Method for determining indicator of expected quality of landing and system for determining value of indicator of expected quality of landing (options)

Abstract

FIELD: agriculture.SUBSTANCE: method which includes receiving, via a processor, a plurality of data types related to planting via an agricultural seeding implement; combining, via the processor, the plurality of data types to calculate an indicator of expected planting quality. The expected planting quality index is calculated by determining the optimal planting quality index and calculating the collected set of data types related to planting through an agricultural seeding implement. The expected seeding quality indicator indicates one or more expected criteria, additionally one or more expected criteria include expected density or expected piece-by-piece separation. The system comprises: a processor; a storage device and / or a non-volatile machine-readable medium that stores executable commands that, when executed by the processor, perform operations including: collecting, through the processor, a plurality of types of data associated with planting using an agricultural seeding implement; combining, through the processor, a plurality of types of data to calculate the value of the expected quality of planting. The system comprises: at least one processor and at least one memory device configured to implement a learning model, wherein the learning model is generated based on training data, wherein the learning model is trained using a method that includes the steps of: viewing a plurality of types of data associated with planting through an agricultural seeding tool; and identifying a classifier in the form of an expected planting quality value that corresponds to an operational planting quality based on a plurality of types of data; and wherein the learning model is stored on one or more non-volatile machine-readable media containing instructions that include: collecting in real time data associated with planting through an agricultural seeding tool; and generating and displaying an expected planting quality value for the collected data through a display; wherein the expected planting quality indicator is indicative of one or more expected criteria, further wherein the one or more expected criteria comprises an expected density or an expected piece separation.EFFECT: inventions provide for the determination of the expected quality of seeding.20 cl, 8 dwg

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority under 35 U.S.C. 119 to U.S. Provisional Patent Application No. 63 / 383,972, filed November 16, 2022. The provisional patent application is incorporated herein by reference in its entirety, including, without limitation, the description, claims, and abstract, as well as any figures, tables, appendices, or drawings. TECHNICAL FIELD

[0002] The present invention generally relates to a computer display or other machine-readable medium for use in the agricultural industry. More specifically, but not exclusively, the invention relates to the use of environmental conditions and planter settings to adjust expectations regarding how well aspects of an agricultural implement will perform. BACKGROUND

[0003] The description of the prior art provided herein provides the context for the present invention. The work of the inventors named herein, as well as aspects of the description that are not otherwise qualified as prior art at the time of filing, are not admitted, either expressly or impliedly, as prior art.

[0004] Agricultural implements perform various agricultural operations. For example, a row crop seeder is a machine designed to precisely distribute seeds into the soil. A row crop seeder generally consists of a horizontal attachment bar, attached to a hitch for towing behind a tractor or another implement. The seeding units are mounted on the attachment bar. In various configurations, seeds can be stored in individual hoppers on each seeding unit or contained in a central hopper and delivered to the seeding units as needed. The seeding units contain soil cultivators for opening and closing the seed furrow, as well as a seed metering system for distributing the seeds into the seed furrow.

[0005] In its simplest form, a seed meter comprises a housing, a seed disc, and a seed chute. The housing is designed to create a reservoir for the seed hopper. The seed disc is located within the housing and rotates around a predominantly horizontal central axis. As the seed disc rotates, it passes through the seed hopper, where it picks up individual seeds. The seeds are then distributed into the seed chute, where they fall into the seed furrow. Seed metering units are assigned a location on the seeder's attachment bar, and this location determines at least some of the meter's functionality.

[0006] Seeder settings and environmental conditions can cause seeders to place seeds less accurately than desired. It's difficult for users to know how performance will vary based on a given set of settings and environmental conditions before they begin seeding.

[0007] During planting, the user may discover that the settings and environmental conditions are causing the seeder to perform less than optimally. When the seeder no longer performs as expected, it can be difficult to determine which settings and environmental conditions are negatively impacting seed placement. This makes identifying the cause of problems and then resolving them very challenging for the user.

[0008] Once plants begin to germinate, a few days after planting, areas of poor seed placement are much easier to identify, but without data on what settings and conditions were present when planting in these areas, it is difficult to determine the cause of poor performance and therefore difficult to avoid this problem in the future.

[0009] Therefore, there is a need in the art for a device, such as a user display in a seeder, to provide updated information related to the expected performance of the seeder to ensure better performance of the seeder and adjust the user's expectations.SUMMARY OF THE INVENTION

[0010] The following objectives, features, advantages, aspects, and / or embodiments of the invention are not exhaustive and do not limit the general disclosure of the invention. Not every objective, feature, or advantage must be provided in any embodiment of the invention. Any of the objectives, features, advantages, aspects, and / or embodiments of the invention disclosed herein may be integrated with one another, either in whole or in part.

[0011] One main object, feature and / or advantage of the present invention is that it provides an improvement or elimination of disadvantages in the given technical field.

[0012] Another object, feature and / or advantage of the aspects and / or embodiments of the invention shown and / or described in the present invention is to combine several types of collected data into an expected fit quality value, which provides the user with one piece of information to evaluate when making decisions.

[0013] Another object, feature, and / or advantage of the aspects and / or embodiments of the invention shown and / or described herein is to assist in making decisions that include, but are not limited to, updating planter settings, postponing planting until environmental conditions become more favorable, or determining whether problems need to be addressed immediately before continuing planting or whether planting can be continued with minimal negative consequences.

[0014] Another object, feature, and / or advantage of the aspects and / or embodiments of the invention shown and / or described in the present invention is to determine the expected planting quality using an expected planting quality index that can be used by the user, in conjunction with experts, or in conjunction with planter dealers and original equipment manufacturers (OEMs) to diagnose problems, make purchasing decisions, decide on the best planting methods, and by the OEM to create a better product.

[0015] The methods and systems disclosed herein can be used in a wide variety of applications. For example, while the applications generally relate to the agricultural industry, they can include planting, spraying, seeding, or generally any other application of interaction with the soil of solid and / or liquid particles in a field with an agricultural implement. For example, the present invention can be used for the application of chemicals, including, but not limited to, fertilizers, herbicides, pesticides, water, and the like. According to embodiments of the invention in which the present invention is applied to the application of chemicals, a criterion can be determined and / or calculated, wherein said criterion is similar to the expected planting quality indicator described herein. Such a criterion can be referred to as the expected chemical application quality indicator.This expected chemical application quality indicator may be determined and / or calculated in the same and / or similar manner as the expected planting quality indicator and may be used by the operator in the same and / or similar manner as the expected planting quality indicator is used by the operator for planting. In addition, this expected chemical application quality indicator may be used to optimize and / or improve aspects of chemical application, such as the chemical application rate, the chemical mixture, and the like. The plurality of data types used to determine and / or calculate the expected chemical application quality indicator may include any data types used to determine and / or calculate the expected planting quality indicator, such as each of the data types shown in Fig. 5, including, without limitation, implement / vehicle settings, environmental conditions, and the like.Such an indicator of the expected quality of chemical application and its system used to determine said indicator of the expected quality of chemical application may include and / or include any aspects of any embodiments of the present invention.

[0018] At least one embodiment of the invention disclosed herein has a distinct aesthetic appearance. Decorative aspects included in such an embodiment may help attract consumer attention and / or identify the source of the product being sold. These decorative aspects will not interfere with the functionality of the disclosed subject matter and will facilitate the user's understanding and use of the information provided by the system.

[0017] The methods and / or systems described herein may be incorporated into larger systems or structures that achieve some or all of the previously stated objectives. This may include, without limitation, display units in vehicles, handheld computers, computers, tablets, telephones, servers, cloud systems, or any other system or device that includes a processor and / or computing application.

[0018] According to some aspects of the present invention, a method for estimating an indicator of expected planting quality includes: receiving, through a processor, a plurality of types of data associated with planting through an agricultural planting implement; combining, through the processor, the plurality of types of data to calculate an indicator of expected planting quality; wherein the indicator of expected planting quality is calculated by: determining an indicator of optimal planting quality; and comparing the value of optimal planting quality with the collected plurality of types of data associated with planting through the agricultural planting implement.

