MACHINE-ENABLED FARMING

Abstract

The present teachings relate to a method for validating an agricultural farming operation prior to and/or during executing an agricultural farming operation at a geographical location using a machine, the machine being operatively coupled to a computing unit, which method comprises: —providing to the computing unit one or more signals retrieved from the machine; the one or more signals being indicative of one or more parameters related to the machine and/or to the farming operation; —determining, via the computing unit, whether any one or more of the parameters related to the machine and/or to the farming operation lie within an acceptable range or value, which acceptable range or value is specified using field specific data that are provided at a memory storage operatively coupled to the computing unit; and—generating, via the computing unit, an output signal in response to the determination; wherein the output signal is usable for validating and/or specifying the farming operation to monitor and/or control the machine. The teachings also relate to a machine, a software product and a computing unit.

Claims

1. A method for validating an agricultural farming operation prior to and/or during executing an agricultural farming operation at a geographical location using a machine, the machine being operatively coupled to a computing unit, which method comprises: providing to the computing unit one or more signals retrieved from the machine, the one or more signals being indicative of one or more parameters related to the machine and/or to the farming operation; determining, via the computing unit, whether any one or more of the parameters related to the machine and/or to the farming operation lie within an acceptable range or value, which acceptable range or value is specified using field specific data that are provided at a memory storage operatively coupled to the computing unit; and generating, via the computing unit, an output signal in response to the determination; wherein the output signal is usable for validating and/or specifying the farming operation to monitor and/or control the machine.

2. The method of claim 1, wherein the field specific data have an expiry date beyond which date the computing unit is prevented from using said field specific data.

3. The method of claim 1, wherein the farming operation involves dissemination of at least one agricultural substance.

4. The method of claim 3, wherein specifying of the farming operation comprises selection of any one or more of the at least one agricultural substance for dissemination at the geographical location, preferably the selection at least partly being performed dependent upon any one or more of the parameters, or in response to the output signal.

5. The method of claim 3, wherein specifying of the farming operation comprises determining the quantity and/or concentration of any one or more of the at least one agricultural substance for dissemination at the geographical location, preferably the quantity and/or concentration at least partly being determined dependent upon any one or more of the parameters, or in response to the output signal.

6. The method of claim 1, wherein validating the farming operation involves performing a static validation which is performed by the computing unit under static or near static conditions of the machine, such as, prior to conducting the farming operation and/or validating the farming operation involves performing a dynamic validation that involves one or more determinations that are performed by the computing unit while the machine is being used during conducting the farming operation.

7. The method of claim 1, wherein the output signal includes data specifying the farming operation, a user confirmation for executing the farming operation, a warning and/or an user overridable signal to prevent farming operation.

8. The method of claim 1, wherein the determination whether any one or more of the parameters related to the machine and/or to the farming operation lie within an acceptable range or value is triggered based on an operation activation signal from the machine.

9. The method of claim 1, wherein an output signal is generated to prevent farming operation from being conducted in response to on one or more of the parameters related to the machine and/or to the farming operation not lying within an acceptable range or value.

10. The method of claim 9, wherein the output signal to prevent farming operation is user overridable, wherein an exception signal is generated when the prevented farming operation is overridden, wherein the exception signal is provided at the memory storage and/or at a remote server.

11. The method of claim 1, wherein field specific data relates to the machine and/or to the farming operation and/or validation data and/or one or more validation rule(s).

12. The method of claim 1, wherein the farming operation is conducted, monitored and/or controlled in response to the output signal.

13. A validation device including a computing unit operatively coupled to a memory storage comprising the computer program code for carrying out the method steps of claim 1.

14. A machine for performing an agricultural farming operation at a geographical location, the machine being operatively coupled to a computing unit, and the computing unit being operatively a memory storage, the machine being adapted such that the computing unit is configured to: provide one or more signals retrieved from the machine, the one or more signals being indicative of one or more parameters related to the machine and/or to the farming operation; determine whether any one or more of the parameters related to the machine and/or to the farming operation lie within an acceptable range or value, which acceptable range or value is specified using field specific data that are provided at the memory storage; and generate an output signal in response to the determination; wherein the output signal is usable for validating and/or specifying the farming operation to monitor and/or control the machine.

