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 .
Notice to Applicant
The following is a Final Office Action for Application Serial Number: 18/153,213, filed on November 11, 2023. In response to Examiner’s Non-Final Rejection dated February 27, 2025, Applicant on August 27, 2025, amended claims 1, 4, 12, 15 and 20, cancelled claims 3 and 14 and added new claims 21 and 22. Claims 1, 2, 4-13 and 15-22 are pending in this application and have been rejected below.
Response to Amendment
Applicant's amendments are acknowledged.
Regarding the 35 U.S.C. 101 rejection, Applicants arguments and amendments have been considered but are insufficient to overcome the rejection.
The 35 U.S.C. § 103 rejections are hereby withdrawn in light of Applicants amendments to claims 1, 12 and 20.
Response to Arguments
Applicant's Arguments/Remarks filed August 27, 2025 (hereinafter Applicant Remarks) have been fully considered but are not persuasive. Applicant’s Remarks will be addressed herein below in the order in which they appear in the response filed August 27, 2025.
Regarding the 35 U.S.C. 101 rejection, Applicant states claim 1 includes features that cannot be practically performed in the human mind, such as:
generating a first set of features for a first span of the first set of spans, the first set of features including a type of a first road of the first set of roads that is nearest to the first span feature, a distance from the first span to the first road feature, and an intersection feature that indicates whether a vector from the first span to the first road intersects a building of the first set of buildings; providing the first set of features to a first set of trained decision trees to generate a first predicted trim device for the first span;
Applicant's specification states "[i]n one example, the trim device prediction module 208 utilizes a random forest machine learning algorithm to train a set of decision trees and provides the sets of features to the set of trained decision trees to generate predicted trim devices for trimming vegetation around different electrical assets." Specification at [0053]. Decision trees may be trained on random subsets of data so that each decision tree may be less correlated with other decision trees. The combination of weakly correlated trees may give a more reliable prediction. The human mind is not equipped to utilize trained decision trees, such as those trained by a random forest machine learning algorithm to process features and make a prediction, to predict a trim device. Therefore, the above features of claim 1 cannot practically be performed in the human mind. For at least these reasons claim 1 does not recite a "mental process" that the Supreme Court has identified as an abstract idea. Claims 12 and 20 recite generally similar features as claim 1 and therefore also do not recite a mental process. Therefore, claims 1, 12, and 20 do not recite an abstract idea.
In response, Examiner respectfully disagrees. Examiner finds Applicants remarks are directed to limitations that recite both abstract and additional elements (i.e. trained decision trees to generate a first predicted trim device for the first span), and therefore were not analyzed under Step 2A-Prong One. Examiner finds receiving a first geographic area, the first geographic area including one or more first feeders of one or more first electrical power distribution infrastructures; receiving a first set of roads for the first geographic area, receiving a first set of spans for the first geographic area, a span of the first set of spans electrically connected to a feeder of the one or more first feeders of the one or more first electrical power distribution infrastructures; receiving a first set of buildings for the first geographic area; generating a first set of features for a first span of the first set of spans, the first set of features including a type of a first road of the first set of roads that is nearest to the first span feature, a distance from the first span to the first road feature, and an intersection feature that indicates whether a vector from the first span to the first road intersects a building of the first set of buildings; generate a first predicted trim device for the first span; and generating and providing a first report, the first report including the first predicted trim device for the first span recites an abstract ideas of predicting trim devices for geographical areas, which Examiner maintains constitutes methods that mimic human thought processes that can be performed mentally by a combination of the human mind and a human using pen and paper, such as observations, evaluations, judgements and/or opinion. Furthermore, Examiner maintains, the aforementioned additional elements (i.e., trained decision trees) do not take the claim out of the mental processes grouping.
Regarding the 35 U.S.C. 101 rejection, Applicant states as discussed in Applicant's specification, the claimed technology provides predictions of trim devices to be used to trim vegetation proximate to electrical assets. Specification at [0034]. Various embodiments correct problems caused by previous approaches or technologies. Id. at [0036]. For example, such embodiments allow for personnel of utilities and their contractors to have a high degree of confidence that the trim devices delivered to a job site are both the appropriate trim devices and the appropriate number of trim devices. Id. Moreover, various embodiments may allow for reductions in the occurrences of fires and/or impacts of fires because utilities and their contractors are more likely to have the appropriate equipment for managing vegetation near electrical assets. Id. at [0037]. These are practical applications that are enabled by the features of claim 1. Accordingly, claim 1 recites meaningful additional features that integrate the alleged judicial exception into a practical application that is also an improvement to computer technology. Claims 12 and 20 recite generally similar features that also integrate the alleged judicial exceptions into practical applications.
