DETAILED ACTION
Final Rejection
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 Amendment
Applicant’s amendments, filed 03/30/2026 to claims are accepted. In this amendment, claims 1, 3-8 and 10-12 have been amended.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 3 recites the limitation "the neural network" in line 1. There is insufficient antecedent basis for this limitation in the claim.
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, 3-8 and 10-12 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Each of claims1, 3-8 and 10-12 falls within one of the four statutory categories. See MPEP § 2106.03. For example, each of claims 1 and 3-8 fall within category of process; For example, each of claim 10-12 falls within category of machine, i.e., a “concrete thing, consisting of parts, or of certain devices and combination of devices.” Digitech, 758 F.3d at 1348–49, 111 USPQ2d at 1719 (quoting Burr v. Duryee, 68 U.S. 531, 570, 17 L. Ed. 650, 657 (1863));
Regarding Claims 1-11
Step 2A – Prong 1
Exemplary claim 1 is directed to an abstract idea of a value of a primary signal.
The abstract idea is set forth or described by the following italicized limitations:
1. A method of generating a synthetic sensor for providing a geophysical measurement comprising:
receiving a plurality of secondary signals from a plurality of secondary sensors;
downloading a trained learning model on a processor enabled device,
wherein the trained learning model is configured to transform the plurality of secondary signals into a value of a primary signal for the geophysical measurement,
wherein the trained learning model is trained by obtaining a measured value of the primary signal for the geophysical measurement from at least one primary sensor and training the trained learning model by modeling the plurality of secondary signals to the measured value of the primary signal of the geophysical measurement;
gnal for displaying on the processor enabled device..
The italicized limitations above represent a mental step (i.e., a process that can be performed by can be performed mentally and/or with pen and paper or a mental judgment) . Therefore, the italicized limitations fall within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance.
For example, the limitations “generating a synthetic sensor for providing a geophysical measurement [..];transform the plurality of secondary signals into a value of a primary signal for the geophysical measurement ” are a combination of mathematical concepts and mental steps (i.e., a process that can be performed by can be performed mentally and/or with pen and paper or a mental judgment) (see [0046], [0076])
Limitations are considered together as a single abstract idea for further analysis. (discussing Bilski v. Kappos, 561 U.S. 593 (2010)).
Step 2A – Prong 2
Claims 1 does not include additional elements (when considered individually, as an ordered combination, and/or within the claim as a whole) that are sufficient to integrate the abstract idea into a practical application.
For example, first additional first element is “receiving a plurality of secondary signals from a plurality of secondary sensors; downloading a trained learning model on a processor enabled device, wherein the trained learning model is trained by obtaining a measured value of the primary signal for the geophysical measurement from at least one primary sensor and training the trained learning model by modeling the plurality of secondary signals to the measured value of the primary signal of the geophysical measurement” to be performed, at least in-part, these additional elements appear to only add insignificant extra-solution activity (e.g. ,field of use and/or data gathering) and only generally link the abstract idea to a particular field. Therefore, this element individually or as a whole does not provide a practical application. See MPEP 2106.05(g)
The 2nd additional element of “learning model” in limitations are at best mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept and it is recited a computer component at a high level of generality. In view of the above, the “additional element” individually or combine does not provide a practical application of the abstract idea. See MPEP 2106.05(f).
For example, first additional first element is “transforming the plurality of secondary signals into the value of the primary signal for displaying on the processor enabled device ” to be performed, at least in-part, these additional elements appear to only add post solution activity (e.g. ,field of use and/or data display) and only generally link the abstract idea to a particular field. Therefore, this element individually or as a whole does not provide a practical application. See MPEP 2106.05(g)
In view of the above, the three “additional elements” individually do not provide a practical application of the abstract idea. Furthermore, the “additional elements” in combination amount to a plurality of generic data collection system with computer component with software, where such computers and software amount to mere instructions to implement the abstract idea on a computer(s) and/or mere use of a generic computer component(s) as a tool to perform the abstract idea. Therefore, these elements in combination do not provide a practical application. The combination of additional elements does no more than generally link the use of the abstract idea to a particular technological environment, and for this additional reason, the combination of additional elements does not provide a practical application of the abstract idea.
.
Step 2B
Claims1 does not include additional elements, when considered individually and as an ordered combination, that are sufficient to amount to significantly more than the abstract idea. For example, the limitation of Claim 1 contains additional elements that are, i.e. sensors, display”, generic devices, which are well understood, routine and conventional (see background of current discloser and IDS and PTO 892) and MPEP 2106.05(d))The reasons for reaching this conclusion are substantially the same as the reasons given above in § Step 2A – Prong 2. For brevity only, those reasons are not repeated in this section. See MPEP §§ 2106.05(g) and MPEP §§2106.05(II).
.
Dependent Claims3-8
Dependent claims 3-8 fail to cure this deficiency of independent claim 1 (set forth above) and are rejected accordingly. Particularly, claims 2-9 recite limitations that represent (in addition to the limitations already noted above) either the abstract idea or an additional element that is merely extra-solution activity, mere use of instructions and/or generic computer component(s) as a tool to implement the abstract idea, and/or merely limits the abstract idea to a particular technological environment.