[0019] According to some aspects of the present invention, the method further includes updating the setting of the agricultural seeding implement based on the expected planting quality indicator.

[0020] According to some aspects of the present invention, the setting is updated automatically via the processor.

[0021] According to some aspects of the present invention, the method further comprises displaying an indicator of the expected fit quality on a display.

[0022] According to some aspects of the present invention, the method further comprises displaying a proposed change to one or more settings of the agricultural seeding implement to improve the expected planting quality indicator.

[0023] According to some aspects of the present invention, the method further comprises storing the expected fit quality indicator and a plurality of types of data in the memory device.

[0024] According to some aspects of the present invention, the method further includes analyzing a plurality of expected planting quality indicators based on a plurality of types of data to improve an agricultural seeding implement.

[0025] According to some aspects of the present invention, at least one of the plurality of types of data includes environmental weather conditions.

[0026] According to some aspects of the present invention, at least one of the plurality of data types includes GPS data.

[0027] According to some aspects of the present invention, a system for estimating a value of expected planting quality comprises: a processor; a memory device and / or a non-transitory computer-readable medium that stores executable instructions that, when executed by the processor, perform operations, wherein the operations include: collecting, through the processor, a plurality of types of data associated with planting through an agricultural seeding implement; combining, through the processor, the plurality of types of data to calculate a value of expected planting quality; wherein the value of expected planting quality is calculated by: determining a value of optimal planting quality; and comparing the value of optimal planting quality with the collected plurality of types of data associated with planting through the agricultural seeding implement.

[0028] According to some aspects of the present invention, the processor is part of a display.

[0029] According to some aspects of the present invention, the display is configured to display a value of the expected fit quality.

[0030] According to some aspects of the present invention, the display comprises a graphical user interface.

[0031] According to some aspects of the present invention, a user may make changes to one or more settings of an agricultural seeding implement through a graphical user interface based on an expected planting quality value.

[0032] According to some aspects of the present invention, the graphical user interface comprises a map, and the expected landing quality value is displayed relative to a location on the map.

[0033] According to some aspects of the present invention, the collected plurality of data types and the expected fit quality value are stored in a memory device and / or on a non-volatile machine-readable medium as a data pair containing a location and an expected fit quality value.

[0034] According to some aspects of the present invention, a system for estimating a value of expected planting quality of an agricultural seeding tool comprises: at least one processor and at least one memory device configured to implement a learning model, wherein the learning model is generated based on training data, wherein the learning model is trained using a method including the steps of: considering a plurality of types of data associated with planting through an agricultural seeding tool; and identifying a classifier in the form of a value of expected planting quality that corresponds to an operational planting quality based on the plurality of types of data; and wherein the learning model is stored on one or more non-volatile computer-readable media containing instructions including: collecting in real time data associated with planting through an agricultural seeding tool;and generating and displaying the expected fit value for the collected data via a display.

[0035] According to some aspects of the present invention, the expected fit quality value is stored in at least one memory device and / or on one or more non-volatile computer-readable media.

[0036] According to some aspects of the present invention, the commands of one or more non-transitory computer-readable media further include generating and displaying via a display suggestions for improving the value of the expected quality of fit.

[0037] According to some aspects of the present invention, the plurality of data types include GPS data, environmental weather conditions, and agricultural seeding implement settings.

[0038] These and / or other objects, features, advantages, aspects and / or embodiments of the invention will become apparent to those skilled in the art upon consideration of the following brief and detailed description of the drawings. The present invention encompasses (a) combinations of the disclosed aspects and / or embodiments of the invention and / or (b) reasonable modifications not shown or described. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Several embodiments in which the present invention is practiced are illustrated and described in detail, with like reference numerals designating like components throughout the several views. The drawings are provided by way of example and may not be drawn to scale unless otherwise indicated.

[0040] Fig. 1 is a side elevational view of a tractor, such as one used for towing agricultural implements.

[0041] Fig. 2 is a perspective view of an agricultural seeding implement, such as the type pulled by the tractor shown in Fig. 1.

[0042] Fig. 3 shows an example of a display unit for use with an agricultural seeding implement, such as a display unit that includes information related to the operation of the agricultural seeding implement.

[0043] Fig. 4 is another view of a display unit for use with an agricultural seeding implement, showing the seeding implement moving across a field.

[0044] Fig. 5 is a diagram showing at least some aspects of some embodiments of a system for determining an expected landing quality indicator and mapping it.

[0045] Fig. 6 is a decision tree showing variations of aspects and / or embodiments of the present invention.

[0046] Fig. 7A is another decision tree showing variations of aspects and / or embodiments of planting according to the present invention.

[0047] Fig. 7B is another decision tree showing variations of aspects and / or embodiments of solutions associated with the present invention.

[0048] Fig. 7C is another decision tree showing variations of aspects and / or embodiments of off-season decisions according to the present invention.

[0049] Fig. 8 is a diagram showing aspects and / or embodiments of a system for determining an expected fit quality indicator according to the present invention.

[0050] A person of ordinary skill in the art need not consider within the scope of a single figure(s) the almost infinite number of different combinations of features described in the following detailed description in order to facilitate understanding of the present invention.DETAILED DESCRIPTION OF THE INVENTION

[0051] The present invention is not intended to be limited to what is described herein. Mechanical, electrical, chemical, procedural, and / or other changes may be made without departing from the spirit and scope of the present invention. No features shown or described are essential to the basic operation of the present invention unless otherwise indicated.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as generally understood by one of ordinary skill in the art to which embodiments of the present invention pertain.

[0053] Terms in the singular include both singular and plural objects denoted.

[0054] The term "or" is synonymous with "and / or" and means any element or combination of elements of a particular list.

[0055] As used herein, the term "illustrative" refers to an example, instance, or illustration and does not indicate the preferred mode of carrying out the invention unless otherwise indicated.

[0056] The term "about," as used in this document, refers to small variations in numerical values ​​relative to any quantifiable variable. Unintentional error may arise, for example, due to the use of typical measurement methods or equipment, or due to differences in the manufacturing, source, or purity of components.

[0057] The term "substantially" refers to a high or significant degree. Thus, "substantially" can refer to a plurality, a majority, and / or a supermajority of the specified quantifiable variable, given the appropriate context.

[0058] The term "in general" covers both "about" and "in essence."

[0059] The term "capable" describes a design that is capable of performing a task or adopting a particular configuration. The term "capable" can be used interchangeably with other similar phrases, such as "designed," "organized," "adapted," "fabricated," and the like.

[0060] Terms characterizing sequential order, position and / or orientation are not limiting and are referred to only in accordance with the views presented.

[0061] The term "invention" is not intended to indicate any one embodiment of a particular invention, but covers all possible embodiments of the invention as described in the description and claims.

[0062] The "scope" of the present invention is defined by the appended claims, as well as the full scope of equivalents to which such claims extend. The scope of the invention is further qualified as including any possible modification of any of the aspects and / or embodiments of the invention disclosed herein that will lead to other embodiments of the invention, combinations, subcombinations, etc., that will be obvious to those skilled in the art.

[0063] The term "agricultural equipment" encompasses any type of machinery related to the agricultural industry. For example, both agricultural vehicles and agricultural implements are covered by the term "agricultural equipment."

[0064] The term "bulk material" is to be understood broadly and includes, without limitation, grain, seeds, fertilizers, insecticides, dust, pollen, rocks, gravel, dirt, raw materials, or any combination thereof. Bulk material can be mixed with air to form airborne substances.

[0067] It should be understood that the invention, including any or all components disclosed herein, can be used in relation to an agricultural seeding implement, but this should not limit the invention. Furthermore, as will be understood, any aspects of any of the embodiments shown and / or described herein can be combined with each other to form any number of embodiments, whether explicitly disclosed or not, that will be understood by one skilled in the art.

