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 .
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.
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) 2-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Achen et al. (9,814,172) in view of Redden (2015/0027040).
Regarding claim 2, Achen et al. discloses a computer implemented method of causing automatic adjustments to down pressure on a soil engaging tool of an agricultural row unit, comprising the steps of:
Receiving a measurement from one or more sensors coupled to one or more soil engaging tools of an agricultural row unit of an agricultural planter, the measurement being related to a compaction or density of soil (column 14 lines 47-50)
Providing a representation of the sensor measurement to detect a soil type and adjusting the device based on changes in the soil type (column 9 line 66 through column 10 line 6)
Repeating the steps of receiving and providing to acquire data over time to establish or adjust a maximum or minimum value associated with the data and comparing the acquired data with data from known sample (column 9 line 66 through column 10 line 6)
Responsive to the repeating, causing an automatic adjustment to a downward pressure on the agricultural planter or the soil engaging tool (column 14 lines 56-60)
While Achen discloses the invention as described above and further mentions “intelligent control” but it fails to specifically disclose utilizing machine learning for detecting the soil type and automatically making adjustments (column 15 lines 19-23). Like Achen, Redden also discloses a soil engaging tool that utilizes sensors for monitoring soil properties and making automatic adjustments based on the sensor readings and known data samples. Unlike Achen, Redden discloses the use of machine learning to make adjustments based on classifiers (pgph 0032). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize machine learning that utilizes classifiers based on historical data in Achen as taught by Redden to adjust the downforce based on sensor readings as the use of a known technique to improve similar devices in the same way (KSR International Co. v. Teleflex Inc., 550 USPQ2d 1385 (2007)).
Regarding claim 3, the combination disclose that the automatic adjustment includes increasing or decreasing a downforce applied to the soil engaging tool (column 14 lines 56-60).
Regarding claim 4, the combination discloses determining/checking whether adjustments need to be made and making the adjustments in response to sensor readings/measurements.
Regarding claim 5, the combination discloses that the setpoint parameter includes a seed depth, a row cleaner depth or force, a down pressure gauge wheel load target or a closing wheel pressure or depth (column 15 lines 37-40).
Regarding claim 6, the combination discloses that the soil type includes soil or sand, the machine learning system makes the inference using a hardness of a furrow formed by the tool of the row unit (column 4 lines 5-10; column 9 lines 16-20).
Regarding claim 7, the combination discloses that the soil engaging tool is a gauge wheel () and wherein the one or more sensors includes a furrow hardness sensor (, the method further comprising the step of, responsive to the receiving the measurement, adjusting a gauge wheel load target including increasing the gauge wheel load target response to the furrow hardness sensor being low and decreasing the gauge wheel load target responsive to the furrow hardness sensor being high (Column 8 lines 36-42; column 9 lines 1-19)
Regarding claim 8, the combination discloses that the soil engaging tool is a closing wheel (118).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Plymill et al. (2016/0378086) discloses utilizing sensors and machine learning in precision agriculture.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jamie L McGowan whose telephone number is (571)272-5064. The examiner can normally be reached Monday through Friday 9:00-5:00 CST.
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/JAMIE L MCGOWAN/Primary Examiner, Art Unit 3671
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