In response, Examiner respectfully disagrees. Examiner notes the advancements disclosed in RCT v. Microsoft, Diamond v. Diehr and SiRF Technology v. ITC recite improvements to the functioning of a computer, or an improvement to another technology or technical field. Specifically, in RCT v. Microsoft, the claims are directed to a process of halftoning an image comprising the steps of generating a mask, comparing pixels, and using the results of the comparison to convert a binary image to a halftoned image. The process uses less memory, had faster computation times, and processed improved image quality compared to other masks, Diamond v. Diehr utilized the Arrhenius equation to improve the process of controlling the operations of a mold in curing rubber parts, and SiRF Technology v. ITC disclosed a GPS receiver utilizing software that applies a mathematical formula to improve the ability to determine its position in weak environments. In contrast, Examiner finds there are no similar improvements here. Examiner finds Applicant’s arguments are directed to improvements to an existing business process (e.g. predictions of trim devices to be used to trim vegetation proximate to electrical assets). Examiner maintains the amended claims are directed to an abstract idea, reciting mental processes without providing meaningful limitations that integrates the abstract idea into a practical application.
Regarding the 35 U.S.C. 101 rejection, Applicant states Applicant's claims recite significantly more than the alleged abstract idea. As noted above, claim 1 recites "receiving a first geographic area, the first geographic area including one or more first feeders of one or more first electrical power distribution infrastructures; receiving a first set of roads for the first geographic area; receiving a first set of spans for the first geographic area, a span of the first set of spans electrically connected to a feeder of the one or more first feeders of the one or more first electrical power distribution infrastructures; receiving a first set of buildings for the first geographic area; generating a first set of features for a first span of the first set of spans, the first set of features including a type of a first road of the first set of roads that is nearest to the first span feature, a distance from the first span to the first road feature, and an intersection feature that indicates whether a vector from the first span to the first road intersects a building of the first set of buildings; providing the first set of features to a first set of trained decision trees to generate a first predicted trim device for the first span; and generating and providing a first report, the first report including the first predicted trim device for the first span." These additional features are neither well-known, routine nor conventional in the art, and are outside the scope of the alleged abstract idea. As Applicant's specification at para. [0003] notes, manual examination of electrical assets and the vegetation proximate thereto is impractical. Applicant's technology provides technical solutions to the technical problem of how to determine a trim device for a span connected to a feeder of one or more electrical power distribution infrastructures. The features of claim 1 are directed towards these technical solutions. Accordingly, claim 1 integrates the alleged judicial exception into a practical application and provides significantly more. Claims 12 and 20, which recite generally similar features, also integrate the alleged judicial exceptions into practical applications and provide significantly more.
In response, Examiner respectfully disagrees. Examiner respectfully notes, the analysis in Step 2B addresses the question on whether an additional element (or combination of additional elements) represents well-understood, routine and/or conventional activities. Examiner finds Applicant is again, attempting to say the Step 2A-Prong One elements, the abstract idea, is what makes the claim eligible. Applicant has provided no detailed explanation to the configuration of the combination of additional elements nor has Applicant identified any disclosure in the claimed invention showing and/or submitting that the technology used is being improved, there was a technical problem in the technology that the claimed invention solves, or the ordered combinations of the known elements is significantly more than the abstract idea. Examiner maintains the additional elements recited in the claims do not perform any unconventional functions that can be considered “significantly more” than the judicial exception. Therefore, Examiner maintains the claims recite addition elements used as tools to perform the instructions of the abstract idea without disclosing limitations that integrates the abstract idea into a practical application, nor do these elements provide meaningful limitations that transforms the judicial exception into significantly more than the abstract idea itself.
Regarding the 35 U.S.C. 101 rejection of claim 6, Applicant recites limitations of claim 6 and argues Example 39 (see par. 17, Applicant Remarks). Applicant states Example 39 to the 2019 PEG states that "the claim does not recite a mental process because the steps are not practically performed in the human mind." 2019 PEG, Subject Matter Eligibility Examples: Abstract Ideas, p. 9 This example claim was found eligible under Step 2A - Prong 1. Id. The "generating" features of claim 6 are analogous to the "creating" features of the example claim, and the "utilizing" features of claim 6 are analogous to the "training" features of the example claim. Because the example claim is patent eligible, claim 6 is also patent eligible. Accordingly, dependent claim 6 does not recite an abstract idea.