[0066] Fig. 1 shows a tractor 100 used for towing machines / implements used in agriculture. The tractor 100 comprises a cabin 101 with a steering wheel 102 and a seat 103 for an operator. The tractor 100 also comprises a vehicle frame 104, in which an engine is located near the front axle of the tractor 100 and in front of the cabin 101. The cabin 101 and the vehicle frame 104 are structurally supported by a tractor chassis 105, which is attached to the rear drive wheels 106 and the front steering wheels 107, wherein said front steering wheels 107 are operatively connected to the steering wheel 102. The exhaust pipe 108 provides the release of carbon monoxide from the tractor 100 during engine operation. The tractor coupling 109 provides a connection between the agricultural machinery and the tractor 100.

[0067] Fig. 2 shows an agricultural implement in the form of an agricultural seeder 110 used for sowing seeds and applying fertilizers to them in a controlled manner. For example, the seeder 110, as shown in Fig. 2, comprises a drawbar 112, which can be telescopic. The drawbar 112 comprises a first end 114 with a hitch 116 of the implement for attaching to a towing vehicle, such as a tractor 100. The opposite end of the drawbar 112 is attached to a frame or a central beam 118 for hanging interchangeable working tools. Longitudinal rods 120 are connected between the central beam 118 for hanging replaceable working elements and the drawbar 112 and are used together with the folding actuators 122 for folding forward the central beam 118 for hanging replaceable working elements.Thus, drawbar 112 may be a telescopic drawbar, as it can extend or extend, allowing for the forward folding of central bar 118 for attaching interchangeable tools. Seeder 110 may also be a tilt-and-turn, rear-folding, vertical-folding, narrow-row, or any other type of seeder.

[0068] The central beam 118 for hanging replaceable working elements comprises first and second side parts 130, 134 extending therefrom. The central beam 118 for hanging replaceable working elements comprises central hoppers 124, which contain seeds or other granules / particles used in sowing. A plurality of transport wheels 128 are also connected to the central beam 118 for hanging replaceable working elements. The first and second side parts 130, 134 are generally mirror images of each other. The side parts comprise beams 132, 135 for hanging replaceable working elements of the first and second side parts. A plurality of seeding sections 140 are attached along the central beam 118 for hanging replaceable working elements, as well as the beam 132, 135 for hanging replaceable working elements of the first and second side parts.The seeding sections comprise seed meters 142, tools for interacting with the soil and / or other components used for sowing, soil cultivation and / or application of fertilizers to seeds in a controlled manner. First and second markers 133, 136 are also connected to the first and second side portions 130, 134. The markers comprise actuators 137, which are used to raise and lower the markers 133, 136. The markers 133, 136 can be lowered to provide a reference for the edge of the seeder for use during sowing. When this is not necessary, the markers can be raised to the position as shown in Fig. 2, to move the markers out of the way.

[0069] Fig. 2 also shows a plurality of fans 126, as well as a plurality of wheels 138. The side portions may also contain actuators 131 for raising and lowering or otherwise applying a downward force to the side portions. Therefore, as shown in Fig. 2, there are a plurality of components of the seeding implement 110. The components may include movable parts, such as actuators used to move the side portions, markers, seeding sections, etc., and to perform additional functions. For example, the fans 126 are used to create pressure in the seed meters 142, which promotes the adhesion of seeds to the seeding disk moving in them.The seed meters may be electrically driven, with a motor, such as a stepper motor, used to rotate the seed meters to promote seed adhesion and provide controlled seed distribution for ideal spacing, seeding density, and / or placement. Other features may include actuators or other mechanisms for applying downforce to the seeding units 140. Lighting may also be included with the planter.

[0070] Furthermore, a pneumatic seed delivery system may be provided between the central hoppers 124 and any plurality of seed meters 142 on the row units 140, wherein the pneumatic seed delivery system provides a continuous flow of seeds to the row units as needed to ensure continuous seeding through the seed meters on the row units. Thus, various controls of the planter may require or otherwise facilitate the use of an implement control system. The implement control system may assist in controlling each of the functions of the implement or planter 110 to ensure uninterrupted or nearly uninterrupted control of the implement, as well as provide communication and / or transfer of data, status and / or other information between the components.

[0071] It should be understood that the seeder does not necessarily have to include all of the features disclosed herein and may include additional or alternative features shown and / or described. The above has been included as an illustrative seeder, and it should be understood that, in general, any seeder from any manufacturer and any additional devices or aftermarket components may be included in any seeder that encompasses any of the aspects of this invention.

[0072] Therefore, the seeder 110, such as shown, can be towed by a towing vehicle, such as the tractor 100 shown in Fig. 1. In addition, the tractor 110 can be towed by a self-propelled autonomous towing unit, rather than by an operator-powered vehicle, such as a tractor, such as shown and described in commonly owned U.S. Patent No. 10,575,453, which is incorporated herein by reference in its entirety. The rear drive wheels and the front steerable wheels can be replaced by tracks, regardless of whether said tracks are implemented on an operator-powered vehicle or on a self-propelled vehicle.

[0073] Aspects of the operation of the seeder 110, including any operation associated with any of its electronic or mechanical components, can be controlled and / or viewed on a display unit, which can be located in the cab 101 of the tractor 100 or located remotely from the seeder and / or tractor. The display unit can also be called a user interface unit, a monitor and input unit, a monitor unit, an interactive display, or other relative terms. The display unit is configured to be used with an agricultural implement, while being remote from the agricultural implement. For example, it is contemplated that the display unit will be in communication, such as electronic communication, with the seeder. The operator can use the display unit remotely from the seeder, for example, in a tractor or other towing vehicle that is connected to the seeder.The display unit may be displayed inside the towing vehicle, but may also be designed to be removable from the towing vehicle, thus creating a portable unit.

[0074] The display unit may take various forms and may generally comprise or include an intelligent control element and a user interface. For example, an intelligent control element is generally considered a machine-readable medium or a computing device or device containing a processing unit. Examples of such devices include tablets, computers, servers, cell phones, or generally any other handheld, portable, permanently mounted, or other device that may contain a central processing unit and a graphical user interface ("GUI"). A graphical user interface may also be a user interface ("UI") without the required graphics. A user interface refers to the way a user interacts with a machine.The user interface may be a digital interface, a command-line interface, a graphical user interface ("GUI"), a spoken interface, a virtual reality interface, or any other way a user can interact with a machine (a user-machine interface). For example, the user interface ("UI") may comprise a combination of digital and analog input and / or output devices or any other type of UI input / output device necessary to achieve the desired level of control and management of the device. Examples of input and / or output devices include computer mice, keyboards, touchscreens, rotary knobs, control knobs, switches, buttons, speakers, microphones, LIDAR, RADAR, etc. The input(s) received from the UI can then be sent to a microcontroller to control the functional aspects of the device.

[0075] The user interface module may comprise a display that can act as an input and / or output device. More specifically, the display may be a liquid crystal display ("LCD"), a light-emitting diode display ("LED"), an organic LED ("OLED") display, an electroluminescent display ("ELD"), a surface conduction electron emission display ("SED"), a field emission display ("FED"), an active matrix LCD with thin-film transistors ("TFT"), a bistable cholesteric reflective display (e.g., electronic paper), etc. The user interface may also be implemented with a microcontroller to display conditions or data related to the host device in real time or substantially in real time.

[0076] Additional aspects of the display unit may include wired connections for electronic communication with the seeder. Furthermore, it is contemplated that the unit will be able to communicate wirelessly, for example, via any wireless connection. This may include, but is not limited to, Bluetooth, Wi-Fi, cellular data, radio waves, satellite, or any other form of wireless connection that allows communication between the unit and the seeder. Thus, the unit will generally contain any electronic components necessary to support such wireless or wired communication. Wired communication may take the form of a CAN bus, Ethernet, coaxial cable, fiber optic line, or generally any other line that allows communication between the unit and the implement and / or seeder.