15. A computer program, or a non-transitory computer readable medium storing the program, comprising instructions which, when the program is executed by a suitable computing unit operatively coupled to a memory storage, causes the computing unit to: provide one or more signals retrieved from the machine, the one or more signals being indicative of one or more parameters related to the machine and/or to the farming operation; determine whether any one or more of the parameters related to the machine and/or to the farming operation lie within an acceptable range or value, which acceptable range or value is specified using field specific data that are provided at the memory storage; and generate an output signal in response to the determination; wherein the output signal is usable for validating and/or specifying the farming operation to monitor and/or control the machine.

Description

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0112] Certain aspects of the present teachings will now be discussed with reference to the following drawings that explain the said aspects by the way of examples. Since the generality of the present teachings is not dependent on it, the drawings may not drawn to scale. Certain features shown in the drawings can be logical features that are shown together with physical features for sake of understanding and without affecting the generality of the present teachings. To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced.

[0113] FIG. 1 illustrates a machine in accordance with certain aspects of the present teachings.

[0114] FIG. 2 illustrates an aspect of the present teachings with the machine in combination with or the machine being a sprayer.

[0115] FIG. 3 illustrates more detailed aspects of the sprayer.

[0116] FIG. 4 illustrates a flow-chart in accordance with the present teachings.

[0117] FIG. 5 illustrates an embodiment of a validation device for validating agricultural farming operations.

[0118] FIG. 6 illustrates an embodiment of the method for validating the agricultural farming operation prior to and/or during execution of the agricultural farming operation.

[0119] FIGS. 7a to c illustrates different configurations of the validation device for validating agricultural farming operations.

[0120] FIG. 8 illustrates an example of a data flow between different components of the distributed computing system of FIG. 1.

[0121] FIG. 9 illustrates the headers of example data packages that may be exchanged.

DETAILED DESCRIPTION

[0122] FIG. 1 illustrates a machine 102 shown here as part of a distributed computing environment. The machine 102 is used for performing and/or conducting an agricultural farming operation on a field which comprises a plurality of geographical locations 108. The farming operation may be a treatment for a crop which comprises a crop plant 114 located at a first geographical location 108a. The farming operation may even relate to a control or eradication of weed plants.

[0123] The machine 102 may be a smart sprayer and it may include a connectivity interface 104. The connectivity interface 104 may either be a part of a network interface, or it may be separate unit. In this drawing for simplicity it is assumed that the connectivity interface 104 and the network interface are the same unit. The connectivity interface 104 is operatively coupled to a computing unit (not shown explicitly in FIG. 1). The computing unit is operatively connectable to the machine 102. The connectivity interface 104 is configured to communicatively couple the machine 102 to the distributed computing environment. The connectivity interface 104 can be configured to provide field specific data at the computing unit. Moreover, the connectivity interface 104 can also be configured to provide update data, for example collected at the machine 102 to any one or more remote computing resources 106, 110, 112 of the distributed computing environment. Any one or more of the computing resources 106, 110, 112 may be a remote server 106, which can be a data management system configured to send data to the machine 102 or to receive data from the machine 102. For example, as detected maps or as farming operation maps comprising update data recorded during the farming operation on a geographical location 108a may be sent from the machine 102 to the remote server 106, shown in this example as a cloud based service. Any one or more of the computing resources 106, 110, 112 may be a field management system 110 that may be configured to provide a control protocol, an activation code or a decision logic, or in general field specific data, to the machine 102 or to receive data, for example, update data, from the machine 102. Alternatively, or in addition, such data may be received by the field management system 110 via the remote server 106 or data management system. Any one or more of the computing resources 106, 110, 112 may be a client computer 112 that may be configured to receive client data from the field management system 110 and/or the machine 102. Such client data may include for instance farming operation schedule to be conducted on one or more fields or on the plurality of geographical locations 108 with the machine or field analysis data to provide insights into the health state of certain one or more geographical locations or field. The client computer 112 may also refer to a plurality of devices, for example a desktop computer and/or one or more mobile devices such as a smartphone and/or a tablet and/or a smart wearable device. The machine 102 may be at least partially equipped with the computing unit, or the computing unit may be a mobile device that can be connected to the machine, via the connectivity interface 104. It will be appreciated that the field management system 110 and the remote server 106 may be the same unit. The computing unit may receive the field specific data either via the client computer 112, or it may receive it directly from the remote server 106 or the field management system 110.

