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. DETAILED ACTION The action is in response to the Applicant’s communication filed on 12/05/2023. Claims 1-20 are pending, where claims 1 and 11 are independent. Information Disclosure Statement The information disclosure statement (IDS) submitted on 12/05/2023 has been filed on the filing date of the application. The submission is in-compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Multiple filed related applications Applicants have filed multiple related applications. To date, some of the related applications have been allowed or under NOA and it appears that some related applications are stand pending, yet to be examined. There are plurality of co-pending related Applications and double patenting is proper . See MPEP 804 and 1490 (VI) D: Nonstatutory Double Patenting The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum , 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington , 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA/25, or PTO/AIA/26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer . See MPEP § 804 and 1490 (VI) D. Claims 1 and 11 are rejected on the ground of nonstatutory double patenting over the claims 1 and 18 of USP No. 12,022,772 B2 (Appl. No. 17/248378 and Pub. No. 2022/0232770 A1). The subject matter claimed in the instant application and the patent are claiming similar subject matter, as follows: Instant Application No. 18/529,407 USP No. 12,022,772 B2 (Appl. No. 17/248378 and Pub. No. 2022/0232770 A1) Title PROACTIVE VARIABLE CONTROL OF HARVESTER HEADER POSITIONING Agricultural Header Control Claim 1. A system for adjusting a position of at least a portion of a header of an agricultural vehicle , the system comprising: at least one optical sensor positioned to obtain captured information of at least the header; at least one processor; a memory device coupled to the at least one processor, the memory device including instructions that when executed by the at least one processor cause the at least one processor to: classify one or more features detected in the captured information without use of fiduciary markers to identify one or more objects represented in the captured information, the one or more objects comprising at least a portion of the header ; determine, using at least the captured information, a position of at least the portion of the header relative to at least one attribute of an upstream crop material or a ground surface of a field upon which the agricultural vehicle performs an agricultural operation; determine, for a location upstream of the agricultural vehicle, a variance in a position of at least the portion of the header relative to a position of the at least one attribute of the upstream crop material or the ground surface; determine, based on the variance, one or more adjusted control settings to adjust the position of the portion of the header relative to the position of the at least one attribute of the upstream crop material or the ground surface; and adjust, based on the one or more adjusted control settings, the position of the portion of the header before, or upon, the header being displaced to a location at which the header encounters the variance in the at least one attribute of the upstream crop material or the ground surface. 1. A computer-implemented method performed by one or more processors for controlling an agricultural header based on movement of at least one crop grain component relative to the agricultural header during harvesting , the method comprising: analyzing one or more images containing at least a portion of the agricultural header to detect at least one crop grain component detached from a crop plant present in the one or more images, wherein said portion of the agricultural header includes at least one static location and said analyzing includes detecting movement of said crop grain component relative to said static location; and categorizing the detected crop grain component detected in the one or more images ; and generating measured distribution data based on the categorized crop grain component; and adjusting a setting of the agricultural header using the measured distribution data. Claims 2- 20 are also obvious to the claims 1- 2 2 of the US Pat . No. 12,022,772B2 (Appl. No. 17/248378 and Pub. No. 2022/0232770 A1 ) . Although the conflicting claims are not identical, they are not patentably distinct from each other (as shown in the table for comparison) because they are conceptually or inherently similar to the limitations of the patent (as for example the limitation “ classify one or more features detected in the captured information without use of fiduciary markers to identify one or more objects represented in the captured information, the one or more objects comprising at least a portion of the header ” of the application is equivalent to the limitation “ categorizing the detected crop grain component detected in the one or more images ” of the patent) in scope and they use the similar limitations and produce the similar/same end result of adjusting (controlling) position header (agricultural header) of agricultural vehicle (movement). It would be therefore obvious to one having ordinary skill in the art before the effective filing date of the claimed invention was made that to modify or to omit the additional elements of claims 1, and 1 8 of the patent to arrive at the claims 1 and 1 1 of the instant application, would perform the similar functions as before. This is an obviousness-type double patenting rejection. A terminal disclaimer is required to overcome the obviousness-type double patenting rejection. See MPEP § 804 and 1490 (VI) D: 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 of this title, 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. The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness . 