DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments with respect to the prior art rejection are fully persuasive however a new rejection with the Vandike reference (a common inventor to this application) follows below.
Applicant’s arguments (page 12) with respect to the 101 rejection are not persuasive. Applicant argues that if a seemingly conventional washing machine is outside the realm of abstract ideas that a cotton harvesting system would be as well. Applicant further notes the recent Ex Parte Desjardins et all decision.
The examiner notes that the structural elements (communication system, in-situ sensor, processor and data store) in and of themselves are conventional well understood and routine elements and aren’t the abstract idea identified, rather the abstract idea is the predictive model and predictive map of the worksite.
The examiner suggests positively claiming a control of the system such as that in claims 2, 14 and 20 to overcome the 101 rejection.
A new examiner has taken over for the prior examiner.
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, 3-13 and 15-19 are rejected under 35 U.S.C. 101, because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Independent claim 1 is directed toward a system, claim 13 is directed toward a method, and claim 19 is directed toward a system. Therefore, each of the independent claims 1, 13,19 along with the corresponding dependent claims 1, 13,19 are directed to a statutory category of invention under step 1.
Step 2A, Prong 1
Under Step 2A, Prong 1, the claims are analyzed to determine whether one or more of the claims recites subject matter that falls within one of the following groups of abstract ideas: (1) mental processes, (2) certain methods of organizing human activity, and/or (3) mathematical concepts. In this case, the independent claims 1, 13,19 are directed to an abstract idea without significantly more. Specifically, the claims, under their broadest reasonable interpretation cover certain mental processes. The language of independent claim 1 is used for illustration:
A cotton harvesting system comprising: a communication system configured to receive an information map that includes values of a characteristic corresponding to different geographic locations in a worksite at which a cotton harvester performs an operation; an in-situ sensor configured to detect a value of feedrate corresponding to a geographic location in the worksite; one or more processors; and a data store configured to store computer executable instructions that, when executed by the one or more processors, are configured to configure the one or more processors to: (Pre solution insufficient activity);
generate a predictive model that models a relationship between values of the characteristic and values of feedrate based on a value of the characteristic in the information map at the geographic location and the value of feedrate detected (A person could mentally observe and process data information);
by the in-situ sensor corresponding to the geographic location; and generate a functional predictive map of the worksite, that maps predictive values of feedrate to the different geographic locations in the worksite, based on the values of the characteristic in the information map and based on the predictive model. (Post solution insufficient activity);
As explained above, independent claim 1 recites at least one abstract idea. The other independent claims 13 and 19 which are of a similar scope to claim 1 likewise recite at least one abstract idea under Step 2A, Prong 1.
Step 2A, Prong 2
Under Step 2A, Prong 2, the claims are analyzed to determine whether the claim, as a whole, integrates the abstract idea into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements such as merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application”; see at least MPEP 2106.04(d)
In this case, the mental processes judicial exception is/are not integrated into a practical application. For example, independent claims 1, 13,19 recite the additional elements of a communication system, an in-situ sensor, cotton harvesting system. These limitations amount to implementing the abstract idea on a computer, add insignificant extra solution activity, and/or generally link use of the judicial exception to a particular technological environment or field of use; see at least MPEP 2106.04(d). More specifically,
one or more processing devices… This limitation amounts to implementing the abstract idea on a computer
data storage medium… This limitation amounts to implementing the abstract idea on a computer
database… This limitation amounts to implementing the abstract idea on a computer
receiving a plurality of measure values… This limitation amounts to implementing the abstract idea on a computer
Therefore, taken alone, the additional elements do not integrate the abstract idea into a practical application. Furthermore, looking at the additional limitation(s) as an ordered combination or as a whole, the limitations add nothing significant that is not already present when looking at the elements taken individually. Because the additional elements, do not integrate the abstract idea into a practical application by imposing meaningful limits on practicing the abstract idea, independent claims 1, 13, 18 are directed to an abstract idea.
Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a vehicle controller to perform the evaluating… amounts to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “one or more processing devices” “data storage medium” “database” “receiving a plurality of measure values…,” the examiner submits that these limitations are insignificant extra-solution activities.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well understood, routine, conventional activity in the field. The additional limitations of “one or more processing devices” “data storage medium” “database” “receiving a plurality of measure values…,” are well-understood, routine, and conventional activities because the background recites that the sensors are all conventional sensors mounted on the vehicle, and the specification does not provide any indication that the vehicle controller is anything other than a conventional computer within a vehicle. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner. The Federal Circuit in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere displaying of data is a well understood, routine, and conventional function. Hence, the claim is not patent eligible
The respective dependent claims, with the exception of claims 2, 14 and claim 20 are similarly rejected because they do not contain limitations which render them patent eligible under 101. Claims 2, 14 and 20 recite an affirmative control signal based on the predictive map.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
The applied reference has a common inventor with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2). This rejection under 35 U.S.C. 102(a)(2) might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C. 102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B) if the same invention is not being claimed; or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed in the reference and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement.
Claim(s) 1-5, 7-9, 13-14 and 19-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US 2022/0110255 A1 to Vandike et al.