Fore examples,
Claims 4-8 : these additional elements appear to only add insignificant extra-solution activity (e.g., data gathering) and only generally link the abstract idea to a particular field.
Claim 3: mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept and it is recited a computer component at a high level of generality. In view of the above, the “additional element” individually or combine does not provide a practical application of the abstract idea. See MPEP 2106.05(f).
Regarding Claims 10-12
Claims 10-12 contains language similar to claims 1, 3-8 as discussed in the preceding paragraphs, and for reasons similar to those discussed above, claims 10-12 are also rejected under 35 U.S.C. § 101(abstract idea).
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.
Claim(s) 1, 3-8 and 10-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larsen(US 2024/0341248) in view of Davis (US 2021/0264252).
Regarding Claims 1 and 10. Larsen teaches a method of generating a synthetic sensor for providing a geophysical measurement comprising(abstract; 230: fig. 2; generate a prediction value for soil moisture levels: [0055]):
receiving a plurality of secondary signals from a plurality of secondary sensors([0012]);
a trained learning model on a processor enabled device(352: fig. 3), wherein the trained learning model is configured to transform the plurality of secondary signals (sensors: [0012]; data from the weather, the remote moisture flow sensors: [0038]) into a value of a primary signal (predictive soil moisture: [0012]) for the geophysical measurement([0012], [0038],[0053], [0078], [0101]),
wherein the trained learning model (346: fig.3; [0068])is trained by obtaining a measured value of the primary signal for the geophysical measurement from at least one primary sensor and training the trained learning model by modeling the plurality of secondary signals to the measured value of the primary signal of the geophysical measurement(330: fig. 3; [0061], [0065]-[0068], [0105]-[0106]);
transforming the plurality of secondary signals into the value of the primary signal for displaying([0035]) on the processor enabled device(fig. 4; watering actions the system intends to make based on the prediction system: [0070]; fig. 8; [0097]-[0098]).
Larsen silent about downloading a trained learning model on a processor enabled device.
However, Davis teaches downloading a trained learning model (0062: fig. 1)on a processor enabled device(the software solution database 58 may be updated (e.g., neural network algorithms or other algorithms may be iteratively trained: [0038]; If the software solution assumes the form of a neural network algorithm or other algorithm that is relatively large in file size, the controller architecture 32 may download the software solution request to the local memory: [0049]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Larsen, downloading a trained learning model on a processor enabled device, as taught by Davis, so as to optimal-fit software solution may be availed to a particular network-connected work machine 14.
Regarding Claim 3. Larsen further teaches the neural network is a recurrent neural network that is used to create the trained learning model that models a relationship between the plurality of secondary signals and the measured value of the primary signal([0095]-[0096], [0101], [0105]-[0106]).
Regarding Claim 4. Larsen further teaches the trained learning model( 346: fig.3; [0068]) is trained using secondary signals from at least five secondary sensors (330: fig. 3; the data from the weather, the remote moisture flow sensors: [0038]; [0061], [0065]-[0068], [0105]-[0106]).
Regarding Claims 5 and 11. Larsen further teaches the value of the primary signal is a sensor other than the plurality of secondary sensors(the remote soil moisture sensors: [0038]; [0007], [0012], [0060], [0063], [0065], [0105]-[0106]).
Regarding Claims 6 and 12. Larsen further teaches the primary signal replaces one of the plurality of secondary signals (collect and/or maintain the data from the weather, the remote moisture flow sensors, and/or the remote soil moisture sensors: [0038], [0060][0076]).
Regarding Claim 7. Larsen further teaches obtaining at least one historical environmental data value; and predicting a future value of the primary signal based on the at least one historical environmental data value(abstract; [0031], [0037]; round truth soil moisture level: [0053]-[0054]; [0105])
Regarding Claim 8. Larsen further teaches the at least one historical environmental data value is weather data(abstract).