[0077] An illustrative image of a display unit 200 that can be used with any or all aspects and / or embodiments of the invention disclosed herein is shown generally in Fig. 3. It should be understood, as has been disclosed, that the display unit 200 shown in Fig. 3 is intended for illustrative purposes and should not limit the invention. However, as shown, the display unit 200 comprises a screen area 202 surrounded by a panel or frame 204, which may be part of a housing 206 of the display unit 200. The display unit 200 shown in Fig. 3 and other figures comprises a color graphical user interface showing both color icons and images. In addition, it should be noted that the display unit 200 shown in the figures comprises a touch screen that allows a user to interact with the display unit 200 by touching.This may be an appendage, such as a finger, or a conductor, such as a stylus or other device. In the illustrated configuration, the housing / panel 206 / 204 does not contain interfaces such as inputs, but it is contemplated that buttons, knobs, or the like will be included in the housing / panel 206 / 204 outside the screen area 202 to provide input options and other interfaces for controlling and / or entering information through the display unit 200.

[0078] Furthermore, although not shown, it should be understood that the display unit 200 comprises a processor, a non-transitory computer-readable medium, modules / programs, a memory device, an operating system, a database, a power source, communication / networking means, and / or a number of inputs and / or outputs.

[0079] In communications and computing, a machine-readable medium is a medium capable of storing data in a format readable by a mechanical device. The term "non-volatile" is used herein to refer to a machine-readable medium ("CRM") that retains data for short periods of time or while powered, such as a memory storage device.

[0080] One or more embodiments of the invention described herein may be implemented using software modules, machines, or components. A software module, machine, or component may comprise a program, subroutine, portion of a program, or software component, or a hardware component capable of performing one or more stated tasks or functions. A module or component may exist within a hardware component independently of other modules or components. Alternatively, a module or component may represent a common element or process of other modules, programs, or machines.

[0081] The display unit 200 preferably comprises an intelligent control element (i.e., a controller) and communication components. Examples of such a controller may be a processor unit or other subcomponents of computing devices. The controller may also comprise other components and may be partially or fully implemented on a semiconductor chip (e.g., a field-programmable gate array ("FPGA")), such as a chip developed using the register-transfer-level ("RTL") design process.

[0082] A processing unit, also called a processor, is an electronic circuit that performs operations on some external data source, typically a memory device or some other data stream. Non-limiting examples of processors include a microprocessor, a microcontroller, an arithmetic logic unit ("ALU"), and, most notably, a central processing unit ("CPU"). A CPU, also called a central processing unit or main processor, is an electronic circuit within a computer that carries out the instructions of a computer program by performing basic arithmetic, logical, control, and input / output ("I / O") operations specified in the instructions. Processing units are common in tablets, phones, portable devices, laptops, user displays, smart devices (TVs, speakers, watches, etc.), and other computing devices.

[0083] The memory device comprises, in some embodiments of the invention, an instruction storage area and / or a data storage area. The memory device may include read-only memory ("ROM", an example of non-volatile memory, meaning that data will not be lost when it is not connected to a power source) or random access memory ("RAM", an example of volatile memory, meaning that data will be lost if it is not connected to a power source). Examples of volatile memory include static RAM ("SRAM"), dynamic RAM ("DRAM"), synchronous DRAM ("SDRAM"), etc. Examples of non-volatile memory include electrically erasable programmable read-only memory ("EEPROM"), flash memory, hard drives, SD cards, etc.In some embodiments of the invention, a processing unit, such as a processor, microprocessor, or microcontroller, is coupled to a memory device and executes software instructions that may be stored in the RAM of the memory device (e.g., during execution), the ROM of the memory device (e.g., generally on a permanent basis), or another non-volatile computer-readable medium, such as another memory device or disk. According to some embodiments of the invention, the intelligent control element of the display unit 200 may comprise one or more processors / processing units.

[0084] In general, the non-volatile computer-readable medium operates under the control of an operating system stored in the storage device. The non-volatile computer-readable medium implements a compiler that enables a software application written in a programming language such as COBOL, C++, FORTRAN, or any other known programming language to be converted into code readable by a processing unit, which may be a central processing unit and / or an intelligent control element. Once completed, the processing unit accesses and manipulates the data stored in the storage device of the non-volatile computer-readable medium using the relationships and logic dictated by the software application and generated by the compiler.

[0085] In at least one embodiment of the invention, a software application and a compiler are tangibly embodied in a machine-readable medium. When instructions are read and executed by the non-volatile machine-readable medium, the non-volatile machine-readable medium performs the steps necessary to implement the invention and / or use the invention of at least some aspects of at least some embodiments of the present invention. The software application, control instructions, and / or firmware (semi-permanent software programmed into a read-only memory) may also be tangibly embodied in a storage device and / or data transmission devices, thereby turning the software application into a product or manufactured article in accordance with the present invention.

[0086] For example, according to some embodiments of the invention, non-volatile computer-readable media may store executable instructions that may be executed by a processor / processing unit, wherein such instructions may include collecting a plurality of types of data related to planting through an agricultural seeding implement, combining the plurality of types of data to calculate an expected planting quality value and displaying the expected planting quality value, wherein the expected planting quality value is calculated by: determining an optimal planting quality value and comparing the optimal planting quality value with the collected plurality of types of data related to planting through the agricultural seeding implement.

[0087] A database is a structured collection of data, typically stored on a computer. A database and the data and information contained within it need not reside in a single physical or electronic location. For example, a database may reside at least partially on a local storage device, an external hard drive, a network-connected database server, a cloud storage system, a distributed ledger (such as those commonly used with distributed ledger technology), or the like.

[0088] A power supply supplies a specific voltage to a device or component or components of a device. The power supply may be a DC power supply, an AC power supply, a linear generator, etc. The power supply may be implemented with a microcontroller to accept power from other power sources independent of the grid, such as a generator or solar panel.

[0089] Regarding batteries, a dry cell battery may be used. Additionally, the battery may be rechargeable, such as a lead-acid battery, a low self-discharge nickel-metal hydride battery (LSD-NiMH), a nickel-cadmium battery (NiCd), a lithium-ion battery, or a lithium-ion polymer battery (LiPo). When using a lithium-ion battery or LiPo battery, care should be taken to avoid the risk of unexpected fire due to the heat generated by the battery. Although such incidents are rare, they can be minimized through appropriate design, installation, procedures, and levels of protective equipment that make the risk acceptable.

[0090] The power supply can also be driven by a power generation system, such as a dynamo, using a switch or electromagnetic induction. Electromagnetic induction eliminates the need for batteries or dynamo systems, but requires placing a magnet on the moving component of the system.

[0091] According to some embodiments of the invention, the power supply may also include an emergency stop element, also known as a "kill switch," to shut down the equipment in an emergency. According to some embodiments of the invention, the power supply may include any other safety mechanisms known to prevent injury to machine users. The emergency stop element or other safety mechanisms may require user input or may use automatic sensors to detect and determine when certain safety actions should be taken.

[0092] In some embodiments of the invention, the network is, by way of example only, a wide area network ("WAN"), such as a TCP / IP-based network or a cellular network, a local area network ("LAN"), a neighborhood area network ("NAN"), a home area network ("HAN"), or a personal area network ("PAN") using any of a variety of communication protocols, such as Wi-Fi, Bluetooth, ZigBee, near field communication ("NFC"), etc., although other types of networks are possible and are discussed herein. The network typically provides communication between the communication module and the central location during times of poor connection quality. Communication over the network may be secured using one or more encryption methods, such as those provided by the Advanced Encryption Standard (AES), which replaced the Data Encryption Standard (DES), the IEEE 802 standard.1 for port-based network security, pre-shared key, Extensible Authentication Protocol ("EAP"), Wired Equivalent Privacy ("WEP"), Temporal Key Identification Protocol ("TKIP"), Wi-Fi Protected Access ("WPA"), etc.

[0093] ISO 11783, known as "Tractors and machinery for agriculture and forestry — Serial control and data network" (commonly referred to as "ISO-bus" or "ISOBUS"), is a communication protocol for the agricultural industry based on the SAE J1939 protocol (which includes the CAN-bus). The standard consists of 14 parts: ISO 11783-1: "Generic standard for mobile data communications"; ISO 11783-2: "Physical layer"; ISO 11783-3: "Data link layer"; ISO 11783-4: "Network layer"; ISO 11783-5: "Network management"; ISO 11783-6: "Virtual terminal"; ISO 11783-7: "Implementation of the message application layer"; ISO 11783-8: Powertrain messages; ISO 11783-9: Tractor ECU; ISO 11783-10: Task controller and management information system data exchange; ISO 11783-11: Mobile data element dictionary; ISO 11783-12: Diagnostic services; ISO 11783-13: File server; ISO 11783-14: Sequence management.

