of recipients; and
transmit said zone map in a machine readable format, via the wireless network, to be displayed on a second graphical user interface on a display component of a secondary electronic communication device.
These limitations simply state that the system displays various information on interfaces of a plurality of electronic communication devices. However, the claim does not provide significant technical detail regarding how the information is displayed. Therefore, these limitations amount to no more than merely outputting/displaying data, which is a form of insignificant extra-solution activity (See MPEP 2016.05(g): OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015)).
Thus, claim 1 does not include any limitations or additional elements that integrate the abstract idea into a practical application. As a result, claim 1 is directed to an abstract idea.
Step 2B
8. Under the 2019 PEG step 2B analysis, the additional elements of claim 1 are evaluated to determine whether they amount to something “significantly more” than the recited abstract idea. (i.e., an innovative concept). Here, the recited additional elements (e.g., one or more hardware processors configured by machine readable instructions; a location-based service selected from the group comprising of global positioning system tracking service, cellular triangulation service or cell tower identification service; wireless network; natural language processing; a machine learning model; a first graphical user interface on a display component of an electronic communication devices; and a second graphical user interface on a display component of a secondary electronic communication device), do not amount to an innovative concept since, as stated above in the Step 2A, Prong 2 analysis, the claims are simply using the additional elements as a tool to carry out the abstract idea (i.e., “apply it”) on a computer or computing device and/or via software programming (See e.g., MPEP §2106.05(f)). The additional elements are specified at a high level of generality such that they are being used in the claims to simply implement the abstract idea and are not themselves being technologically improved (See e.g., MPEP §2106.05 I.A.); (See also e.g., applicant’s Specification at least Paragraphs 54-60).
Additionally, the following limitation identified above as insignificant extra-solution activity (merely outputting/displaying data) has been revaluated in Step 2B:
transmit said message in a machine readable format, via a wireless network to be displayed on a first graphical user interface on a display component of an electronic communication devices of said plurality of recipients; and
transmit said zone map in a machine readable format, via the wireless network, to be displayed on a second graphical user interface on a display component of a secondary electronic communication device.
As stated in MPEP 2106.05(d), a factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity (Berkheimer v. HP, Inc., 881 F.3d 1360, 1368 (Fed. Cir. 2018)). In view of this requirement set forth by Berkheimer, this limitation does not integrate the abstract idea into a practical application, or amount to significantly more than the abstract idea, because the courts have found the concept of merely outputting/displaying data to be well-understood, routine, and conventional activity (See MPEP 2106.05(d): OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015)).
Thus, claim 1 does not recite any additional elements that amount to “significantly more” than the abstract idea.
Additional Independent Claims
9. Independent claim 12 is similarly rejected under 35 U.S.C. 101 for the reasons described below:
Claim 12 recites limitations that are substantially similar to those recited in claim 1. However, the primary difference between claims 12 and 1 is that claim 12 is drafted as a method rather than as a system. Similarly, as described above regarding claim 1, claim 12 recites generic computer components (e.g., a communication module and one or more processors; a location-based service selected from the group comprising of global positioning system tracking service, cellular triangulation service or cell tower identification service; wireless network; natural language processing; a machine learning model; a first graphical user interface on a display component of an electronic communication devices; and a second graphical user interface on a display component of a secondary electronic communication device) that are simply being used as a tool (“apply it”) to implement the abstract idea. Therefore, since the same analysis should be used for claims 1 and 12, claim 12 is not patent eligible (See Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014)).
Dependent Claims
10. Dependent claims 2-11 and 13-19 are also rejected under 35 U.S.C. 101 for the reasons described below:
Claims 2 and 13 simply refine the abstract idea because they recite process steps (e.g., generating an action response plan, and providing the action response plan to a user) that fall under the category of organizing human activity, namely zoning geographic regions for insurance/commercial purposes, as described above regarding claim 1.
Claims 3 and 14 simply refine the abstract idea because they recite process steps (e.g., receiving updated data regarding the implementation of the action response plan, and updating a data set based on the received data) that fall under the category of organizing human activity, namely zoning geographic regions for insurance/commercial purposes, as described above regarding claim 1.
Claims 4-7 and 15-18 simply state that the model data is used by a machine learning model or an artificial intelligence model in order to generate the action response plan and the zone maps. However, the claims do not provide any technical detail regarding how the machine learning model and/or the artificial intelligence model are implemented to produce the action response plan and the zone maps. Therefore, these limitations amount to no more than simply applying generic machine learning and artificial intelligence technology to implement the abstract idea on a computer.
Claims 8 and 19 simply refine the abstract idea because they recite process steps (e.g., generating a second action response plan based on updated responses, and providing the updated response plan to the user) that fall under the category of organizing human activity, namely zoning geographic regions for insurance/commercial purposes, as described above regarding claim 1.