Response to Argument
Applicant’s arguments with respect 101 rejection, specially claims 1 and 34, The applicant did not agree with it., see, pages 6-8
In response, the Examiner respectfully disagree because limitations of claim 1 represent a combination of mathematical concepts (i.e., a process that can be performed by mathematical relationships or rules or idea) and a mental step (i.e., a process that can be performed by can be performed mentally and/or with pen and paper). Therefore, the italicized limitations above fall within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance. In view of the above, the three “additional elements” individually do not provide a practical application of the abstract idea. Furthermore, the “additional elements” in combination amount to a plurality of generic control system with computer component with software, where such computers and software amount to mere instructions to implement the abstract idea on a computer(s) and/or mere use of a generic computer component(s) as a tool to perform the abstract idea. Therefore, these elements in combination do not provide a practical application. The combination of additional elements does no more than generally link the use of the abstract idea to a particular technological environment, and for this additional reason, the combination of additional elements does not provide a practical application of the abstract idea.. The combination of additional elements does no more than generally link the use of the abstract idea to a particular technological environment, and for this additional reason, the combination of additional elements does not provide a practical application of the abstract idea. see the rejection above. Furthermore, See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer and the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. Furthermore, this additional element is” transforming the plurality of secondary signals into the value of the primary signal for displaying on the processor enabled device” to be performed, at least in-part, by use of a an output apparatus configured to output information relating to the result, which is conventional and generic technology. See, ELECTRIC POWER GROUP, LLC v. ALSTOM S.A., where Court cites “Two of our decisions that rejected § 101 challenges are materially different from this case. The claims at issue here do not require an arguably inventive device or technique for displaying information, unlike the claims at issue in DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1257 (Fed. Cir. 2014) (at JMOL stage finding inventive concept in modification of conventional mechanics behind website display to produce dual-source integrated hybrid display). Nor do the claims here require an arguably inventive distribution of functionality within a network, thus distinguishing the claims at issue from those in Bascom, 2016 WL 3514158, at *6 (at pleading stage finding sufficient inventive concept in “the installation of a filtering tool at a specific location, remote from the endusers, with customizable filtering features specific to each end user”). The claims in this case specify what information in the power-grid field it is desirable to gather, analyze, and display, including in “real time”; but they do not include any requirement for performing the claimed functions of gathering, analyzing, and displaying in real time by use of anything but entirely conventional, generic technology. The claims therefore do not state an arguably inventive concept in the realm of application of the information- based abstract ideas.” And a an post solution activity well known in the particular industry As such 1o1 is maintained.
Applicant’s arguments with respect to claim(s) 1, and 10 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
a) Oak. et al. (US 2022/0124964) disclose Systems and methods for virtual agronomic sensing are provided. In embodiments methods comprise receiving first agronomic data for a first geographic location comprising sensor data from agronomic sensors at the first geographic location; receiving first agronomic information for the first geographic location; and generating first predictive agronomic data for the first geographic location using the first agronomic data for the first geographic location and the first agronomic information for the first geographic location. Methods may further comprise testing the first predictive agronomic data for the first geographic location to be used for a second geographic location; receiving second agronomic information for the second geographic location; generating virtual agronomic sensors for the second geographic location as a function of the testing the first predictive agronomic data for the first geographic location; and providing second predictive agronomic data for the second geographic location using the virtual agronomic sensors.
b) Van et al. (US 2021/0140908) disclose a soil moisture and fertility sensor system is presented that includes an elongated probe having a plurality of sensor modules positioned along the length of the probe. Each sensor module includes a co-located sensors configured to take a moisture, temperature, and fertility measurements at varying depths of the soil. The probe is configured for wireless communication. The probe is configured to take moisture measurements, temperature measurements and/or nutrient measurements at different times so as to prevent interference between measurements. The probe includes a plurality of receptacles that receive the fertility sensor assembly cartridge that may be inserted into and removed from a receptacle so as to facilitate end-of-life replacement. In one arrangement, the fertility sensor assembly includes a reference sensor and a plurality of nutrient sensors that are each configured to sense the presence of a specific nutrient.
c) Casas et al. (US 2020/0184214) disclose a computer-implemented method for predicting subfield soil properties for an agricultural field comprises: receiving satellite remote sensing data that includes a plurality of images capturing imagery of an agricultural field in a plurality of optical domains; receiving a plurality of environmental characteristics for the agricultural field; generating a plurality of preprocessed images based on the plurality of satellite remote sensing data and the plurality of environmental characteristics; identifying, based on the plurality preprocessed images, a plurality of features of the agricultural field; generating a subfield soil property prediction for the agricultural field by executing one or more machine learning models on the plurality of features; transmitting the subfield soil property prediction to an agricultural computer system.
D) Chandra et al. (US 2019/0331832) disclose A method can include receiving sensor data from at least three different types of sensor situated in the geographic area, the types of sensors including an air temperature sensor, relative humidity sensor, dewpoint sensor, soil moisture sensor, soil temperature sensor, average wind speed sensor, maximum wind speed sensor, and a rainfall sensor, producing a feature vector including a time series of values corresponding to the received sensor data, and using a neural network, estimating the physical characteristics, the physical characteristics including at least one of (a) a leaf wetness, (b) a solar radiation, (c) an evapotranspiration, (d) a future soil moisture, and (e) a future soil temperature.
E) US 20200356898: the mobile device 301 may request and download the appropriate trained classifier or model. With the trained classifier or model loaded, the operator may start the diagnosis or tuning of the machine. Sensor of the mobile device 301 may generate sensor data 309 based on the operation of the machine.
F) US 20200202167: A neural network request based on the sensor data is send to a server. In response to the request, a neural network is downloaded from the server. Image data or video data is collected at the vehicle, and an analysis of the image data or video data using the neural network downloaded from the server is performed.
Contact information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMAD K ISLAM whose telephone number is (571)270-0328. The examiner can normally be reached M-F 9:00 a.m. - 5:00 p.m..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A Turner can be reached at 571-272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMMAD K ISLAM/Primary Examiner, Art Unit 2857
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