[0094] Ethernet is a family of computer networking technologies commonly used in local area networks ("LANs"), metropolitan area networks ("MANs"), and wide area networks ("WANs"). Systems transmitting data over Ethernet divide the data stream into shorter pieces called frames. Each frame contains source and destination addresses, as well as error-checking data to detect and discard corrupted frames; more often, higher-layer protocols trigger retransmission of lost frames. According to the OSI model, Ethernet provides services up to and including the data link layer. Ethernet was first standardized within the Institute of Electrical and Electronics Engineers ("IEEE") 802.3 working group / IEEE standards collection, a working group that defines the physical layer and media access control (MAC) of the data link layer of wired Ethernet.Since then, Ethernet has been enhanced to support higher bit rates, more nodes, and longer link distances, while still maintaining significant compatibility with previous versions. Ethernet has industrial applications and works well with Wi-Fi. The Internet Protocol (IP) is typically transmitted over Ethernet, making it one of the key technologies that makes up the internet.

[0095] The Internet Protocol (IP) is the primary communications protocol in the internet protocol suite for relaying datagrams across network boundaries. Its routing function enables inter-network communication and essentially establishes the internet. IP delivers packets from a source host to a destination host based solely on the IP addresses in the packet headers. To this end, IP defines packet structures that contain the data to be delivered. It also defines the addressing methods used to label datagrams with source and destination information.

[0096] The Transmission Control Protocol (TCP) is one of the core protocols of the Internet Protocol suite. It originates from the original network implementation, in which it complemented IP. Therefore, the entire suite is commonly referred to as TCP / IP. TCP provides reliable, ordered, and error-checked delivery of a stream of octets (bytes) between applications running on hosts communicating over an IP network. Key Internet applications, such as the World Wide Web, email, remote administration, and file transfer, use TCP, which is part of the transport layer of the TCP / IP suite.

[0097] The Transport Layer Security (TLS) protocol and its predecessor, the Secure Sockets Layer (SSL) protocol (SSL / TLS), often run on top of TCP. SSL / TLS are cryptographic protocols designed to provide secure communications over a computer network. Several versions of the protocol have found widespread use in applications such as web browsing, email, instant messaging, and Voice over IP (VoIP). Websites can use TLS to secure all communications between their servers and web browsers.

[0098] Each of the networks and communication methods / protocols described herein may be used by aspects of the present invention in accordance with various embodiments of the invention.

[0099] In some embodiments of the invention, the display unit 200 or other device may include one or more communication ports, such as Ethernet, a standard ATA ("SATA") interface, a universal serial bus ("USB"), or embedded disk management electronics ("IDE"), for transmitting, receiving, and / or storing data.

[0100] Some embodiments of the invention utilize a satellite-based radio navigation system, such as the Global Positioning System (GPS). GPS is owned by the United States and uses satellites to provide geolocation information to a GPS receiver. GPS and other satellite-based radio navigation systems can be used for positioning, navigation, tracking, and mapping.

[0101] Referring again to Fig. 3, the display unit 200 comprises a number of icons and bars for hanging tool attachments, such as a bar for hanging tool attachments at the top of the display unit 200 and a bar for hanging tool attachments with icons along the right side of the display unit 200, which can lead to additional screens that will provide more options and inputs.

[0102] Furthermore, it should be understood that at least some aspects of some embodiments of the invention disclosed herein may be on other devices, such as telephones, PDAs, tablets, computers, processors, or the like. Information may be transmitted from a seed drill or other implement to the device via a wired and / or wireless connection and may be included as part of a farm management system. As will be understood, the information may be used in real time or at a later date / time to provide information related to the agricultural implement (e.g., seed drill 110) and / or its use. Such information may relate to the performance of the seed drill and may include possible results for the equipment's operation, as well as information on how to better manage the system.

[0103] Fig. 4 shows an image of a display unit 200 used during planting with a seeding implement. The display screen 202 has changed to show a graphical image of a tractor and a seeding machine moving across an illustrative field. A number of icons, sections, and other parts of the display screen 202 include information related to planting and the movement of the tractor and the implement. The information includes, without limitation, information on speed, direction, down force (% contact), information on the seeding unit, information on density, planting, etc. This is presented in the form of numbers, text, percentages, color information, and combinations thereof. As will be understood, the screen 202 can be changed, for example, in accordance with the user's preferences, to selectively display the desired information and to switch between different screens.Non-limiting examples include the user being able to view problems / warnings that the system may indicate, viewing help manuals and / or operating command manuals, viewing field information, viewing and changing system, planting tool, or display unit 200 settings, viewing status information associated with the planting tool, and / or even making changes to one or more components of the planting system. For example, changes may be made to accommodate planting preferences, displayed / displayed information, or to run diagnostics.

[0104] One piece of information displayed on the display unit 200, such as that shown in the figures, relates to the quality of operation. For example, it may display seed spacing, seed singulation information (e.g., skips and / or repeats), seeding density information, or other information that shows the desired or specified planting conditions compared to what actually occurs. Users expect these settings to be met or achieved with a slight discrepancy (e.g., 95%+ seed singulation or optimal seed spacing). When the display shows that the actual readings from the sensors and other planter components do not match the set / required planting settings, the operator may assume that the implement or another component is not operating correctly or that other problems may occur.They may overlook the fact that certain settings, conditions, or other factors can actually limit a tool's performance, and that performance can be improved in some cases or may require significant modifications to demonstrate improvement. However, without information about performance limitations, users will be unaware and may assume the problem lies with the hardware itself.

[0105] Thus, as will be appreciated, at least some aspects of some embodiments of the present invention relate to identifying an "expected planting quality" indicator that provides the user with performance / limitations information. Furthermore, the system can provide guidance or information to help improve the expected planting quality indicator to ensure a better user experience. Many planter settings and environmental conditions, such as quality and / or GPS data, can be used to predict that the planter will not perform optimally. Presenting these predictions to the user with an "expected planting quality" indicator allows the user to know whether they are "suitable for planting" or whether there are planter settings or environmental conditions that will negatively impact the planter's performance.This allows users to decide whether to make changes to the planter, allows the user to decide to delay planting until better environmental conditions are established, and / or gives users an informed expectation of the planter's potential performance.

[0106] Changes in this expected planting quality indicator can be observed in real time, for example, on the screen of the display unit 200 shown in Fig. 3 or 4, in real time during the planting process, and also stored by the GPS position when the seeder crosses the field. This information can be displayed on a map (similar to that shown in Fig. 4), so that the changing expected planting quality in the field can be easily viewed over a large area. The expected planting quality indicator can be displayed relative to the location on the map. In addition, the expected planting quality indicator and the collected data associated with it (for example, shown in Fig. 5) can be stored in a memory device together as a data pair, so that the data pair will include the expected planting quality indicator and the location to which the expected planting quality indicator relates.

[0107] The planter settings and environmental conditions that contribute to the expected planting quality value can also be recorded by GPS position separately from the expected planting quality value, so that they can be viewed on a map separately from other values.

[0108] Fig. 5 shows an example of a system 300 for determining an expected landing quality indicator and mapping it. The system 300 shown in Fig. 5 shows a plurality of possible inputs and exports for the system 300, which, when considered in combination with the export and logical model shown in Fig. 6, indicate at least some options for using the output data of the system 300. According to some embodiments of the invention, any and / or all inputs to the system 300 and / or the processor 305 can be combined and / or used by the processor 305 and / or its components to determine, calculate, optimize and / or improve the expected landing quality indicator.

[0109] System 300 includes a processor 305, which may be any type of intelligent control element, controller, or the like that may include a processing unit and associated components. Although processor 305 in Fig. 5 is referred to herein as a single "processor," according to some embodiments of the invention, processor 305 may include any number of processors / processing units in the range from 1 to N, where N is any number greater than 1. Processor 305 is shown as electronically connected to multiple inputs, which are shown by arrows from the inputs to the processor. Although multiple inputs are shown, they should not limit the present invention, and it should be understood that any input that can provide information to system 300 should be considered part of the present invention.