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 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. Claims 1-20 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Ingalls , et al. USPGPub No. 20240407285 A1 . As to claim s 1 and 11 , Ingalls discloses A system for adjusting a position of at least a portion of a header of an agricultural vehicle (Ingalls [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] “agricultural vehicle, a database, and a control system” [abstract] see Fig. 1-8) , the system comprising: at least one optical sensor positioned to obtain captured information of at least the header; at least one processor; a memory device coupled to the at least one processor, the memory device including instructions that when executed by the at least one processor cause the at least one processor to: (Ingalls [ 0027-85 ] “ height adjustment system 400 - control the operation of a header/cutting height, roll angle, and tilt angle - at least one sensor 420 - provide a signal indicating the current height and angle of the SPW header 100 - use image data collected from the sensor 420 to analyze the height of the header 100 in relation to a known reference point (e.g., a point on a vehicle associated with the header, a point on the ground, etc.) - measure position of the lifting mechanism 108 to determine the height of the header 100 ” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] [abstract] see Fig. 1-8 , plurality of sensor includes image data collected from sensor obviously provides optical sensor positioned to obtain captured information ) classify one or more features detected in the captured information without use of fiduciary markers to identify one or more objects represented in the captured information, the one or more objects comprising at least a portion of the header; (Ingalls [0027-85] “height adjustment system 400 - control the operation of a header/cutting height, roll angle, and tilt angle - at least one sensor 420 - provide a signal indicating the current height and angle of the SPW header 100 - use image data collected from the sensor 420 to analyze the height of the header 100 in relation to a known reference point (e.g., a point on a vehicle associated with the header, a point on the ground, etc.) - measure position of the lifting mechanism 108 to determine the height of the header 100 - adjusting the height of an SPW header - performed autonomously by a controller utilizing a neural network or a machine learning model - harvest a wide range of crops, including: wheat, corn, soybeans, rice, barley, oats, rye, sunflowers, canola, peanuts, cotton, lentils, flax, sorghum, and millet - adapted with different headers or attachments to harvest other crops, such as grapes, olives, and fruits - any variety of input devices - indicate which crop is to be harvested - input devices - scanner, webcam - barcode scanner ” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] “receive an indication of a crop to be harvested by the agricultural vehicle, determine at least one attribute of the crop to be harvested - adjust the parameter of the agricultural vehicle to the default setting - operate the agricultural vehicle - receive an input of a user to adjust the setting of the parameter, store the adjusted setting of the parameter as a secondary setting, and upon thereafter receiving a second indication of the crop to be harvested, display the default setting and the secondary setting ” [abstract] see Fig. 1-8 , plurality of sensor includes image data collected from sensor, receive indication of crop to be harvested, determine plurality of attribute , adjust parameter to default setting of agricultural vehicle obviously provides classify one or more features detected in the captured information without use of fiduciary markers to identify one or more objects represented in the captured information, the one or more objects comprising at least a portion of the header ) determine, using at least the captured information, a position of at least the portion of the header relative to at least one attribute of an upstream crop material or a ground surface of a field upon which the agricultural vehicle performs an agricultural operation; determine, for a location upstream of the agricultural vehicle, a variance in a position of at least the portion of the header relative to a position of the at least one attribute of the upstream crop material or the ground surface; determine, based on the variance, one or more adjusted control settings to adjust the position of the portion of the header relative to the position of the at least one attribute