[0124] In particular when data such as update data is recorded by the machine 102, such data may be distributed to any one or more of the computing resources 106, 110, 112 of the distributed computing environment.

[0125] Now including reference to FIG. 2, the machine 102 may for instance include a spray device 202 including a monitoring system 212 for monitoring dissemination, for example, spray application of one or more agricultural substances. In one example, monitoring of one or more spray nozzles 204 may be done via one or more sensors, for example, sensor 214 and sensor 216. The sensors 214, 216 may be built into the fluidic system of the spray device 202. Such sensors 214, 216 are preferably placed in the common fluidic line 222 of a subset of spray nozzles 204, or for all spray nozzles 204. Together with one or more activation signals for controlling valves of the spray nozzles 204 and/or their associated tank(s), the machine 102 or spray device 202 has sufficient information to determine, e.g.: [0126] 1. deviations of the measured fluid property from the expected fluid property, and/or [0127] 2. a spray nozzle specific fluid property, and/or [0128] 3. a fluid property as measured by the sensor in the fluidic line, and/or [0129] 4. a spray nozzle position causing deviations.

[0130] Any such data, for example, the update data, may be recorded during the farming operation and transferred to e.g. the remote server 106 in real-time during the farming operation or spraying, and/or the data may be transferred after the farming operation is conducted. The latter may be the case for example if a network connection for transferring the data is not available during the farming operation. Based on update data any suboptimal or unsuitable farming operation conducted on the agricultural area or one or more geographical locations 108 may be analyzed.

[0131] FIG. 2 shows further a non-limiting example of the spray device 202, and FIG. 3 shows a more detailed example of the spray device 202. For the sake of clarity FIGS. 2 and 3 are principle sketches, where the core elements are illustrated. In particular, the fluidic set up shown is a principle sketch and may comprise more components, such as dosing or feed pumps, mixing units, buffer tanks or volumes, distributed line feeds from multiple tanks, back flow, cyclic recovery or cleaning arrangements, different types of valves like check valves, ½ or ⅔ way valves and so on. Also, different fluidic set ups and mixing arrangements may be chosen. The teachings related to this example are, however, applicable to all dissemination setups, which have at least one common fluidic line serving a subset of spray nozzles or all spray nozzles with one or more fluids. Moreover, it will be appreciated that dissemination of one or more agricultural substances is non-limiting to the generality of the present teachings, as the teachings may be applied also to farming operations that do not involve a dissemination. Further moreover, those skilled in the art will realize that other farming operations such as aquatic farming operations being conducted via a suitable machine operatively connected to a computing unit pursuant to the present teachings are also possible as outlined in the present disclosure.

[0132] The machine 102 of FIGS. 2 and 3 may comprise a tractor (not shown) operatively attached or mounted with a spray device 202 for disseminating an agricultural substance, for example application of a pesticide, a herbicide, a fungicide or an insecticide on the geographical location 108a. The spray device 202 may be releasably attached or directly mounted to the tractor. The spray device 202 comprises a boom with one or more spray nozzles 204 arranged along the boom of the spray device 202. In FIG. 3, a plurality of such spray nozzles 204 is shown as spray nozzles 304a-c. The spray nozzles 204 or 304a-c may be arranged fixed or movably along the boom in regular or irregular distances. Each of the spray nozzles 304a-c may be arranged together with a respective controllable valve 306a-c to regulate dissemination or fluid release of the agricultural substance from the spray nozzles 304a-c to any one or more the geographical locations 108a-d.

[0133] One or more tanks 208a-c for containing one or more agricultural substances are shown in fluid communication with the spray nozzles 304a-c through common fluidic line 222, which distributes contents of any of the tanks 208a-c or a mixture of the contents as released from the tanks 208a-c to the spray nozzles 304a-c. Each of the tanks 208a-c holds one or more agricultural substances for the fluid mixture to be released at any one or more of the geographical locations 108a-d. This may include chemically active or inactive ingredients like a herbicide mixture, individual ingredients of a herbicide mixture, a selective herbicide for specific weeds, a fungicide, a fungicide mixture, ingredients of a fungicide mixture, ingredients of a plant growth regulator mixture, a plant growth regulator, water, oil, or any other formulation agent. Each of the tanks 208a-c may further comprise a respective tank valves 306a-c for regulating the dissemination or fluid release from the respective of the tanks 208a-c to the respective fluid lines 308a-c. Such arrangement allows to control the mixture released at any one or more of the geographical locations 108a-d in a targeted manner depending on the conditions sensed at the respective and/or other of the geographical locations 108a-d.