For at least these reasons, and for its dependency upon independent claim 1, dependent claim 6 is not directed to a judicial exception under Pathway B and thus qualifies as eligible subject matter under 35 U.S.C. § 101.
For at least the reasons set forth herein, the Applicant respectfully requests that the
rejections of claims 1, 2, 4-13, and 15-20 under 35 U.S.C.§ 101 be withdrawn. Claims 3 and 14 have been canceled, and accordingly, the 35 U.S.C.§ 101 rejections of these claims are now moot.
In response, Examiner respectfully disagrees. Example 39 improves the computer technology for identifying human faces in digital images, which is not similar to the present invention. Taking the claim elements separately and in combination, the functions performed by the additional elements are purely conventional. Specifically, unlike Example 39 that was found to improve the training process of a neural network, the present invention merely confines the use of the abstract idea to a particular technological environment (i.e., trained decision trees) and fails to add an inventive concept to the claims. See MPEP 2106.05(h). For at least these reasons the claims remain rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
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.
Step 1: The claimed subject matter falls within the four statutory categories of patentable subject matter.
Claims 1, 2, 4-11 and 21 are directed towards a non-transitory computer-readable medium, claims 12, 13, 15-19 and 22 are directed towards a system and claim 20 is directed towards a method, which are among the statutory categories of invention.
Step 2A – Prong One: The claims recite an abstract idea.
Claims 1, 2, 4-13 and 15-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite predicting trim devices for geographical areas.
Claim 1 recites limitations directed to an abstract idea based on mental processes. Specifically, receiving a first geographic area, the first geographic area including one or more first feeders of one or more first electrical power distribution infrastructures; receiving a first set of roads for the first geographic area, receiving a first set of spans for the first geographic area, a span of the first set of spans electrically connected to a feeder of the one or more first feeders of the one or more first electrical power distribution infrastructures; receiving a first set of buildings for the first geographic area; generating a first set of features for a first span of the first set of spans, the first set of features including a type of a first road of the first set of roads that is nearest to the first span feature, a distance from the first span to the first road feature, and an intersection feature that indicates whether a vector from the first span to the first road intersects a building of the first set of buildings; generate a first predicted trim device for the first span; and generating and providing a first report, the first report including the first predicted trim device for the first span, wherein the first set of features further includes a building density feature, and further comprising: determining an area of a feeder region that includes a first feeder of the one or more first feeders to which the first span is electrically connected, the feeder region further including multiple buildings, a building having an area; obtaining a total building area based on the areas of the multiple buildings in the feeder region; and generating the building density feature based on the total building area and the area of the feeder region constitutes methods based on observations, evaluations, judgements and/or opinion that can be performed by a combination of the human mind and a human using pen and paper. The recitation of a non-transitory computer-readable medium comprising executable instructions by processors and trained decision trees to does not take the claim out of the mental processes grouping. Thus the claim recites an abstract idea. Claims 12 and 20 recite mental processes for similar reasons as claim 1.
Step 2A – Prong Two: The judicial exception is not integrated into a practical application.
The judicial exception is not integrated into a practical application. In particular, claim 1 recites a non-transitory computer-readable medium comprising executable instructions by processors at a high-level of generality such that it amounts to no more than generic computer components used as tools to apply the instructions of the abstract idea; see MPEP 2106.05(f). Additionally, claim 1 recites providing the first set of features to a first set of trained decision trees to generate a first predicted trim device for the first span. The general use of a machine learning technique does not provide a meaningful limitation to transform the abstract idea into a practical application. Therefore, providing the first set of features to a first set of trained decision trees is considered to be an insignificant extra-solution activity of collecting and delivering data; see MPEP 2106.05(g) and the set of trained decision trees disclosed in the claims are solely used as a tool to perform the instructions of the abstract idea; see MPEP 2106.05(f). Thus, the additional elements do not integrate the abstract idea into practical application because it does not impose any meaningful limitations on practicing the abstract idea. Claim 1 as a whole, looking at the additional elements individually and in combination, does not integrate the judicial exception into a practical application and therefore is directed to an abstract idea. The system comprising memory containing executable instructions by the at least one processor recited in claim 12 and method in claim 20 also amount to no more than tools to perform the instructions of the abstract idea; see MPEP 2106.05(f). Thus, the additional elements recited in claims 12 and 20 do not integrate the abstract idea into practical application for similar reasons as claim 1.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements in the claims other than the abstract idea per se, including a non-transitory computer-readable medium comprising executable instructions by processors and system comprising memory containing executable instructions by the at least one processor amount to no more than a recitation of generic computer elements utilized to perform generic computer functions, such as receiving or transmitting data over a network, e.g., using the Internet to gather data, buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); and storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; see MPEP 2106.05(d)(II). The machine learning technique recited in the claim (i.e., trained decision trees) are disclosed at a high-level of generality (see par. 0053) and does not amount to significantly more than the abstract idea. Viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Therefore, since there are no limitations in the claim that transform the abstract idea into a patent eligible application such that the claim amounts to significantly more than the abstract idea itself, the claims are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
§ 101 Analysis of the dependent claims.