Regarding claim 1, Vandike discloses a cotton harvesting system (0031) comprising:
a communication system 206 configured to receive an information map that includes values of a characteristic corresponding to different geographic locations in a worksite at which a cotton harvester performs an operation (0047, the harvester 100 receives an information map; 0155 shows a map with multiple regions)
an in-situ sensor 208 configured to detect a value of feedrate corresponding to a geographic location in the worksite (0047, 0064 discloses controlling a fed rate for different regions of a map such as if there’s a section with weeds).;
one or more processors; anda data store configured to store computer executable instructions that, when executed by the one or more processors (0046, processor/server 201 and data store 202), are configured to configure the one or more processors to
:generate a predictive model that models a relationship between values of the characteristic and values of feedrate based on a value of the characteristic in the information map at the geographic location and the value of feedrate detected by the in-situ sensor corresponding to the geographic location (0064);and generate a functional predictive map of the worksite, that maps predictive values of feedrate to the different geographic locations in the worksite, based on the values of the characteristic in the information map and based on the predictive model (0064, Settings controller 232 can generate control signals to control various settings on the agricultural harvester 100 based upon predictive map 264, the predictive control zone map 265, or both. For instance, settings controller 232 can generate control signals to control machine and header actuators 248.… Feed rate controller 236 can control various subsystems, such as propulsion subsystem 250 and machine actuators 248, to control a feed rate based upon the predictive map 264 or predictive control zone map 265 or both. For instance, as agricultural harvester 100 approaches a weed patch having an intensity value above a selected threshold, feed rate controller 236 may reduce the speed of machine 100 to maintain constant feed rate of biomass through the machine.)
Regarding claim 2, see the discussion of Vandike paragraph 0064 as discussed above which discloses: the cotton harvesting system of claim 1, wherein the computer executable instructions, when executed by the one or more processors, are further configured to configure the one or more processors to: generate a control signal to control a controllable subsystem of the cotton harvester based on the functional predictive map.
Regarding claim 3, the limitations of: wherein the information map comprises a vegetative index map that maps, as the values of the characteristic, vegetative index values to the different geographic locations in the worksite, and wherein the predictive model models a relationship between vegetative index values and values of feedrate based on the value of feedrate detected by the in-situ sensor corresponding to the geographic location and the vegetative index value, in the vegetative index map, at the geographic location, the predictive model being configured to receive a vegetative index value as a model input and generate a value of feedrate as a model output based on the identified relationship between vegetative index values and values of federate, are met by the prior discussion of paragraph 0064 as it can maintain a constant feed rate that is maintained by changing the speed of the machine 400, changing speed means that it has a different stored rate in order to maintain a constant output. Further see paragraph 0051( For example, if the information map 258 maps a vegetative index value to different locations in the field, and the in-situ sensor 208 is sensing a value indicative of crop flow, then information variable-to-in-situ variable model generator 228 generates a predictive model that models the relationship between the vegetative index value and the crop flow value. The predictive model can also be generated based on vegetative index values from the information map 258 and multiple in-situ data values generated by in-situ sensors 208. Then, predictive map generator 212 uses the predictive model generated by predictive model generator 210 to generate a functional predictive map 263 that predicts the value of a crop flow sensed by the in-situ sensors 208 at different locations in the field based upon the information map 258.Further at 0064, the predictive map 264 is used to determine feed rate)
Regarding claim 4, see Vandike paragraph 0056-0059, further at 0064 the feed rate is performed based on the predictive map which discloses:
wherein the information map comprises a yield map that maps, as the values of the characteristic, yield values to the different geographic locations in the worksite, and wherein the predictive model models a relationship between yield values and values of feedrate based on the value of feedrate detected by the in-situ sensor corresponding to the geographic location and the yield value, in the yield map, at the geographic location, the predictive model being configured to receive a yield value as a model input and generate a value of feedrate as a model output based on the identified relationship between yield values and values of feedrate.
Regarding claim 5, at 0060, Vandike discloses the use of a weed intensity map generated during a prior operation such as from a srprayer which is part of the predictive map 264, at 0064 the feed rate is performed based on the predictive map and thus teaches:
wherein the information map comprises a prior product application operation map that maps, as the values of the characteristic, prior product application operation characteristic values to the different geographic locations in the worksite, and wherein the predictive model models a relationship between prior product application operation characteristic values and values of feedrate based on the value of feedrate detected by the in-situ sensor corresponding to the geographic location and the prior product application operation characteristic value, in the prior product application operation map, at the geographic location, the predictive model being configured to receive a prior product application operation characteristic value as a model input and generate a value of feedrate as a model output based on the identified relationship between prior product application operation characteristic values and values of feedrate.
Regarding claim 7, see Vandike paragaphs 0043-0044 and 0109 which deal with moisture levels for the soil as part of the predictive map 264 and thus teach wherein the information map comprises a soil moisture map that maps, as the values of the characteristic, soil moisture values to the different geographic locations in the worksite, and wherein the predictive model models a relationship between soil moisture values and values of feedrate based on the value of feedrate detected by the in-situ sensor corresponding to the geographic location and the soil moisture value, in the soil moisture map, at the geographic location, the predictive model being configured to receive a soil moisture value as a model input and generate a value of feedrate as a model output based on the identified relationship between soil moisture values and values of feedrate.
Regarding claim 8, see the discussion of predictive map 264 in combination of soil type map at 0027 and thus Vandike teaches:
wherein the information map comprises a soil type map that maps, as the values of the characteristic, soil type values to the different geographic locations in the worksite, and wherein the predictive model models a relationship between soil type values and values of feedrate based on the value of feedrate detected by the in-situ sensor corresponding to the geographic location and the soil type value, in the soil type map, at the geographic location, the predictive model being configured to receive a soil type value as a model input and generate a value of feedrate as a model output based on the identified relationship between soil type values and values of feedrate.
Regarding claims 13-14 and 19-20 see claims 1-2 as addressed above.
Allowable Subject Matter
Claims 6, 10-12, 15-18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims should the 101 rejection be overcome.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUNTER B LONSBERRY whose telephone number is (571)272-7298. The examiner can normally be reached M-F 8:00-5:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, TC Director James Trammell can be reached at 571-272-6712. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
HUNTER B. LONSBERRY
Supervisory Patent Examiner
Art Unit 3665
/HUNTER B LONSBERRY/Supervisory Patent Examiner, Art Unit 3665
Prosecution Insights