[0134] The dissemination is based on one or more signals retrieved from the machine 102 and/or the spray device 202. Some or all of the signals may be retrieved or obtained, for example, by sensing at the spray device 202 via a detection system 220. The detection system 220 may comprise multiple sensors or detection components 218 arranged along the boom. The detection components 218 may be arranged fixed or movable along the boom in regular or irregular intervals. The detection components 218 may be configured to sense one or more conditions at the geographical locations 108a-d, preferably at the geographical location where the farming operation is conducted. The detection components 218 may be, or they may include an optical detection component for providing an image at the geographical location. Certain optical detection components 218 that are suitable for the present teachings include multispectral cameras, stereo cameras, Infrared (“IR”) cameras, Charge-coupled device (“CCD”) cameras, hyperspectral cameras, ultrasonic or light detection and ranging (“LIDAR”) system cameras. Alternatively, or additionally, the detection components 218 may include further sensors to measure humidity, light, temperature, wind or any other suitable condition on the geographical location.

[0135] The detection components 218 may, for example, be arranged perpendicular or nearly perpendicular to the movement direction of the spray device 202 and in front of the spray nozzles 304a-c (e.g., seen from drive direction). In the example shown in FIG. 2, the detection components 218 are optical detection components and each of the detection components 218 is associated with a respective of the spray nozzles 204. Now with reference also to FIG. 3, the detection components 218 can be associated such that the respective field-of-view of the respective sensor comprises or at least overlaps with the spray profile 314 of the respective nozzle, e.g., spray nozzle 304c, at that geographical location once the spray nozzle 304c reached the respective position. In other arrangements each of the detection components 218 may be associated with more than one of the spray nozzles 304a-c, or even more than one detection components 218 may be associated with each of the spray nozzles 304a-c.

[0136] Now with reference to FIG. 3 along with FIG. 2, as a more detailed example of the spray device 202, it shows the detection components 218, as well as actuators e.g., tank valves 306ac and nozzle valves 310a-c that are communicatively coupled to a control system or control unit 210. In FIG. 2, the control unit 210 is shown located in a main sprayer housing 206, from where it may be operatively coupled via the connectivity interface 104 to the respective components such as sensors and actuators. The connection may be a wired connection to some or all of the components, or it may be a wireless connection. Accordingly, the connectivity interface 104 may allow wired and/or wireless connections. In some cases, it may be more than one control unit 210 or system that may be distributed in the machine 102 and/or the main sprayer housing 206 and communicatively coupled to the detection components 218, the tank valves 306a-c and/or the nozzle valves 310a-c. The control unit 210 may at least partially be the computing unit. Accordingly, the computing unit may either be the control unit 210, or the control unit 210 may be a part of the computing unit. For example, the control unit 210 may communicatively connect with a processing unit of the machine 102 to collectively form and function as the computing unit. The connection may be established via the connectivity interface 104, wired and/or wireless. The processing unit of the machine 102 may be a permanently installed computer or it may be a mobile device that can be detachably connected via the connectivity interface 104. In other cases, the control unit 210 may be a detachable device such as a mobile device that can be connected to the machine 102 or the spray device 202.

[0137] The computing unit or the control unit 210 is configured to analyze one or more signals retrieved from the spray device 202 and/or the machine 102. The signals may be retrieved from the detection system 220 that is operatively connected with the machine 102 and/or the spray device 202. For the sake of simplicity, the machine 102 and the spray device 202 will be considered as one apparatus, namely the machine 102, with an assumption that in this example the spray device 202 is attached to the machine 102 for conducting the farming operation. Similarly, control unit 210 and computing unit will be used interchangeably or as simply as control unit 210. Accordingly, the control unit 210 is operatively connected to a memory storage.

