CTFR 18/767,653 CTFR 83391 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. DETAILED ACTION This action is in response to communications filed on 2/12/2026. Claims 1, 5-7, 9-10, 16 & 18-19 have been amended. No other claims have been amended, added, or canceled. Accordingly, claims 1- 20 are pending. Response to Arguments Applicant’s arguments with respect to claim(s) 1- 20 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. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim s 1- 20 are rejected under 35 U.S.C. 103 as being unpatentable over WO 2023021005A1 (hereinafter 005) in view of Carpenter et al. (hereinafter Carpenter, US 2016/0237640 A1) . As per claim 1, 005 discloses: an agricultural system comprising: a sensor system communicably coupled to and remotely positionable from an agricultural work machine at a worksite, the sensor system (see 005 at least fig. 1-4 and Abstract; optical sensor [6] aim at area cultivated by harvester ) configured to: detect one or more job quality attributes in a measurement area at least partially behind the agricultural work machine, relative to a travel direction of the agricultural work machine, and generate sensor data indicative of the detected one or more job quality attributes (see 005 at least fig. 1-4 and Abstract; optical sensor [6] aim at area cultivated by harvester ) ; one or more processors; and memory storing instructions, executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to: obtain the sensor data indicative of the detected one or more job quality attributes (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10] ) ; determine job quality corresponding to the agricultural work machine based on the obtained sensor data indicative of the detected one or more job quality attributes (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10], optimizing component settings, value of lost grains ) ; and control the agricultural system based on the determined job quality (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10], optimizing component settings, value of lost grains ) . 005 discloses the invention as detailed above. However, 005 does not appear to explicitly disclose wherein the sensor system is remotely positioned from the work machine and that the remotely positioned sensor provides control instructions to the work machine. Nevertheless, the use of remotely positioned sensor systems used for monitoring and controlling work machines were well known to one of ordinary skill in the art prior to the effective filing date of the given invention as is evident by the disclosure of Carpenter (see Carpenter at least fig. 7 & 12 and Abstract and ¶75-79; drone [25] monitoring the path and productivity of the work equipment [1]) . One of ordinary skill in the art prior to the effective filing date of the given invention would have been motivated to combine 005’s method for evaluating operation parameters of an agricultural device with those of Carpenter’s use of a drone in order to ensure an optimal and efficient progress in a work area (i.e., by utilizing the drone to help with enabling real-time assessments to optimal production/productivity). Motivation to combine 005 with Carpenter not only comes from knowledge well known in the art but also from 854 (see Carpenter at least fig. 7 & 12 and ¶75-79) . Both 005 and Carpenter disclose claim 2: wherein the agricultural work machine comprises an agricultural harvester and wherein the one or more job quality attributes comprise one or more attributes of material expelled by the agricultural harvester (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 3: wherein the agricultural work machine comprises an agricultural tillage machine and wherein the one or more job quality attributes comprise one or more attributes of ground over which the agricultural tillage machine has passed (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 4: wherein the sensor system is disposed on a drone, communicably coupled to the agricultural work machine (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 5: wherein the computer executable instructions, when executed by the one or more processors, further cause the one or more processors to: generate a travel plan for the drone, the travel plan including a monitoring location defining a location to position the drone to have the sensor system, disposed on the drone, detect the one or more job quality attributes; and control the drone based on the travel plan (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 6: wherein the computer executable instructions, when executed by the one or more processors, further cause the one or more processors to: identify one or more characteristics of an obstruction at a worksite, the one or more characteristics comprising one or more of a location of the obstruction or a future location of the obstruction; and generate the travel plan based, at least in part, on the identified one or more characteristics of the obstruction (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 7: wherein the computer executable instructions, when executed by the one or more processors, further cause the one or more processors to: identify the monitoring location, based, at least in part, on the identified one or more characteristics of the obstruction, the identified monitoring location defining a location to position the drone such that the obstruction does not obstruct the sensor system from detecting the one or more job quality attributes (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 8: wherein the obstruction comprises one of a debris cloud or a component of the agricultural work machine (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and 854 disclose claim 9: wherein the control signal controls a controllable subsystem of the agricultural work machine (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 10: a computer implemented method comprising: controlling positioning of a drone relative to an agricultural work machine (see 005 at least fig. 1-4 and Abstract; and see Carpenter at least fig. 7 & 12 and ¶75-79) ; detecting, with a sensor system disposed on the drone, one or more job quality attributes in a measurement area at least partially behind the agricultural work machine, relative to a travel direction of the agricultural work machine (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10] ) ; generating, with the sensor system, sensor data indicative of the detected one or more job quality attributes (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10], optimizing component settings, value of lost grains ) ; determining job quality corresponding to the agricultural work machine based on the sensor data indicative of the detected one or more job quality attributes (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10], optimizing component settings, value of lost grains ) ; and generating a control signal based on the determined job quality (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10], optimizing component settings, value of lost grains ) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 