Regarding the dependent claims, claims 21 and 22 recite receiving the first set of buildings for the first geographic area includes receiving a first set of polygons from one or more data sources, which is considered an insignificant extra-solution activities of collecting and delivering data; see MPEP 2106.05(g). Claims 2, 6, 7, 9, 11, 13, 17 and 18 recites recite limitations utilizing a trained sets of decision trees, which solely uses a machine learning technique as a tool to perform the instructions of the abstract idea; MPEP 2106.05(f). Additionally, claims 2, 4-11, 13, 15-19, 21 and 22 recite steps that further narrow the abstract idea. No additional elements are disclosed in the dependent claims that were not considered in the independent claims. Therefore claims 2, 4-11, 13, 15-19, 21 and 22 do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself.
Distinguishable over the Prior Art of Record
The prior art rejections of the amended claims are removed in light of Applicant’s Amendments and Remarks filed August 27, 2025, in particular pg. 19-21 regarding the prior art of record. Examiner analyzed amended claim 1 in view of the prior art on record and finds not all claim limitations are explicitly taught nor would one of ordinary skill in the art find it obvious to combine references with a reasonable expectation of success.
Terrazas (US 20140270355 A1) teaches estimating demography based on aerial images (see par. 0001). Specifically, Terrazas discloses an example density calculator that analyzes an aerial image (e.g., using image analysis techniques) to detect objects and/or determine characteristics of the geographic area. For example, the object detector may detect objects and/or determine characteristics based on the aerial image based on shapes, colors, and/or boundaries in the image. The example density calculator may determine a density of one or more objects in the aerial image (see par. 0055). The density calculator calculates a density of the buildings (e.g., a number of buildings and/or an area occupied by the buildings per unit area) and/or calculates a density of the green space (e.g., a number of distinct green spaces separated by non-green spaces and/or an amount of green space per unit area) of an aerial image (see par. 0046). The density calculator may calculate and compare the density of the buildings in different geographic areas (see par. 0047).
However, Terrazas, both individually or in combination with the prior art of record, does not explicitly teach the combination of claim limitations as a whole as recited in independent claim 1. Thus, claim is found to be distinguishable over the prior art. Claims 12 and 20 are distinguishable over the prior art for similar reasons as cited for claim 1. Dependent claims 2, 4-11, 13, 15-19, 21 and 22 are distinguishable because it depends on claims 1 and 12 respectively.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Crain et al. (US 20140368378 A1) – The system is capable of conjoint use of image data developed by these and other scanning apparatus to form a model of a zone. In some versions, the model includes subsurface image information. Methods for use to scan and for implementation of images and models developed by the scan are also disclosed.
Cruickshank III (US 20210296897 A1) – A method, system and apparatus are provided for optimized load shaping for optimizing production and consumption of energy. Information signals indicative of a first load shape signal are obtained corresponding to a total load, a renewable energy load of one or more renewable energy sources and a non-renewable energy load of one or more non-renewable energy sources. The first load shape signal corresponding to renewable energy load is removed from a non-renewable energy load to obtain a resulting load shape signal. The resulting load shape is flattened signal by apportioning the resulting load shape signal across time intervals to obtain a flattened load shape signal. At least a portion of the first component corresponding to the renewable energy load is added to the flattened load shape signal to create an optimized load shape signal.
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 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.
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/CRYSTOL STEWART/Primary Examiner, Art Unit 3624