DETAILED ACTION
This Final Office Action is responsive to the claims filed on February 25, 2026.
Claims 1-6, 11, 17, and 19-34 are pending. Claims 11 and 17 are withdrawn. Claims 11, 17, and 20 are withdrawn.
Claims 1-6, 19, and 21-34 are rejected under 35 USC 112(b).
Claims 1-6, 11, 17, and 19-34 are rejected under 35 USC 101.
Responses To Arguments/Amendments
35 USC 101: The Applicant’s arguments and amendments have been considered but are not persuasive. The Applicant’s arguments will be addressed in the order presented in the Applicant’s response.
The Alleged Practical Integration: The Applicant states that amended claim 1 produces data using machine learning, receives selections from a headset, and show a simulation on the headset based on the determined data. The machine learning is recited at a high level and does not contain any improvement to machine learning technology. All AI elements are being used in their ordinary way defined by the names of the generic networks. Natural language processing models process language. Deep Learning Image Analysis models analyze images, e.g., from videos. AR goggles have long been configured to receive user input and responsively display scenarios. These are longstanding practices, and the claim provides no improvements to them. The claim provides no unconventional arrangements of these elements.
Step 2A, Prong 1: The Applicant states that the claim cannot be entirely performed in the mind. This was not the assertion of the details rejections of the prior Office Action. The Applicant has ignored the characterizations presented in the Office Action of different elements as abstract ideas and additional limitations that fail to confer eligibility under the MPEP. The Applicant has, accordingly, failed to demonstrate that those sections of the MPEP do not apply. Further, the Applicant did not specifically dispute the Office Action’s characterization of the elements identified as abstract ideas. Consequently, the Applicant has failed to make a prima facie case demonstrating integration into a practical application at Step 2A, Prong 2.
The Applicant then compares the claim to Example 45 claims 2-4. The extent to which these examples are still valid in light of recent decisions, including Recentive, is in question. However, even if, arguendo, example 45 is still valid, the Applicant’s analogy to the claims of the instant application is flawed. The controller in the example does not merely display data but modifies the operation of the mold to affect a physical transformation. Contrary to the assertions of the Applicant, displaying data on a headset does not represent a physical change, nor does it represent a transformation that the courts recognize as an integration into a practical application.
Further, the Applicant correctly asserts that the MPEP does not require an improvement to a computer and that an improvement to any technology can qualify if it meets the judicial threshold. The Applicant also correctly asserts that agricultural simulation is a part of a technical field. However, the Applicant concedes by omission that this claim does not represent such an improvement. The Applicant has not demonstrated support in the specification for such an improvement and has also failed to explicitly incorporate this improvement into the claim. Also, the Applicant has failed to demonstrate how the additional limitations (the ones the Applicant ignored in the analysis) integrate the abstract ideas into a practical application. Accordingly, the claims are directed to the abstract idea.
Specific elements of the amended claim 1 allegedly apply the method in a meaningful way and allegedly help the claim as a whole be more than a drafting effort designed to monopolize a judicial exception: The Applicant makes a blank assertion that elements of the claim help the claim as a whole be more than a drafting effort designed to monopolize a judicial exception, but the Applicant fails to specify what those elements are and how they help the claim be more than the aforementioned drafting effort.
With regard to the “non-transitory” language exclusion, transmitted signals per se can be products of computer programs. The Applicant attempts to rely on the specification for the exclusion of signals per se, but the claim must explicitly recite that the media are non-transitory or a valid alternative (e.g., a memory device).
35 USC 102/3: The Applicant’s arguments and amendments have been considered and are persuasive. Accordingly, the art rejections have been withdrawn.
Request For Rejoinder: There are still outstanding issues that must be addressed by amendment, so rejoinder of withdrawn claims is improper at this time.
Election/Restrictions
The independent claims are not yet allowable, so the withdrawn dependent claims will not currently be rejoined.
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.
Ineligible Subject Matter
Claims 1-6, 19, 21-23, and 28-34 are directed to an abstract idea without significantly more.