[0138] The signals are indicative of one or more parameters related to the machine 102 and/or to the farming operation, i.e., the spraying in this example.

[0139] In response to the analysis of the one or more signals, the computing unit or control unit 210 is configured to determine whether any one or more of the parameters lie within an acceptable range or value. The range or value is specified using the field specific data that are provided at the memory storage operatively coupled to the control unit 210. The field specific data may be provided from the remote server 106, either directly to the control unit 210, or via a download at the client computer 112 and then a subsequent transfer, wired or wireless via the connectivity interface 104 to the control unit 210.

[0140] In response to the determination, the control unit 210 is configured to generate an output signal which is usable for validating and/or specifying the farming operation. The control unit 210 may thus validate if a particular farming operation may be conducted or not, and/or the control unit 210 may specify the farming operation. The farming operation can hence also be controlled via the control unit 210.

[0141] The field specific data may be specific to the machine 102, and usable for validating and/or specifying the farming operation. For example, nozzle type or characteristics, and working width. According to an aspect, the field specific data may be weather related, and usable for validating and/or specifying the farming operation. For example, temperature, wind characteristics, precipitation, humidity, solar radiation, bee activity. According to an aspect, the field specific data may be task related, and usable for validating and/or specifying the farming operation. For example, geographical characteristics such as coordinates and/or topographical data of one or more geographical locations or the field, which can provide information related to any one or more of: location, boundary, crop, variety, crop properties, prior crop, tillage system, yield expectation, disease status, and their likes, time window for allowable farming operation, agricultural substance data, dosage, distribution of prior agricultural substances in the field or at one or more geographical locations in the field, recommendation data based on disease status, biomass, weather or legal requirements, execution related data for the farming operation, such as speed, optimal path, overlap, gaps, acceleration, end effector unit selection, for example nozzle selection.

[0142] During, or even prior to, the farming operation, the control unit 210 is configured to monitor and/or control the detection components 218 and/or any of the tank valves 306a-c and/or the nozzle valves 310a-c respectively, according to control logic that is provided in the field specific data. The control unit 210 may comprise multiple modules. For example, one module is configured to control the detection components 218 to collect data such as an image or snapshot of measurements at the geographical location. A further module may be configured to analyze the collected data such as the image or measurements for making determination using the field specific data. The further module may even be configured to derive parameters for the tankand/or nozzle valve control. There may even be further modules for controlling the tank valves 306a-c and/or the nozzle valves 310a-c based on the determination or the output signal.

[0143] In addition to the control unit 210, the spray device 202 may also comprise a monitoring system 212, which may be any processing device with respective interfaces suitable to receive data measured by the sensor 214 and/or sensor 216 and/or from the control unit 210. In particular, the monitoring system 212 may be configured to receive data from the sensor 214 arranged to measure a fluid property present in the common fluidic line 222. As shown in FIG. 3, the common fluidic line 222 may serve multiple spray nozzles 304a-c with a fluid mixture from the tanks 208a-c. To control the amount of fluid released from the tanks 208a-c, tank valves 306a-c are associated with each of the tanks 208a-c respectively. Depending on the specific conditions sensed on one or more of the geographical locations, the control unit 210 determines characteristics or parameters of the farming operation at the specific geographical location. For example, a specific composition of an agricultural substance or chemical agent to be disseminated or released at the geographical location. Accordingly, the control unit 210, in response to the output signal, provides a respective activation signal to the tank valves 306a-c to provide respective amount of substance to the fluid lines 308a-c respectively. In the example of FIG. 3 one or more of the fluid streams, via respective fluid lines 308a-c, from the tanks 208a-c are mixed in the common fluidic line 222 where the mixture is then fed via distribution lines 302a-c to the individual spray nozzles 304a-c. Each of the spray nozzles 304a-c includes a respective of the nozzle valves 310a-c, which is triggered for spraying depending on the activation signal provided by the control unit 210. Depending on the desired dissemination or application rate provided by the activation signal the application nozzles 312a-c are controlled to spray the respective amount of agricultural substance per activated spray nozzles 304a-c onto the geographical location.