[0110] The figure shows sensors such as sensor 1 302A, sensor 2 302B and sensor N 302C, where "N" denotes any number of sensors of the agricultural system. Thus, the number of sensors can vary from zero to N, where N is any number greater than zero. The modules can be placed on and around the agricultural implement and / or tractor and include various sensors for providing information to the intelligent control element / processor 305. As an example, the tractor 100 and / or the seeder 110 can be included as part of the system 300. The sensors can include vision sensors, radar sensors, LIDAR sensors, thermal sensors, moisture sensors, radio frequency sensors, short-range radio communication, long-range radio communication, antennas, and the like. These sensors can be grouped in any way and can be used to determine many aspects.For example, sensors can be used to determine the location of an agricultural implement and / or tractor, or they can be used to determine the location of a nearby object or obstacle. Sensors can be used to determine soil characteristics such as moisture, compaction, temperature, and so on. Sensors can also be position sensors to determine whether the agricultural implement is on level ground, on a hillside, climbing a hill, or descending a hill, etc. Position sensors can also determine areas where the implement should not move, based on predetermined and / or programmed data. One or more sensors can be included in the seeding unit, for example, to detect seeds being planted by the seeding unit. The sensor can be in the seed meter, the seed transport system (seed-to-ground system), or otherwise included.As an example, a sensor will be disclosed in a seed tube used to deliver seeds from a dispenser to a furrow in the ground.

[0111] The seed sensor for the gravity seed tube is located in the elements. Therefore, the sensor may be exposed to soil and other materials as the planter moves through the field. The sensor, which may be an optical sensor, may be affected by the accumulation of soil or other material on one or more parts of the sensor. For example, accumulation on the transmitter, receiver, and / or transceiver may affect the ability to detect seeds and / or distinguish between seeds passing by the sensor and other materials, such as soil, fertilizer, etc. To account for this accumulation, the sensor can self-adjust. This may take the form of increasing or decreasing sensitivity levels or adjusting the amount of information needed to detect material passing it. This may continue until the operator or user is able to clean (wipe) the surface of the sensor components.

[0112] However, the problem may also occur after clearing the sensor components of accumulation. As noted, the sensor automatically adjusts to account for accumulation. After clearing the accumulation, a clean sensor may not be properly calibrated and may therefore contain errors in its signals.

[0113] The sensors can also be used with positioning systems such as GPS 304 and / or Real-Time Kinematic Positioning (RTK) 306. These inputs, along with the tractor, can provide information related to direction, speed, etc.

[0114] Additional inputs for system 300 include a weather determination device 307. Such a weather determination device can provide information related to environmental conditions (temperature, humidity, precipitation, pressure, wind speed / direction, etc.). The weather determination device 307 can also include forecasting, for example, to provide predicted future weather conditions. The weather determination device 307 can include a weather determination application and / or a connection to a meteorological service / station.

[0115] System 300 includes any number of warnings 308 that relate to the condition of one or more implement components. This may include parts that are worn and / or have experienced wear, parts that require calibration, dirty sensors, or other information indicating that the components may not be operating optimally. System 300 may include implement settings 310 and / or any other settings. Settings 310 refer to settings entered by the user or selected automatically by the implement control system. This may include speed, downforce, seed spacing, row spacing, seed population, and / or any other variable that is adjustable for the implement.

[0116] As noted, all inputs from system 300 are provided to processor 305 to determine the best possible implement output, which can be reflected in the expected fit value or indicator 312. One advantage of the present invention is that it combines several types of collected data into the expected fit value or indicator 312, which provides the user with a single piece of information to evaluate when making decisions. This is indicated by arrow 321. Since the expected fit value or indicator 312 represents a single value, this can simplify user decision-making.

[0117] According to some embodiments of the invention, the system 300 may determine and / or calculate the expected planting quality indicator 312 by first determining and / or calculating an optimal planting quality indicator, which may be an optimal planting quality indicator in general or may be an optimal planting quality indicator based on the settings of the agricultural seeding implement. The system 300 may then compare the optimal planting quality indicator with the collected plurality of types of data (which may include any and / or all inputs to the system 300 and / or the processor 305, such as those shown in Fig.5) to determine and / or calculate the expected planting quality indicator 312 In some embodiments of the invention, once the optimal planting quality indicator is determined and / or calculated as a whole, the system 300 may then consider and / or take into account the collected plurality of data types (which may include any and / or all inputs to the system 300 and / or the processor 305, such as those shown in Fig. 5) to determine and / or calculate the expected planting quality indicator 312. In some embodiments of the invention, once the optimal planting quality indicator is determined and / or calculated based on the settings of the agricultural seeding implement, the system 300 may then consider and / or take into account the collected plurality of data types (which may include any and / or all inputs to the system 300 and / or the processor 305, such as those shown in Fig. 5) to determine and / or calculate the expected planting quality indicator 312.

[0118] Additional aspects of the system 300 include the location of the processor 305. This is shown generally by the dotted lines between the processor 305 and the cloud processor 314, display 316, or other devices 318 (other devices generally refer to any other component that has a processing unit, such as a computer, PDA, tablet, server, smart device, or the like). In other words, the processor 305 can be located with the implement and / or tractor, for example, a wired connection between the inputs and the processor 305, or it can be wireless and remote. The cloud processor 314 will allow inputs to be sent to the cloud system, where an indicator 312 of the expected planting quality will be determined. It can then be sent back to the implement / tractor. The information can also be sent to the farm management system, which can be on the computer 318 remote from the implement, where it is calculated.Additionally, the processing unit 305 may be part of a display 316 that is located in or on the tractor, which provides real-time feedback to the user.

[0119] Furthermore, it should be understood that system 300 includes all processors (i.e., cloud processor 314, display 316, and any other device 318). In such a situation, it should be understood that all components can be connected to each other, for example, by wire or wirelessly, to exchange information with each other. Thus, the expected landing quality indicator 312 can be determined at any or all locations and then transmitted to others. This is shown by arrows 317A and 317B, which indicate two-way communication for information from any and all devices.

[0120] After the expected planting quality indicator 312 is determined based on the inputs, it can be sent to a display on any of the devices, including, but not limited to, the cloud processor / display / system 314, the display in the tractor 316, or other processing devices 318 (e.g., part of a farm management system). The expected planting quality indicator 312 can be displayed on any or all devices to provide information to users so that they can monitor and make decisions based on such information. This is generally shown by arrow 320, which shows that the indicator 312 is sent to various devices.

[0121] As shown in Figs. 6, 7A, 7B and 7C, there are various methods and / or determinations that can be made using expected planter quality index (EPQI) information, such as that determined and / or mapped as disclosed herein.

[0122] For example, starting with Fig. 6, the decision starts and asks whether the operator / system is planting. If so, the decisions go to the diagram in Fig. 7A (going to the letter A in Fig. 6). As shown in Fig. 7A, the first determination is whether the EPQI is at or above an acceptable level. As noted, the EPQI will be determined based on a number of inputs and factors. This will indicate the expected planting quality, including, but not limited to, the expected individual separation, planting density, spacing, down force, planting depth, etc. If the system 300 and environmental conditions suggest that the planter will operate at a normal or acceptable level, the diagram indicates the need to continue planting / operating as usual. In addition, the system 300 (e.g., the display) will provide suggested updates to maintain or improve the EPQI, which can be configured to be executed automatically or to be mandatory for implementation.Additionally, the 300 System will allow data to be sent to dealers and / or OEMs (original equipment manufacturers) for review and improvement of the 300 System.