Independent Claims
Claim 28 (Statutory Category – Machine)
Step 2A – Prong 1: Judicial Exception Recited?
Yes, the claims recite a mental process and a mathematical concept, which are abstract ideas.
Claim 28 recites (Claim language in bold italic)
applying [analysis] to the data to produce the initial configuration data set, the applying of the [analysis] comprising (i) [text analysis] to the news and reports and (ii) […] image analysis of the video; (Mental Evaluation, Mental Process – applying analysis to data specific to the data type (e.g., watching a video or reading the news) to generate a dataset can be practically performed in the mind or with aid of pen, paper, and/or a calculator. For example, one could read news and watch videos and assign descriptive keywords for the content and property data.)
configuring [a simulation] in an initial configuration based on the initial configuration data set; (Mental Evaluation, Mental Process – Setting up a simulation can be performed in the mind or with aid of pen, paper, and/or a calculator. For example, one could write down a game board with paper pieces on a sheet of paper that mimics a real world environment.)
running the [simulation] starting in the initial configuration and simulating actions and/or conditions to obtain a simulated end configuration for the organism area, with the simulation including simulation of the first natural force and the changed first influencing parameter (Mental Evaluation, Mental Process – Running a simulation can be performed in the mind or with aid of pen, paper, and/or a calculator. For example, one could envision in the mind how a scenario would play out in the context of the simulation or one could act it out with paper dolls on a paper simulation environment.)
performing […] analysis on the simulated end configuration to obtain a first recommendation for improving the organism area. (Mental Evaluation, Mental Process – Analyzing a simulation can be performed in the mind or with aid of pen, paper, and/or a calculator. For example, one could envision in the mind how a scenario would play out and how to improve circumstances for another simulation or even to be tried in the real world!)
Claim 28 recites mental processes, which are abstract elements of an abstract idea.
Claim 28 recites an abstract idea.
Step 2A – Prong 2: Integrated into a Practical Application?
No.
The Additional limitations:
A computer system (CS) comprising:
a processor set;
one or more computer-readable storage media; and
program instructions stored on the one or more computer-readable storage media for execution by the processor set to perform operations comprising: […]
[…] a/the simulator […]
[…] artificial intelligence […]
[…] applying machine learning […] natural language processing […] deep learning […]
[…] reality eyewear […]
wherein the simulation of the first natural force and the simulated end configuration are presented via the reality eyewear;
These are generic computing elements recited at a high level and operating for their ordinary purposes. The hardware, including the reality eyewear, are used in their most generic sense for generic purposes without specific improvements thereto. The machine learning, artificial intelligence, natural language processing, and deep learning image analysis are used for the same purposes they always are without any specific modification for improvement. Accordingly, under MPEP 2106.05(f), these elements fail to integrate the abstract idea into a practical application at Step 2A, Prong 2.
producing an initial configuration data set for an organism area, with the initial configuration data set including (i) information on location, size, and color of organisms in the organism area, (ii) organism area-specific natural forces, and (iii) organism-area specific influencing parameters, wherein the producing comprises: gathering, via (i) video of an image feed of the organism area and (ii) via news and reports tracking, data regarding the organism area; and
receiving […], a selection of (i) a first natural force of the organism area-specific natural forces and (iii) a first influencing parameter;
receiving a change of a degree of the first influencing parameter […]
The producing and receiving steps are mere data gathering activity similar to the MPEP 2106.05(g) insignificant extra-solution activity examples: “e.g., a step of obtaining information about credit card transactions, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps in order to detect whether the transactions were fraudulent.” “iv. Obtaining information about transactions using the Internet to verify credit card transactions” “vi. Determining the level of a biomarker in blood” “iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display.” Because the steps are insignificant extra-solution activity, under MPEP 2106.05(g), the steps fail to integrate the abstract idea into a practical application at Step 2A, Prong 2.