[0144] For monitoring the operation of individual spray nozzles 304a-c, sensors monitoring fluid properties can be used. For example, the fluid property sensed in the common fluidic line 222 may be a fluid flow as measured by sensor 214. Further sensors may be used to measure, continuously or intermittently, other fluid properties such as composition and/or temperature and/or pressure of the applied fluid. Such sensors 316a-c may be placed at each of the respective spray nozzles 304a-c as shown in FIG. 3 or even also in the common fluidic line 222 to monitor the composition of the mixture flowing thereto.

[0145] The data from the geographical location where the farming operation is conducted may be recorded at the memory storage and/or transmitted directly to the remote server 106. The update data may serve as a basis for providing a new field specific data at the memory storage for validating and/or specifying, or even conducting a future farming operation.

[0146] The update data may comprise any one or more of, setpoint for dissemination rate, such as application rate, actual dissemination rate, work state, pressure, work area, working width, tank fill level, composition, pH, status of sections (on/off), geometry, position data, date/time, speed, motor rpm, fuel consumption, environmental sample data, and environment sensor data such as, temperature, wind, precipitation, humidity, solar radiation.

[0147] FIG. 4 shows, as a flow-chart 400, the method for performing the agricultural operation at the geographical location using the machine. In block 402, one or more signal retrieved from the machine are analyzed via the computing unit; the one or more signal being indicative of one or more parameter related to the machine and/or to the farming operation. In block 404, it is determined, via the computing unit, whether one or more of the parameters lie within an acceptable range or value. The range or value is specified using the field specific data that are provided at a memory storage operatively coupled to the computing unit. In block 406, it is generated, via the computing unit, an output signal in response to the determination of block 404. The output signal is usable for validating and/or specifying the farming operation.

[0148] FIG. 5 shows an embodiment of a validation device 500 for validating agricultural farming operations.

[0149] The validation device 500 includes a computing unit 502 with one or more processors, a memory storage 504, a network interface and a connectivity interface. The memory storage 504 may include one or more storage units. The storage unit may be persistent or non-persistent storage. The memory storage 504 may include persistent and/or non-persistent storage. The network interface 506 may be configured to provide data related to the process of validating agricultural farming operations, such as field specific data, to or from the remote server 508 such as the cloud server. The connectivity interface 510 may be configured to provide data related to the process of validating agricultural farming operations, such as signals retrieved from the machine 512 being indicative of one or more parameters related to the machine and/or to the farming operation or output signals usable for validating and/or specifying the farming operation, to or from the machine 512. In this context providing data may include to send, to retrieve or to receive data.

[0150] FIG. 6 shows an embodiment of the method for validating the agricultural farming operation prior to and/or during execution of the agricultural farming operation.

[0151] Via the network interface the field specific data may be provided at the memory storage 504 in step 514, e.g. via the network interface 506 operatively connected to the computing unit 502. The field specific data may be provided from the remote server 508 prior to performing the farming operation on the field. The field specific data may be transferred before the farming operation is conducted. This way the availability of field specific data is ensured such that the machine can operate even when the connection to the server is lost. If connection to the server is available, then also updated field specific data may be transfer during the farming operation. Field specific data may be an immutable set of data defined for a planned operation task and generated on planning of the task. Alternative field specific data may be an immutable set of data defined for a snapshot of the current state of the field specific data. In the latter case field specific data may be updated via the remote server, when field conditions or task planning changes. Hence the field specific data may continuously change on the remote server. In case of a planned task, the field specific data may be synchronized with the machine as soon as a connection to the server is available prior to performing such planned task. If there is no planned task available, the field specific data may be retrieved ad hoc as a snapshot from the current field specific data as stored by the remote server, if the server connection is available. Once a complete set of data is retrieved by the machine, either planned or ad hoc, the operation may start including prior validation. This way it is possible to perform validation without a connection to the server. This is particularly relevant for agricultural fields in rural areas without network.

[0152] Field specific data may include data related to the machine and/or to the farming operation. Field specific data may include validation data and/or one or more validation rules for determining whether a certain farming operation may be conducted or not. Said validation data and/or one or more validation rules may for example be provided as a computer logic data or computer instructions for the computing unit 502. Hence, the field specific data may at least partially include computer control logic data for validating one or more farming operations.