of the upstream crop material or the ground surface; (Ingalls [0027-85] “ height adjustment system 400 - control the operation of a header/cutting height, roll angle, and tilt angle - at least one sensor 420 - provide a signal indicating the current height and angle of the SPW header 100 - use image data collected from the sensor 420 to analyze the height of the header 100 in relation to a known reference point (e.g., a point on a vehicle associated with the header, a point on the ground, etc.) - measure position of the lifting mechanism 108 to determine the height of the header 100 - adjusting the height of an SPW header - performed autonomously by a controller utilizing a neural network or a machine learning model - harvest a wide range of crops, including: wheat, corn, soybeans, rice, barley, oats, rye, sunflowers, canola, peanuts, cotton, lentils, flax, sorghum, and millet - adapted with different headers or attachments to harvest other crops, such as grapes, olives, and fruits - any variety of input devices - indicate which crop is to be harvested - input devices - scanner, webcam - barcode scanner ” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] “receive an indication of a crop to be harvested by the agricultural vehicle, determine at least one attribute of the crop to be harvested - adjust the parameter of the agricultural vehicle to the default setting - operate the agricultural vehicle - receive an input of a user to adjust the setting of the parameter, store the adjusted setting of the parameter as a secondary setting, and upon thereafter receiving a second indication of the crop to be harvested, display the default setting and the secondary setting” [abstract] see Fig. 1-8 , plurality of sensor collect s data from sensor, receive indication of crop to be harvested, analyze the data based on known reference, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, adjust parameter to default setting of agricultural vehicle obviously determine, using at least the captured information, a position of at least the portion of the header relative to at least one attribute of an upstream crop material or a ground surface of a field upon which the agricultural vehicle performs an agricultural operation; determine, for a location upstream of the agricultural vehicle, a variance in a position of at least the portion of the header relative to a position of the at least one attribute of the upstream crop material or the ground surface; determine, based on the variance, one or more adjusted control settings to adjust the position of the portion of the header relative to the position of the at least one attribute of the upstream crop material or the ground surface ) and adjust, based on the one or more adjusted control settings, the position of the portion of the header before, or upon, the header being displaced to a location at which the header encounters the variance in the at least one attribute of the upstream crop material or the ground surface (Ingalls [0027-85] “height adjustment system 400 - control the operation of a header/cutting height, roll angle, and tilt angle - at least one sensor 420 - provide a signal indicating the current height and angle of the SPW header 100 - use image data collected from the sensor 420 to analyze the height of the header 100 in relation to a known reference point (e.g., a point on a vehicle associated with the header, a point on the ground, etc.) - measure position of the lifting mechanism 108 to determine the height of the header 100 - adjusting the height of an SPW header - performed autonomously by a controller utilizing a neural network or a machine learning model - harvest a wide range of crops, including: wheat, corn, soybeans, rice, barley, oats, rye, sunflowers, canola, peanuts, cotton, lentils, flax, sorghum, and millet - adapted with different headers or attachments to harvest other crops, such as grapes, olives, and fruits - any variety of input devices - indicate which crop is to be harvested - input devices - scanner, webcam - barcode scanner ” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] “receive an indication of a crop to be harvested by the agricultural vehicle, determine at least one attribute of the crop to be harvested - adjust the parameter of the agricultural vehicle to the default setting - operate the agricultural vehicle - receive an input of a user to adjust the setting of the parameter, store the adjusted setting of the parameter as a secondary setting, and upon thereafter receiving a second indication of the crop to be harvested, display the default setting and the secondary setting” [abstract] see Fig. 1-8, plurality of sensor includes image data collected from sensor, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, adjust parameter to default setting of agricultural vehicle obviously provides adjust, based on the one or more adjusted control settings, the position of the portion of the header before, or upon, the header being displaced to a location at which the header encounters the variance in the at least one attribute of the upstream crop material or the ground surface ) . It would be therefore obvious to one having ordinary skill in the art at the time of the invention that control