Also, any specific details about the parameters the data recited represent, the parameters merely limit the abstract idea to a particular technological environment and, under MPEP 2106.05(h), fail to integrate the abstract idea into a practical application at Step 2A, Prong 2.
The additional limitations recited in claim 28 fail to integrate the abstract idea into a practical application at Step 2A, Prong 2.
Claim 28 is directed to the Abstract idea.
Step 2B: Claim provides an Inventive Concept?
No.
The additional limitations:
A computer system (CS) comprising:
a processor set;
one or more computer-readable storage media; and
program instructions stored on the one or more computer-readable storage media for execution by the processor set to perform operations comprising: […]
[…] a/the simulator […]
[…] artificial intelligence […]
[…] applying machine learning […] natural language processing […] deep learning […]
[…] reality eyewear […]
wherein the simulation of the first natural force and the simulated end configuration are presented via the reality eyewear;
These are generic computing elements recited at a high level and operating for their ordinary purposes. The hardware, including the reality eyewear, are used in their most generic sense for generic purposes without specific improvements thereto. The machine learning, artificial intelligence, natural language processing, and deep learning image analysis are used for the same purposes they always are without any specific modification for improvement. These are generic computing elements recited a high level of generality and, under MPEP 2106.05(f), fail to combine with other elements of the claim to provide significantly more that would confer an inventive concept at Step 2B.
producing an initial configuration data set for an organism area, with the initial configuration data set including (i) information on location, size, and color of organisms in the organism area, (ii) organism area-specific natural forces, and (iii) organism-area specific influencing parameters, wherein the producing comprises: gathering, via (i) video of an image feed of the organism area and (ii) via news and reports tracking, data regarding the organism area; and
receiving […], a selection of (i) a first natural force of the organism area-specific natural forces and (iii) a first influencing parameter;
receiving a change of a degree of the first influencing parameter […]
The producing and receiving steps are well-understood, routine, and conventional activity similar to the MPEP 2106.05(d) examples: “i. Receiving or transmitting data over a network,” “iii. Electronic recordkeeping” “iv. Storing and retrieving information in memory” “i. Determining the level of a biomarker in blood by any means” (sensors) “vi. Arranging a hierarchy of groups, sorting information, eliminating less restrictive pricing information and determining the price.” Because the receiving step is WURC and, as previously demonstrated, insignificant extra-solution activity, under MPEP 2106.05(d) and MPEP 2106.05(g), the steps fail to combine with other elements of the claim to provide significantly more that would confer an inventive concept at Step 2B.
Also, any specific details about the parameters the data recited represent, the parameters merely limit the abstract idea to a particular technological environment and, under MPEP 2106.05(h), fail to combine with other elements of the claim to provide significantly more that would confer an inventive concept at Step 2B.
The additional limitations fail to combine with other elements of the claim to provide significantly more that would confer an inventive concept at Step 2B.
Claim 28 is ineligible.
Claim 1
Claim 1 (Statutory Category – Process)
Claim 1 substantially recites the method performed by the system of claim 28 and is rejected for at least the same reasons as claim 28.
Claim 1 is ineligible.
Claim 21
Claim 21 (Statutory Category – NONE, but treated here as if amended to be a machine)
Claim 21 substantially recites the method performed by and, potentially, the memory on which the instructions for the method is stored in the system of claim 28 and is rejected for at least the same reasons as claim 28.
Claim 21 is ineligible.
Dependent Claims
The dependent claims fail to provide any additional limitations that would confer eligibility at Step 2A, Prong 2 and Step 2B.
NOTE: For all of the dependent claims, the parameters the data represents merely limit the abstract idea to a particular technological field and fail to confer eligibility under MPEP 2106.05(g). Also, all recited computing elements or the use thereof are recited at a high level of generality and represent generic computing processes, so, under MPEP 2106.05(f), these fail to confer eligibility.
Claims 2, 22, and 29
re-running the simulator with the first recommendation to check whether the first recommendation is likely to work successfully.