[0123] If the EPQI is not at or exceeds an acceptable level, as shown in Fig. 7A, the next step may be to consider options and / or implement one or more of the options. Options include, but are not limited to, continuing planting anyway. There are certainly cases where planting must be continued. This may be due to the time of year, delays, the amount of planting remaining versus the possibility of a delay, etc. In such cases, the operator may continue planting even though the EPQI provides information that planting conditions may be less than ideal or at least worse than expected. For any reason(s), including, but not limited to, implement settings, weather conditions, component wear, lack of proper / updated equipment, etc., one or more planting settings may have a high probability of not being met.The operator can simply ignore this and continue planting, and then evaluate later and / or determine whether the crop was limited based on the decision to continue planting. If the operator decides to ignore the unacceptable / less-than-ideal EPQI and continue planting, according to some embodiments of the invention, the system 300 (e.g., display) can provide suggested updates to maintain or improve the EPQI, as described above. Furthermore, if the operator decides to continue planting despite the less-than-acceptable / less-than-ideal EPQI, the system 300 can send the data to dealers and / or OEMs for review and improvement of the system 300, as described above.

[0124] Other options, if the EPQI is not at or above an acceptable level, include system 300, for example, via a display, providing suggestions for improving the EPQI. These may include suggested setting changes, suggested component cleanings, suggested component replacements or upgrades, or other suggested changes that could potentially increase the EPQI for landing. In some cases, system 300 may be configured to automatically make changes to settings that will ensure the highest possible EPQI based on the desired settings. For example, the user may apply a required spacing or planting density level or may set a speed to successfully complete the landing. System 300 can automatically detect this and automatically adjust the settings to ensure the highest possible EPQI for the settings.

[0125] System 300 can also indicate problems or warnings that may affect the EPQI, as shown in Fig. 7A. These may be in the form of component failure or other problems (e.g., wear, calibration issues, clogging, etc.), or may be in the form of limitations of a specific setting. For example, system 300 can recognize that, based on user input for planting settings, the EPQI is limited based on the state of the equipment itself. This may be an outdated part / component, or the user may be using an implement that does not include all or the necessary options for operation at an optimal level. System 300 can alert the user to provide ways to improve the EPQI, which may be in the form of maintenance, updates, or other changes. For example, system 300 can provide suggested updates that the dealer can perform and allow the user to request such updates before operation.The dealer may be notified and necessary steps may be taken to update the seeding implement and / or the 300 system. The dealer may also be requested to service the implement to increase the EPQI and may be called accordingly.

[0126] Furthermore, the system 300 may detect that weather conditions, such as heat, humidity, or some other factor, are causing the implement to operate with a less-than-ideal EPQI. The system 300 may simply suggest waiting until the indicated weather conditions improve before continuing planting, as shown in Fig. 7A. According to some embodiments of the invention, the system 300 may suggest waiting until any condition and / or factor negatively affecting the EPQI improves before continuing planting.

[0127] However, it should be noted that these are not the only ways to continue operation when a less than acceptable / non-ideal EPQI is indicated, and other options obvious to those skilled in the art should be considered as part of the present invention.

[0128] Referring again to Fig. 6, one of the queries is whether the operator wants to use the implement, i.e., whether he wants to perform landing. This is indicated by the letter B, which is shown in Fig. 7B. The diagram shown in Fig. 7B is similar to the part of Fig. 7A when the EPQI is below the preferred level. However, the difference is that in Fig. 7B, landing is not currently occurring. Instead, there is a desire to perform landing, but there may be some options to try to increase the EPQI before starting work / landing.

[0129] As shown in the figure, one option may be to check whether any updates, acquisitions, or potential changes could improve the EPQI. This could be a part or component update, for example, from a dealer or OEM, a software update, or another change. According to at least some aspects of some embodiments of the invention, options may be provided directly as part of system 300, for example, via a display, where a request for an update or service can be sent to the dealer for improvement. Through a connection to system 300, such a request can be transmitted to the dealer, who can then provide the acquisition and / or service that should increase the EPQI before work / landing. The dealer or dealer technician can perform the necessary equipment maintenance, especially if there is a problem associated with a implement component.

[0130] Another option may be a simple wait, such as waiting for environmental conditions such as weather to change. Weather can affect the EPQI, and system 300 may include a weather application or a connection to a weather service / station, which may include a forecast. System 300 may alert the operator to wait until a specified time period for which the weather is forecast to change, which is likely to increase the EPQI. This may be displayed as part of a field map on the display, which may include a forecast overlay. An hourly image with the corresponding estimated EPQI may also be shown on the display, letting the user know when the weather is best to work.

[0131] Finally, Fig. 7B also shows that any information can be sent automatically or manually by the user to the dealer or OEM. This information can be used to improve the system 300, including any future suggestions for operating the implement with the best possible EPQI. The information can be used by the dealer / OEM to implement best practices and for feedback. The information can further be used by the dealer / OEM to assist in diagnosing problems, making purchasing decisions, and / or developing better product(s).

[0132] FIG. 6 also shows a method for a situation where the operator is viewing the system 300 and is not going to plant / work, for example, due to the off-season. The off-season refers to time not related to work. This may be time other than the planting weeks / months, when the implement can be serviced, stored, or otherwise evaluated, and is shown by the letter C, which refers to FIG. 7C.

[0133] FIG. 7C shows several methods for optimizing the system 300 during the off-season. The first relates to the user / operator method. The EPQI-related information can be reviewed by the user, for example, with one or more experts, for fine-tuning and / or planning future use. For example, the operator can review the EPQI data along with the reasons for the quantity, or with the yield data of the associated crops, with or without them, with an agronomist, dealer, OEM representative, or other expert. The meeting can be used for training to demonstrate how the EPQI could be improved, which could increase yield. The meeting with the expert also allows the operator to ask questions regarding any aspects of the planting and / or the system 300 and receive answers from the expert, and also allows the expert to make suggestions and / or provide comments on ways to improve the planting.Often, a user may be pressed for time to complete an operation and may not understand why a change or changes could improve performance. Taking the time to review this information can be helpful for future seasons.

[0134] In addition, such a meeting can help create prescription maps for future planting seasons, as well as other on-farm operations such as tillage, seeding, spraying, cultivation, etc. There may be reasons beyond the norm for the EPQI to be lower than required, such as field conditions, farm conditions, weather conditions, etc., which cannot be assessed without operator involvement, and this meeting will provide such information for system improvement.

[0135] Another way to process data during the off-season involves dealers and OEMs. OEMs and / or dealers can review EPQI-related information, such as settings, environmental conditions, location information, or any other information, to determine whether there are ways to improve it in the future. This could be in the form of software updates, hardware upgrades, suggested changes, or any other way that could improve the EPQI at a time convenient for the user / operator, resulting in a better product and, potentially, better results (i.e., higher yields).

[0136] It should be noted that while EPQI data may be collected, generated and / or displayed / transmitted in real time on the go, all aspects of such EPQI data, including mapping, may also be stored and used / viewed / analyzed at a later date / time by operators, experts, dealers, OEMs, etc., as described in this document.

[0137] Still further aspects of the invention are shown in Fig. 8. As noted, the EPQI is determined based on a number of inputs. This definition will continue to be improved over time and may include various ways of examining continuous data for improvement. Some, but not all, of the ways in which the system 300 can be improved over time are shown in Fig. 8. Each of the learning methodologies / techniques / networks / models shown in Fig. 8 can be used by aspects of embodiments of the present invention. For example, each of the learning methodologies / techniques / networks / models shown in Fig. 8 can be used to optimize and / or improve aspects of embodiments of the present invention. While the learning methodologies / techniques / networks / models shown in Fig.8 can be used in various aspects of various embodiments of the present invention, in particular, the system 300 can use any and / or all of the learning methodologies / techniques / networks / models shown in Fig. 8, as well as any other learning methodologies / techniques / networks / models, to optimize and / or improve the determination, calculation and / or improvement of the expected landing quality index. For example, any and / or all of the learning methodologies / techniques / networks / models in Fig. 8 can be applied to consider a plurality of data types, such as in Fig. 5, and identify one or more classifiers in the form of an expected landing quality index that corresponds to the operational landing quality based on the plurality of data types.To identify one or more classifiers in the form of an expected fit quality metric and to optimize and / or improve aspects of embodiments of the present invention, any and / or all methodologies / techniques / networks / models may use training data in accordance with some embodiments of the invention.