system ensure s proper header height adjust ing of agricultural vehicle are assumed as header adjusting position of an agricultural vehicle . As to claim s 2 and 12 , Ingalls further d iscloses The system of claim 1, wherein the memory device further includes instructions that when executed by the at least one processor cause the at least one processor to determine, at least in part, the location upstream of the agricultural vehicle as a function of a speed of travel of the agricultural vehicle (Ingalls [0027-85] “ processor uses sensor data from sensor 420 to calculate the contours of the field - ground speed of SPW 710, reel speed, knife speed, roll tension, roll gap, etc.) - directions to adjust the SPW header 700 position in relation to both the crop 712 height and changes in elevation of the field - determine soil conditions - affect the harvesting process - parameter of the agricultural vehicle - include settings - speed of the vehicle, the height of the cutting blade, a speed of the reel, a reel gap, a reel tension, a disc speed, header position/angle, and other factors affect the efficiency and effectiveness of the harvesting process ” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] [abstract] see Fig. 1-8, plurality of sensor includes image data, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, agricultural vehicle parameter (include settings of vehicle speed, cutting blade height, reel speed), adjust parameter to default setting of agricultural vehicle obviously provides determine, at least in part, the location upstream of the agricultural vehicle as a function of a speed of travel of the agricultural vehicle ) . As to claims 3 and 13, Ingalls further d iscloses . The system of claim 1, wherein the memory device further includes instructions that when executed by the at least one processor cause the at least one processor to: determine, using at least the captured information, the position of the one or more objects relative to a first coordinate system; convert the position of the one or more objects from the first coordinate system to a second coordinate system used for a terrain map of a field upon which the agricultural vehicle performs an agricultural operation; and determine, using the second coordinate system and for the location upstream of the agricultural vehicle, the variance in the position of at least the portion of the header relative to the position of the at least one attribute of the upstream crop material or the ground surface (Ingalls [0027-85] “height adjustment system 400 - control the operation of a header/cutting height, roll angle, and tilt angle - at least one sensor 420 - provide a signal indicating the current height and angle of the SPW header 100 - use image data collected from the sensor 420 to analyze the height of the header 100 in relation to a known reference point (e.g., a point on a vehicle associated with the header, a point on the ground, etc.) - measure position of the lifting mechanism 108 to determine the height of the header 100 - adjusting the height of an SPW header - performed autonomously by a controller utilizing a neural network or a machine learning model - harvest a wide range of crops, including: wheat, corn, soybeans, rice, barley, oats, rye, sunflowers, canola, peanuts, cotton, lentils, flax, sorghum, and millet - adapted with different headers or attachments to harvest other crops, such as grapes, olives, and fruits - any variety of input devices - indicate which crop is to be harvested - input devices - scanner, webcam - barcode scanner” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] “receive an indication of a crop to be harvested by the agricultural vehicle, determine at least one attribute of the crop to be harvested - adjust the parameter of the agricultural vehicle to the default setting - operate the agricultural vehicle - receive an input of a user to adjust the setting of the parameter, store the adjusted setting of the parameter as a secondary setting, and upon thereafter receiving a second indication of the crop to be harvested, display the default setting and the secondary setting” [abstract] see Fig. 1-8, plurality of sensor includes image data collected from sensor, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, adjusted parameter setting stored as secondary setting, adjust parameter to default setting of agricultural vehicle obviously provides determine, using at least the captured information, the position of the one or more objects relative to a first coordinate system; convert the position of the one or more objects from the first coordinate system to a second coordinate system used for a terrain map of a field upon which the agricultural vehicle performs an agricultural operation; and determine, using the second coordinate system and for the location upstream of the agricultural vehicle, the variance in the position of at least the portion of the header relative to the position of the at least one attribute of the upstream crop material or the ground surface) . As to claims 4 and 14, Ingalls further d iscloses The system of claim 1, wherein the memory device further includes instructions that when executed by the at least one processor cause the at least one