Rerunning a simulation with a modification is an evaluation practically performable in the mind or with the aid of pen, paper, and/or a calculator. Therefore, this is a mental process, an abstract element that merges with the abstract idea of the claims from which this claim depends.
Claims 2, 22, and 29 fail to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claims 2, 22, and 19 are ineligible.
Claims 3 and 23
sending the first recommendation to a device of a farmer who farms the organism area.
This is transmission of data is similar to the MPEP 2106.05(g) insignificant extra-solution activity examples: “e.g., a step of obtaining information about credit card transactions, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps in order to detect whether the transactions were fraudulent.” “iv. Obtaining information about transactions using the Internet to verify credit card transactions” “vi. Determining the level of a biomarker in blood” “iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display.” This step is insignificant extra-solution activity and, under MPEP 2106.05(g), fails to integrate the abstract idea into a practical application at Step 2A, Prong 2.
This transmission of data is also well-understood, routine, and conventional (WURC) activity similar to the MPEP 2106.05(d) examples: “i. Receiving or transmitting data over a network,” “iii. Electronic recordkeeping” “iv. Storing and retrieving information in memory” “i. Determining the level of a biomarker in blood by any means” (sensors) “vi. Arranging a hierarchy of groups, sorting information, eliminating less restrictive pricing information and determining the price.” Because the obtain and receive steps are WURC and, as previously demonstrated, insignificant extra-solution activity, under MPEP 2106.05(d) and MPEP 2106.05(g), the steps fail to combine with other elements of the claim to provide significantly more that would confer an inventive concept at Step 2B.
Claims 3 and 23 fail to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claims 3 and 23 are ineligible.
Claims 4 and 24
implementing the first recommendation [[of]] in the organism area.
Implementing a recommendation in a simulation is an evaluation practically performable in the mind or with aid of pen, paper, and a calculator. For example, the person can run a paper simulation of an adjusted watering or feeding schedule based on lessons from running a prior simulation.
Claims 4 and 24 fail to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claims 4 and 24 are ineligible.
Claims 5 and 25
wherein the organism area comprises an agricultural crop area that includes at least one member selected from a group consisting of: food plants, textile material plants, pharmaceutical plants and industrial use plants.
This merely limits the abstract idea to a particular field of technology (e.g., agriculture), which under MPEP 2106.05(h) fails to confer eligibility at Step 2A, Prong 2, and Step 2B.
Claims 5 and 25 fail to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claims 5 and 25 are ineligible.
Claims 6 and 26
wherein the first natural force comprises a damaging natural force selected from a group consisting of: fire, flood, earthquake, tsunami, solar radiation, other radiation from natural sources, ice, snow, insects, worms, wild animals, magnetic forces, pollen, natural chemicals and tidal forces.
This merely limits the abstract idea to a particular field of technology (e.g., agriculture), which under MPEP 2106.05(h) fails to confer eligibility at Step 2A, Prong 2, and Step 2B.
Claims 6 and 26 fail to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claims 6 and 26 are ineligible.
Claims 19 and 30
wherein the organisms comprise agricultural crops.
This merely limits the abstract idea to a particular field of technology (e.g., agriculture), which under MPEP 2106.05(h) fails to confer eligibility at Step 2A, Prong 2, and Step 2B.
Claims 19, 27, and 30 fail to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claims 19, 27, and 30 are ineligible.
Claim 20
NOTE: This claim is expected to be canceled but will be treated anyway in the interest of compact prosecution.
wherein the organisms include at least one of livestock and trees.
wherein the organisms comprise agricultural crops.
This merely limits the abstract idea to a particular field of technology (e.g., agriculture), which under MPEP 2106.05(h) fails to confer eligibility at Step 2A, Prong 2, and Step 2B.
Claim 20 fails to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claim 20 is ineligible.
Claim 31
wherein the first natural force is selected from a consisting of fire, flood, earthquake, tsunami, and tidal forces.
These features merely limit the abstract idea to a particular field and, under MPEP 2106.05(h).
Claim 31 fails to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claim 31 is ineligible.