[0138] It is contemplated that system 300, for example, via processor 305, may incorporate the use of heuristics for continuous improvement and learning. A heuristic is an approach to problem solving or self-knowledge using a "computed approximation" derived from previous experience. A heuristic is typically a manually coded function. By using or incorporating heuristics into system 300, for example, during the off-season, the OEM will continually refine the definition and / or calculation of the EPQI and provide better suggestions for improvement during implement use.

[0139] System / processor 300 / 305 may also utilize artificial intelligence (AI), such as through machine learning and / or a neural network. AI is intelligence implemented by machines, such as computers and / or processors. While AI has many definitions, some define AI as the use of machines and / or systems to imitate human cognitive abilities, such as decision-making and / or problem-solving. AI is also described as machines and / or systems that are capable of acting rationally, such that they can discern their environment and effectively and efficiently take the necessary steps to maximize the chance of achieving the desired outcome. AI goals may include, but are not limited to, reasoning, problem solving, knowledge representation, planning, learning, natural language processing, perception, movement and manipulation, social intelligence, and general intelligence.AI tools used to achieve these goals may include, but are not limited to, search and optimization, logic, probabilistic methods, classification, statistical learning methods, artificial neural networks, machine learning, and deep learning. Machine learning (ML) is the study of computer algorithms that can automatically improve through experience and the use of data. ML is considered a subset of AI. Machine learning algorithms build a model based on sample data, known as training data, to make predictions or decisions without being explicitly programmed to do so. A machine learning algorithm and / or model can be designed so that they can be trained using training data to ultimately make predictions and / or decisions. Machine learning can include various approaches, such as supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, and dimensionality reduction, among others. Supervised learning models are trained using training data, which includes inputs and the desired output.This type of training data can be called labeled data, in which the outputs provide labeling for the inputs. A supervised learning model can develop, through optimization or other methods, a method and / or function used to predict the outcome of new inputs. Unsupervised learning models accept data that includes only inputs and look for common features in the inputs, such as grouping or clustering aspects of the inputs. Therefore, the training data for unsupervised learning does not include labeling and / or classification. Unsupervised learning models can make decisions about new data based on how similar or related it is to existing data and / or the desired objective. Examples of machine learning models include, but are not limited to, artificial neural networks, decision trees, support vector machines, regression analysis, Bayesian networks, and genetic algorithms.Examples of potential machine learning applications include, but are not limited to, image segmentation and classification, ranking, recommendation systems, visual identity tracking, face verification, and speaker verification.

[0141] For the present invention, machine learning can be used to identify classifiers, such as input implement settings, environmental conditions, parts, component status (age, wear, version, etc.), etc., to train the system 300 to determine and learn the best solutions / combinations based on the inputs to ensure the highest possible EPQI. ML can be included in the processor 305, included in cloud processors, executed in a remote location, or even executed at the OEM / dealer for continuous training and updating to provide the best information for the system 300.

[0142] Another way to improve System 300 is to use Bayesian statistics and / or Bayesian networks, which use event probabilities to provide the necessary information and feedback. This can be implemented and configured to evaluate inputs, including any settings, environmental conditions, component feedback, statuses, input types, etc., to provide an EPQI based on the probability of the vehicle / component / landing tool's ability to operate.

[0143] Furthermore, fleet learning can be incorporated into System 300 to improve the operation and understanding of EPQI for all implements connected to System 300, including all those connected to the System 300 processor / display, regardless of owner. With fleet learning, a system, such as a processor that calculates EPQI, learns something for one implement based on new information, such as a setting or the like. If this information is valuable overall, it will be shared with all devices that can use the EPQI function, providing benefits for all implements, not just one. This is beneficial for everyone and can be implemented at the OEM level, for example, during System 300 evaluation and upgrades during the off-season.

[0144] Thus, it has been shown that the use of EPQI provides numerous improvements and / or benefits to the operation of one or more implements, such as seeding implements. The provided feedback can be useful to operators, dealers, and OEMs for product improvement and providing the best-case scenario for implement operation. The information monitored to determine expected planting quality can be used by the operator, shared with experts, or shared with seeding dealers and OEMs to assist in problem diagnosis, purchasing decisions, deciding on the best planting methods, and the OEM in developing a better product. It should be understood that any number of variations, alternatives, etc., that are obvious to those skilled in the art are intended to be part of the present invention.

Claims

1. A method for determining the expected quality of landing, including: receiving through the processor a plurality of types of data related to planting through an agricultural seeding implement; combining multiple types of data through a processor to calculate an indicator of expected landing quality; in this case, the expected quality of landing indicator is calculated by: determining the optimal landing quality indicator; and calculation of the collected set of data types related to planting through an agricultural seeding tool; wherein the expected fit quality indicator is indicative of one or more expected criteria, wherein the one or more expected criteria further include expected density or expected piece separation.

2. The method of claim 1, further comprising updating the setting of the agricultural seeding implement based on the expected planting quality indicator.

3. The method according to paragraph 2, further including automatic updating of the settings via the processor.

4. The method according to claim 1, further comprising displaying an indicator of the expected quality of fit on a display.

5. The method of claim 4, further comprising displaying a proposed change to one or more settings of the agricultural seeding implement.

6. The method of claim 1, further comprising storing the expected fit quality indicator and the plurality of data types in the storage device.

7. The method of claim 6, further comprising analyzing a plurality of indicators of expected fit quality based on a plurality of types of data.

8. The method according to claim 1, characterized in that the plurality of types of data includes environmental weather conditions and / or GPS data.

9. The method of claim 1, wherein the one or more expected criteria further include expected seed spacing, expected downforce, and / or expected planting depth.

10. A system for determining the value of expected fit quality, comprising: CPU; a storage device and / or non-volatile machine-readable medium that stores executable instructions that, when executed by a processor, perform operations including: collecting multiple types of data related to planting through an agricultural seeding implement via a processor; combining multiple types of data through a processor to calculate the expected fit value; in this case, the value of the expected quality of fit is calculated by: determining the value of optimal fit quality; and calculation of the collected set of data types related to planting through an agricultural seeding tool; wherein the expected fit quality indicator is indicative of one or more expected criteria, wherein the one or more expected criteria further comprise the expected density or the expected piece separation.

11. The system according to claim 10, characterized in that the processor is part of the display.

12. The system according to claim 11, characterized in that the display is designed with the ability to display the value of the expected quality of fit.

13. The system according to claim 12, characterized in that the display contains a graphical user interface.

14. The system of claim 13, wherein the user can make changes to one or more settings of the agricultural seeding implement through a graphical user interface based on the value of the expected planting quality.

15. The system of claim 13, wherein the graphical user interface comprises a map, and the expected landing quality value is displayed relative to the location on the map.

16. The system according to claim 15, characterized in that the collected set of data types and the value of the expected quality of landing are stored in a memory device and / or on a non-volatile machine-readable medium in the form of a data pair including a location and the value of the expected quality of landing.

17. A system for determining the value of expected planting quality achieved with an agricultural seeding implement, comprising at least one processor and at least one storage device configured to implement a learning model, wherein the learning model is generated based on training data, wherein the learning model is trained using a method comprising the steps of: viewing multiple types of data related to planting through an agricultural seeding implement; and identifying a classifier in the form of an expected fit quality value that corresponds to the operational fit quality based on a plurality of data types; and wherein the training model is stored on one or more non-volatile machine-readable media containing commands including: real-time collection of data related to planting through an agricultural seeding implement; and generating and displaying the expected fit value for the collected data via a display; wherein the expected fit quality indicator is indicative of one or more expected criteria, wherein the one or more expected criteria further comprise the expected density or the expected piece separation.

18. The system according to claim 17, characterized in that the value of the expected quality of fit is stored in at least one storage device and / or on one or more non-volatile machine-readable media.

19. The system according to claim 17, characterized in that the commands of one or more non-volatile machine-readable media further include generating and displaying through the display proposals for improving the value of the expected landing quality.

20. The system of claim 17, wherein the plurality of data types include GPS data, environmental weather conditions, and agricultural seeding implement settings.

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