11: wherein detecting, with the sensor system disposed on the drone, one or more job quality attributes comprises detecting, with the sensor system disposed on the drone, one or more attributes of material expelled by the agricultural work machine (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 12: wherein detecting, with the sensor system disposed on the drone, one or more job quality attributes comprises detecting, with the sensor system disposed on the drone, one or more attributes of ground over which the agricultural work machine has passed (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 13: generating a travel plan for the drone, the travel plan including a monitoring location defining a location to position the drone to have the sensor system, disposed on the drone, detect the one or more job quality attributes; and controlling the drone based on the travel plan (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 14: wherein generating the travel plan comprises: identifying one or more characteristics of an obstruction at a worksite, the one or more characteristics comprising one or more of a location of the obstruction or a future location of the obstruction; and generating the travel plan based, at least in part, on the identified one or more characteristics of the obstruction (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 15: wherein generating the travel plan based, at least in part, on the identified one or more characteristics of the obstruction comprises: identify the monitoring location, based, at least in part, on the identified one or more characteristics of the obstruction, the identified monitoring location defining a location to position the drone such that the obstruction does not obstruct the sensor system from detecting the one or more job quality attributes (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 16: wherein generating the control signal comprises generating the control signal to control a controllable subsystem of the agricultural work machine (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and see Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 17: an agricultural system comprising: a sensor system disposed on a drone communicably coupled to and remotely positionable from an agricultural work machine at a worksite, the sensor system configured to detect one or more job quality attributes in a measurement area at least partially behind the agricultural work machine, relative to a travel direction of the agricultural work machine, and generate sensor data indicative of the detected one or more job quality attributes (see 005 at least fig. 1-4 and Abstract; ; optical sensor [6] aim at area cultivated by harvester; and see Carpenter at least fig. 7 & 12 and ¶75-79) ; one or more processors (see 005 at least fig. 1-4 and Abstract; controller [108] ) ; and memory storing instructions, executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to: generate a travel plan for the drone, the travel plan including a monitoring location defining a location to position the drone to have the sensor system, disposed on the drone, detect the one or more job quality attributes (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10], optimizing component settings, value of lost grains ) ; control the drone based on the travel plan (see 005 at least fig. 1-4 and Abstract; and 854 at least fig. 1 and Abstract) ; obtain the sensor data indicative of the detected one or more one or more job quality attributes (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10] ) ; determine job quality corresponding to the agricultural work machine based on the obtained sensor data indicative of the detected one or more job quality attributes (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10], optimizing component settings, value of lost grains ) ; and generate a control signal based on the determined job quality (see 005 at least fig. 1-4 and Abstract; assessing operating quality of the agricultural harvesting device, image evaluation [10], optimizing component settings, value of lost grains ) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 18: wherein the computer executable instructions, when executed by the one or more processors, further cause the one or more processors to: identify one or more characteristics of an obstruction at a worksite, the one or more characteristics comprising one or more of a location of the obstruction or a future location of the obstruction; and generate the travel plan based, at least in part, on the identified one or more characteristics of the obstruction (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and see Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 19: wherein the computer executable instructions, when executed by the one or more processors, further cause the one or more processors to: identify the monitoring location, based, at least in part, on the identified one or more characteristics of the obstruction, the identified monitoring location defining a location to position the drone such that the obstruction does not obstruct the sensor system from detecting the one or more job quality attributes (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and see Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Both 005 and Carpenter disclose claim 20: wherein the control signal controls a controllable subsystem of the agricultural work machine (see 005 at least fig. 1- 4 & Abstract; harvesting machine; and see Carpenter at least fig. 7 & 12 and ¶75-79) . One of ordinary skill in the art would have been motivated to combine 005 and Carpenter, in the instant claim, for the same reasoning and/or rationale as presented above with respect to claim 1. Conclusion 07-40-01 Applicant's submission of an information disclosure statement under 37 CFR 1.97(c) with the timing fee set forth in 37 CFR 1.17(p) on 6/5/2026 prompted the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL . See MPEP § 609.04(b). 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. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MACEEH ANWARI whose telephone number is (571)272-7591. The examiner can normally be reached 9 am-9:30 pm. 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, Angela Ortiz can be reached at 5722721206. 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. MACEEH . ANWARI Primary Examiner Art Unit 3663 /MACEEH ANWARI/Primary Examiner, Art Unit 3663 Application/Control Number: 18/767,653 Page 2 Art Unit: 3663 Application/Control Number: 18/767,653 Page 3 Art Unit: 3663 Application/Control Number: 18/767,653 Page 4 Art Unit: 3663 Application/Control Number: 18/767,653 Page 5 Art Unit: 3663 Application/Control Number: 18/767,653 Page 6 Art Unit: 3663 Application/Control Number: 18/767,653 Page 7 Art Unit: 3663 Application/Control Number: 18/767,653 Page 8 Art Unit: 3663 Application/Control Number: 18/767,653 Page 9 Art Unit: 3663 Application/Control Number: 18/767,653 Page 10 Art Unit: 3663 Application/Control Number: 18/767,653 Page 11 Art Unit: 3663
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