Claim 32
wherein the initial configuration data set further includes a group of influencing parameters that influence the organism area and the producing the initial configuration data set further includes identifying, via historical learning, a most influential parameter of the group of influencing parameters, wherein the group of influencing parameters includes the first influencing parameter.
Historical learning is not a term of art. No definition has been provided in the claim. Therefore, this can be any type of learning from history. For example, reading a book that says a parameter is the most meaningful is historical learning. This is practically performable in the mind or with the aid of pen and paper, so it is an evaluation, a mental process, an abstract idea.
The nature of the data identified merely limits the abstract idea to a particular technological field, and, under MPEP 2106.05(h), fails to confer eligibility.
Claim 32 fails to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claim 32 is ineligible.
Claim 33
wherein the producing the initial configuration data set further includes gathering data from Internet-of-Things (IoT) sensors in the organism area.
This is mere data gathering and is ineligible for the same reasons as the receiving and producing steps.
Claim 33 fails to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claim 33 is ineligible.
Claim 34
Wherein the first recommendation comprises cultivating a first crop instead of a second crop in the organism area.
This merely limits the abstract idea to a particular field, which under MPEP 2106.05(h), fails to confer eligibility.
Claim 34 fails to provide additional limitations that confer eligibility at Step 2A, Prong 2 and Step 2B.
Claim 34 is ineligible.
Allowance Over Art
The claims are allowable over the prior art of record. The claims recite,
[…]
applying machine learning to the data to produce the initial configuration data set, the applying of the machine learning comprising (i) natural language processing to the news and reports and (ii) applying deep learning image analysis of the video:
configuring a simulator in an initial configuration based on the initial configuration data set, wherein the initial configuration is presented to a user via reality eyewear;
receiving, via the reality eyewear, a selection of (i) a first natural force of the organism area-specific natural forces and (ii) a first influencing parameter:
receiving a change of a degree of the first influencing parameter via the reality eyewear:
running the simulator starting in the initial configuration and simulating actions and/or conditions to obtain a simulated end configuration for the organism area, with the simulation including simulation of the first natural force and the changed first influencing parameter, wherein the simulation of the first natural force and the simulated end configuration are presented via the reality eyewear; and
performing artificial intelligence analysis on the simulated end configuration to obtain a first recommendation for improving the organism area.
The Monteiro reference of record teaches simulating a horticultural setup using a digital twin of the horticultural setup and machine learning by ingesting sensor data and controlling the environment of the horticultural setup based on the simulation.
The Pyliandris reference of record teaches simulating the effects of natural disasters to crops using digital twins and machine learning.
A search revealed a Xi reference made of record that teaches using AR, including headsets, to manage agriculture. It also teaches using weather data and video data as inputs to the simulation.
The search further revealed a Lin reference made of record that discloses multimodal/vision-language machine learning models.
However, the prior art fails to teach the application of machine learning to vision and language multimodal data including natural language processing of news and reports and image processing of video of the organism area to generate initial configuration data for a simulation that is presented via an AR headset and responsively receive user input of a natural force specific to the organism area and an influencing parameter from the headset for use as input in the simulation that simulates the organism area under the conditions specified in the input received from the reality eyewear to obtain an end configuration, then displaying the simulation and the end configuration on the reality eyewear and performing artificial intelligence analysis on the simulated end configuration to obtain a recommendation on improving the organism area, without the use of impermissible hindsight.
Accordingly, the claims are allowable over the art.
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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2023/0022508 A1 to Howell et al. (Teaches an agricultural digital twin with sensors and when to use pesticides)
NPL: The Applicant is directed to the various examples of studies and corresponding references in the Pylianidis reference collected in Table 3 on Pages 5-13. (Teaches all of the features of the claims several times over)
NPL: “A digital twin for smart farming” by Alves et al. (Teaches another digital twin farming system)
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/J.M.W./
Examiner, Art Unit 2188
/RYAN F PITARO/Supervisory Patent Examiner, Art Unit 2188