processor to record as a feedback signal a signal from an input device that changes the position at which the portion of the header was placed based on the adjusted control settings (Ingalls [0027-85] “height adjustment system 400 - control the operation of a header/cutting height, roll angle, and tilt angle - at least one sensor 420 - provide a signal indicating the current height and angle of the SPW header 100 - use image data collected from the sensor 420 to analyze the height of the header 100 in relation to a known reference point (e.g., a point on a vehicle associated with the header, a point on the ground, etc.) - measure position of the lifting mechanism 108 to determine the height of the header 100 - adjusting the height of an SPW header - performed autonomously by a controller utilizing a neural network or a machine learning model - harvest a wide range of crops, including: wheat, corn, soybeans, rice, barley, oats, rye, sunflowers, canola, peanuts, cotton, lentils, flax, sorghum, and millet - adapted with different headers or attachments to harvest other crops, such as grapes, olives, and fruits - any variety of input devices - indicate which crop is to be harvested - input devices - scanner, webcam - barcode scanner” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] “receive an indication of a crop to be harvested by the agricultural vehicle, determine at least one attribute of the crop to be harvested - adjust the parameter of the agricultural vehicle to the default setting - operate the agricultural vehicle - receive an input of a user to adjust the setting of the parameter, store the adjusted setting of the parameter as a secondary setting, and upon thereafter receiving a second indication of the crop to be harvested, display the default setting and the secondary setting” [abstract] see Fig. 1-8, plurality of sensor includes image data collected from sensor, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, adjusted parameter setting stored as secondary setting based on default settings, adjust parameter to default setting of agricultural vehicle obviously provides record as a feedback signal a signal from an input device that changes the position at which the portion of the header was placed based on the adjusted control settings ) . As to claims 5 and 15, Ingalls further d iscloses The system of claim 4, wherein the one or more adjusted control settings are determined using one or more optimization models, and wherein the one or more optimization models are adapted to be refined by machine learning that at least considers information provided by the feedback signal (Ingalls [0027-85] “processor uses sensor data from sensor 420 to calculate the contours of the field - ground speed of SPW 710, reel speed, knife speed, roll tension, roll gap, etc.) - directions to adjust the SPW header 700 position in relation to both the crop 712 height and changes in elevation of the field - determine soil conditions - affect the harvesting process - parameter of the agricultural vehicle - include settings - speed of the vehicle, the height of the cutting blade, a speed of the reel, a reel gap, a reel tension, a disc speed, header position/angle, and other factors affect the efficiency and effectiveness of the harvesting process” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] [abstract] see Fig. 1-8, plurality of sensor includes image data, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, agricultural vehicle parameter (include settings of vehicle speed, cutting blade height, reel speed), adjust parameter to default setting of agricultural vehicle obviously provides adjusted control settings are determined using one or more optimization models, and wherein the one or more optimization models are adapted to be refined by machine learning that at least considers information provided by the feedback signal) . As to claims 6 and 16, Ingalls further d iscloses The system of claim 5, further comprising an artificial intelligence engine having a neural network that is configured to refine, using at least the feedback signal, the one or more optimization models to generate one or more updated optimization models (Ingalls [0027-85] “processor uses sensor data from sensor 420 to calculate the contours of the field - ground speed of SPW 710, reel speed, knife speed, roll tension, roll gap, etc.) - directions to adjust the SPW header 700 position in relation to both the crop 712 height and changes in elevation of the field - determine soil conditions - affect the harvesting process - parameter of the agricultural vehicle - include settings - speed of the vehicle, the height of the cutting blade, a speed of the reel, a reel gap, a reel tension, a disc speed, header position/angle, and other factors affect the efficiency and effectiveness of the harvesting process” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] [abstract] see Fig. 1-8, plurality of sensor includes image data, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, agricultural vehicle parameter (include settings of vehicle speed, cutting blade height, reel speed), adjust parameter to default setting of agricultural vehicle obviously provides an artificial intelligence engine having a neural network