Claims 9-11 simply refine the abstract idea because they recite process steps (e.g., generating insurance policy rates for the identified zones, updating the zone map based on updated responses, and updating the insurance policy rates based on the updated zone map) that fall under the category of organizing human activity, namely zoning geographic regions for insurance/commercial purposes, as described above regarding claim 1.
Thus, the dependent claims do not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application) that results in the claims being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Response to Arguments
11. Applicant’s arguments filed June 17, 2026 have been fully considered.
Arguments Regarding 35 U.S.C. 112(a)
12. All prior rejections under 35 U.S.C. 112(a) have been withdrawn in response to the applicant’s claim amendments. As discussed on pages 1-5 of their remarks, the claims have been amended to remove the problematic language recited in previous claims 1 and 12.
Arguments Regarding 35 U.S.C. 101
13. Applicant’s arguments (Amendment, Pgs. 5-10) concerning the prior rejection of the claims under 35 USC §101, including supposed deficiencies in the rejection, are not persuasive for the following reasons. Under the prior and current 101 analysis under 2019 PEG, the amended claims recite and are directed to a patent ineligible abstract idea, without something significantly more, for the reasons given above after consideration of the claimed features and elements. The abstract idea has been restated herein in line with the 2019 PEG guidance and the amended claims. Applicant is directed to the above full Alice/Mayo analysis in the 101 rejection.
Additionally, on pages 6 and 7 of their remarks, the applicant argues, “These operations are not the kind of human activity (such as commercial or legal interactions, agreements, or business relations) that has been recognized as a method of organizing human activity. See MPEP § 2106.04(a)(2)(II). They are instead specific computer-implemented operations involving wireless networks, location-based services, electronic communication devices, embedded metadata, and a trained machine learning model... The focus of the amended claims is on the technical operations performed by the system or method, not on the underlying human activity of zoning.” The examiner respectfully disagrees. Specifically, the examiner notes that the recitation of technological features within the claim does not prevent the claim from reciting an abstract idea. While the examiner agrees that the claim recites additional elements that fall outside of the abstract idea, the claims recite limitations which do fall under at least one of the categories of abstract ideas defined in MPEP 2106.04(a). As noted in the 101 rejection above, the zoning of geographic regions is a common practice used for various financial and commercial purposes. For example, zoning is an important practice when determining insurance rates for various policies and determining the best location for new businesses. The claims recite limitations for engaging individuals to collect information relevant to these zoning decisions and generating zone maps. Such limitations fall under the category of organizing human activity as noted above.
Additionally, on page 7 of their remarks, the applicant argues, “First, the amended claims reflect an improvement to an existing technological process. The Specification (paragraphs [0002]-[0004]) explains that traditional zoning relies on surveys, census materials, or similar data collection mechanisms, which are difficult to conduct, hard to track, and of unverifiable accuracy or veracity, and that suboptimal zoning results can be “disastrous”, including by causing the placement of fire or police stations in suboptimal locations. The amended claims address this problem by, among other things...” The examiner respectfully disagrees. Specifically, the claims do not recite limitations that amount to a technical improvement to any of the features identified by the applicant. For example, as noted in the 101 rejection above, the claims do not provide significant technical detail regarding how the machine learning model is trained and/or implemented to provide the desired output. Rather, the claims simply states that the machine learning model is trained using various data, and that the machine learning model clusters the data points for zoning based on a similarity of the data points and a proximity of a zone to the metadata. Such limitations do not provide an indication of an improvement to the functioning of the model itself. Rather, they simply apply a generic model to implement the abstract idea on a computer. A similar argument can be made for the additional technical features recited in the claim. For example, claim 1 recites the limitation, “requiring login to a system in order to provide a response, two-factor authentication, or geolocation/geo-fencing methods to ensure the recipient is in the geographic region associated with the geolocation processing.” As noted in the 101 rejection above, the claim does not provide significant technical detail regarding how the system performs the user authentication and/or geo-fencing processes to validate the user responses. Therefore, such limitations amount to no more than merely applying generic computer-related components (e.g., a system that the user logs into) in order to verify the location metadata.
Additionally, on page 8 of their remarks, the applicant argues, “Second, the amended claims are tied to particular machines. As amended, the claims require: location-based services hardware providing at least one of GPS tracking, cellular triangulation, or cell tower identification; a wireless network; electronic communication devices of a plurality of recipients having a display component with a first graphical user interface; and a secondary electronic communication device having a display component with a second graphical user interface.” The examiner respectfully disagrees. As noted above, merely applying generic computer-related technology to perform the abstract idea does not integrate the abstract idea into a practical application. The claims do not provide any indication of an improvement to the functioning of the technologies identified by the applicant. For example, simply stating that the location metadata is identified using “at least one of global positioning system tracking, cellular triangulation, or cell tower identification” does not amount to an improvement to location tracking technology, or any other technology or technological field. Rather, this amounts to no more than merely applying at least one of various generic location tracking technologies to determine the location of the recipients and facilitate the performance of the abstract idea. In other words, the claim is not primarily directed to improved systems/methods for implementing location tracking technology. Rather, these technologies are simply used as tools to perform the abstract idea (e.g., zoning of geographic regions).