that is configured to refine, using at least the feedback signal, the one or more optimization models to generate one or more updated optimization models) . As to claims 7 and 17, Ingalls further d iscloses The system of claim 6, wherein the artificial intelligence engine is located at a secondary device, and wherein the secondary device receives a plurality of other feedback signals from a plurality of other agricultural vehicles, the neural network being further configured to use the plurality of other feedback signals to generate one or more updated optimization models (Ingalls [0027-85] “processor uses sensor data from sensor 420 to calculate the contours of the field - ground speed of SPW 710, reel speed, knife speed, roll tension, roll gap, etc.) - directions to adjust the SPW header 700 position in relation to both the crop 712 height and changes in elevation of the field - determine soil conditions - affect the harvesting process - parameter of the agricultural vehicle - include settings - speed of the vehicle, the height of the cutting blade, a speed of the reel, a reel gap, a reel tension, a disc speed, header position/angle, and other factors affect the efficiency and effectiveness of the harvesting process” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] [abstract] see Fig. 1-8, plurality of sensor includes image data, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, agricultural vehicle parameter (include settings of vehicle speed, cutting blade height, reel speed), adjust parameter to default setting of agricultural vehicle obviously provides artificial intelligence engine is located at a secondary device, and wherein the secondary device receives a plurality of other feedback signals from a plurality of other agricultural vehicles, the neural network being further configured to use the plurality of other feedback signals to generate one or more updated optimization models) . As to claims 8 and 18, Ingalls further d iscloses The system of claim 1, wherein the portion of the header comprises a reel, and wherein the adjusted control settings adjust at least one of a reel height and a longitudinal position of the reel (Ingalls [0027-85] “processor uses sensor data from sensor 420 to calculate the contours of the field - ground speed of SPW 710, reel speed, knife speed, roll tension, roll gap, etc.) - directions to adjust the SPW header 700 position in relation to both the crop 712 height and changes in elevation of the field - determine soil conditions - affect the harvesting process - parameter of the agricultural vehicle - include settings - speed of the vehicle, the height of the cutting blade, a speed of the reel, a reel gap, a reel tension, a disc speed, header position/angle, and other factors affect the efficiency and effectiveness of the harvesting process” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] [abstract] see Fig. 1-8, plurality of sensor includes image data, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, agricultural vehicle parameter (include settings of vehicle speed, cutting blade height, reel speed), adjust parameter to default setting of agricultural vehicle obviously provides adjusted control settings adjust at least one of a reel height and a longitudinal position of the reel) . As to claims 9 and 19, Ingalls further d iscloses The system of claim 8, wherein the at least one attribute of the upstream crop material in at least one of a crop material height, crop orientation, or a crop material posture (Ingalls [0027-85] “processor uses sensor data from sensor 420 to calculate the contours of the field - ground speed of SPW 710, reel speed, knife speed, roll tension, roll gap, etc.) - directions to adjust the SPW header 700 position in relation to both the crop 712 height and changes in elevation of the field - determine soil conditions - affect the harvesting process - parameter of the agricultural vehicle - include settings - speed of the vehicle, the height of the cutting blade, a speed of the reel, a reel gap, a reel tension, a disc speed, header position/angle, and other factors affect the efficiency and effectiveness of the harvesting process” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] [abstract] see Fig. 1-8, plurality of sensor includes image data, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, agricultural vehicle parameter (include settings of vehicle speed, cutting blade height, reel speed), adjust parameter to default setting of agricultural vehicle obviously provides attribute of the upstream crop material in at least one of a crop material height, crop orientation, or a crop material posture) . As to claims 10 and 20, Ingalls further d iscloses The system of claim 9, wherein the memory device further includes instructions that when executed by the at least one processor cause the at least one processor to identify, from the captured information, the at least one attribute of the upstream crop material, and determine the adjusted control settings based in part on the at least one attribute of the crop material (Ingalls [0027-85] “height adjustment system 400 - control the operation of a header/cutting height, roll angle, and tilt angle - at least one sensor 420 - provide a signal indicating the current height and angle of the SPW header 100 - use image data collected from the sensor 420 to analyze the height of the header 100 in relation to a known reference point (e.g., a point on a vehicle associated with the header, a point on the ground, etc.) - measure position of the lifting mechanism 108 to determine the height of the header 100 - adjusting the height of an SPW header - performed autonomously by a controller utilizing a neural network or a machine learning model - harvest a wide range of crops, including: wheat, corn, soybeans, rice, barley, oats, rye, sunflowers, canola, peanuts, cotton, lentils, flax, sorghum, and millet - adapted with different headers or attachments to harvest other crops, such as grapes, olives, and fruits - any variety of input devices - indicate which crop is to be harvested - input devices - scanner, webcam - barcode scanner” [0015-26] “adjust the height of the header - ensuring a proper header height - height of the header adjusted frequently, as the crop height and terrain change quickly” [0001-03] “receive an indication of a crop to be harvested by the agricultural vehicle, determine at least one attribute of the crop to be harvested - adjust the parameter of the agricultural vehicle to the default setting - operate the agricultural vehicle - receive an input of a user to adjust the setting of the parameter, store the adjusted setting of the parameter as a secondary setting, and upon thereafter receiving a second indication of the crop to be harvested, display the default setting and the secondary setting” [abstract] see Fig. 1-8, plurality of sensor includes image data collected from sensor, receive indication of crop to be harvested, performed autonomously utilizing neural network or machine learning model, determine plurality of attribute, adjust parameter to default setting of agricultural vehicle obviously provides identify, from the captured information, the at least one attribute of the upstream crop material, and determine the adjusted control settings based in part on the at least one attribute of the crop material) . Citation of Pertinent Prior Art It is noted that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2141.02 VI. PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY , i.e., as a whole and 2123. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The prior art made of record: Hunt , et al. USPGPub No. 20 21/0185918 A1 discloses a header system for an agricultural harvester includes a first reel section, a second reel section, and a sensor configured to generate data indicative of a parameter related to a crop within a field includes a controller configured to receive the data and to control a first actuator to adjust the first reel section independently from the second reel section based on the data as the agricultural harvester travels through the field . Brokaw, et al. USPGPub No. 20230062392 A1 discloses a control system of agricultural harvester for harvesting crop material includes LIDEA sensor for sensing field condition in a forward path of travel and outputting as adjustment signal to raise the header assembly based on field condition. Lamprecht, USPGPub No. 2022/0117158 A1 discloses a method of mapping height of of a crop in a field divided into plurality of areas includes determining a height of cutting bar of agricultural machine and receiving data from crop height sensor. Van dike , et al. USPGPub No. 20 21/0029878 A1 discloses an agricultural machine maps predictive map on plurality of agricultural characteristic values at different geographic locations of a field includes in-situ sensor and using automated machine control . Honeyman , et al. USPGPub No. 20 21/0243954 A1 discloses a method for adjusting height of header reel measuring rotational speed and force opposing the reel . Posselius , et al. USPGPub No. 20170013777 A1 7 discloses a n agricultural harvester includes header height control system, sensor positioned to sense a crop canopy ahead of the header, to sense an actual ground position relative to the header based on sensed crop canopy and actual ground position . Fries, et al. USPGPub No. 20190327892 A1 discloses a harvester cutter head for cutting crop from a field, a reel with reel fingers and a cross conveyor for transporting the cut crop to a rear discharge opening. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Md Azad whose telephone @ ( 571)272-0553 or email: md.azad@uspto.gov . The examiner can normally be reached on Mon-Thu 9AM-5PM . If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mohammad Ali can be reached on (571)272-4105 . The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300 . Information regarding the status of an application may be obtained from Patent Center and the Private Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from Patent Center or Private PAIR. Status information for unpublished applications is available through Patent Center and Private PAIR for authorized users only. Should you have questions about access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). 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) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form. /Md Azad/ Primary Examiner, Art Unit 2119