Additionally, on page 8 of their remarks, the applicant argues, “Third, the amended claims recite a specific application of a trained machine learning model. The claims specify both the training data for the machine learning model (previous communications and responses received by the system, and information about results of prior zoning) and the purpose for which that training is conducted (“to optimize and improve performance of automated zone creation”), as well as the specific operation the trained model performs (clustering the data points into zones based on similarity of the data points and proximity to the location metadata).” The examiner respectfully disagrees. As noted in the 101 rejection above, the claim does not provide significant technical detail regarding how the machine learning model is trained and/or implemented to provide the desired output. While this limitation provides detail regarding the type of data used to train the model, such detail does not functionally define how the model is trained. Similarly, simply stating that the training is performed “in order to improve performance of automated zone creation” does not provide any indication of an improvement to the functioning of machine learning model itself. Such limitations do not provide any technical detail regarding how the model is trained and/or implemented to perform the claimed functions. Rather, this simply claims the desired result of the training process. Therefore, such limitations amount to no more than merely applying generic machine learning technology to implement the abstract idea on a computer.
Additionally, on page 9 of their remarks, the applicant argues, “The amended claims recite precisely such a non-conventional and non-generic ordered combination, including… That combination is not well-understood, routine, or conventional, and the Examiner has identified no factual basis under Berkheimer v. HP Inc., 881 F.3d 1360 (Fed. Cir. 2018), to conclude that it is.” Similarly, on page 9 of their remarks, the applicant argues, “The Examiner’s contrary observation that “merely outputting/displaying data” is well-understood, routine, and conventional (Final Office Action, ¶ 10, citing OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015)) addresses only one element of the recited combination and does not address the combination as a whole.” The examiner respectfully disagrees. Specifically, it is not required for the examiner to provide Berkheimer evidence for each limitation recited in the claim. Rather, this evidence is only required when the examiner identifies a limitation as being well-understood, routine, and conventional (e.g., when identifying a limitation as reciting insignificant extra-solution activity). The examiner has not claimed that each limitation recited in the claims is well-understood, routine, and conventional. As stated in MPEP2106.07(a)(III), “At Step 2A Prong Two or Step 2B, there is no requirement for evidence to support a finding that the exception is not integrated into a practical application or that the additional elements do not amount to significantly more than the exception unless the examiner asserts that additional limitations are well-understood, routine, conventional activities in Step 2B.” Rather, this analysis has only been applied to the limitations identified above as merely reciting data outputting/displaying operations. As noted in the 101 rejection above, these limitations simply state that the message and the zone map are transmitted to be displayed on a graphical user interface. The claims provide no technical detail regarding how the message and zone map are displayed and or how the user interacts with the displayed information. Therefore, such limitations, when considered individually or in the context of the claim as a whole, amount to no more than merely displaying information.
Additionally, on page 10 of their remarks, the applicant argues, “The withdrawal of all § 103 rejections (Final Office Action, ¶ 16) and the Examiner’s express acknowledgment that no combination of prior art could be identified to teach the specific combination of recited limitations are themselves persuasive indicators that the recited combination is not well-understood, routine, or conventional.” The examiner respectfully disagrees. Specifically, the examiner notes that the lack of a prior art rejection does not necessarily indicate that the claims are eligible under 35 U.S.C. 101. As stated in MPEP2106.05(I), “Although the courts often evaluate considerations such as the conventionality of an additional element in the eligibility analysis, the search for an inventive concept should not be confused with a novelty or non-obviousness determination.” In other words, even newly discovered or novel judicial exceptions are still exceptions.
Therefore, for these reasons and the reasons given above, the rejection of these claims under 35 U.S.C. 101 is maintained.
Citation of Pertinent Prior Art
14. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Conlan (U.S. Pre-Grant Publication No. 20110264529): Describes systems and a method that relate generally to geographic tracking in the context of delivering advertisements. The system provides an improved method for managing tracking units with a map representative of a geographic area, and an improved method for monitoring deliveries within a geographic constraint.
Frasher (U.S. Patent No. 7966199): Describes a method and system for identifying geographic condition zones using claim data mapped in a geographic context. More specifically, embodiments of the invention provide a method and system for mapping filtered claim data obtained from a reimbursement provider in a geographic context, and identifying localized trends associated with a predefined condition in a geographic region.
Conclusion
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/WILLIAM D NEWLON/Examiner, Art Unit 3696