[0153] Prior to start of the farming operation the computing unit 502 retrieves in step 516 one or more signals indicative of one or more parameters related to the machine and/or to the farming operation e.g. via the connectivity interface 510. Step 516 may be triggered by a farming operation activation signal. Such operation activation signal may be depending on the machine: a spray operation activation signal in case of a sprayer, a tillage operation signal in case of a tiller or a harvest operation signal in case of a harvester.

[0154] In step 516, the computing unit 502 retrieves one or more signals being indicative of one or more parameters related to the machine and/or to the farming operation. The operation activation signal may be provided to the computing unit 502 in step 516 and based on the operation activation signal the method for validating farming operation may be initiated. In addition to the operation activation signal further signals may be provided to the computing unit 502. Such signals may include machine related signals such as position of the machine, setpoint, calibration, pre-set calibration intervals, result of previous calibration runs, working parts, setup of working parts, working width, tank fill level, position, date, time or the liken. Such signals may include application related signals such as time stamp of the operation activation signal, measured field conditions such as temperature, wind, humidity, precipitation and/or solar radiation, or the like.

[0155] In step 518 the one or more signals retrieved from the machine are provided to the computing unit or analysed by the computing unit. The computing determines based on the field specific data, whether any one or more of the parameters lie within an acceptable range or value. Field-specific data may be provided to the computing unit from the memory storage. The field specific data may include the field location, application data, such as application map, the timing slot of application, (legal) distance requirements, the crop protection product recommendation, driving patterns/instructions, and validation data, validation rules, fall back/correction parameters, information on serverity of consequence in case of violation. Field specific data may also be influenced by or may contain user preferences.

[0156] The field specific data may include validation data and/or rules with instructions validating the stored application instructions when the machinery is started for application on the field. Such validation may be based on static or dynamic validation factors. In particular, the validation data and/or one or more validation rules provided via the field specific data may be executed by the computing unit 502. Such validation data and/or validation rules may include: [0157] The field specific data may include an expiration threshold such as an expiration time span or an expiration date. It may be validated that the field specific data based on which the analysis by the computing unit 502 is executed has not been expired. [0158] The field specific data may include operation or task related validation data. Such validation data may include field conditions such as temperature or wind conditions. [0159] The field specific data may include operation or task related rules. For instance the operation or task may be attached to time ranges and/or time slots of the day. Such rules may further be connected to weather conditions present on the specific field such as temperature, precipitation, or wind. Depending on the time and sensor measurements executed in response to the operation activation signal and retrieved as signals from the machine, operation or task related rules may be validated prior to executing farming operation by the machine 512.

[0160] In other words, once the machine signals the start of the operation, e.g. via a user interaction, via machine signals or automatically via location coordinates once the machine arrives at the field location, a validation loop may be started. Such validation loop may be based on static validation factors including farming operation specific validation and/or machine specific validation. Farming operation specific validation may include for the application of a crop protection product at least one validation rule based on the application map applicable for the respective field, the time of application, the crop protection products to be applied, the weather conditions on the field expected or measured prior to application of the crop protection product. Machine specific validation may include fill levels of tanks sufficient for the prospective application, valves and nozzles operational and/or check of latest calibration of valves and nozzles still valid.

[0161] In step 520 it may be determined, if the one or more parameters lie within an acceptable range.

[0162] If the one or more parameters lie within an acceptable range, output signals usable for validating and/or specifying the farming operation are provided in step 522 to the machine 512 via the connectivity interface 510 to start the farming operation.

[0163] If the one or more parameters do not lie within an acceptable range, output signals usable for stopping the farming operation are provided in step 524 to the machine 512 via the connectivity interface 510 to stop the farming operation.

[0164] Once the validation is completed and successful the machine may receive an output signal. Such output signal may be a validation signal signifying the readiness of the machine 512 for performing the farming operation. In one embodiment such output signal may be displayed on a display. In case of successful validation, a green light may be output via a display of the machine 512 and the operation may start.

[0165] If the validation is completed and not successful, e.g. because the timing slot is not valid, output signal may signify that e.g. the operation data does not comply with the situation on the field. Similar signals may be output for the hardware specific validation providing a signal that the hardware is not ready for operation. The machine operation may be stopped automatically.

[0166] Output signals may be provided either to a display of the machine 512 or to an intermediary device such as an additional hardware device or a smart phone.

[0167] In some instances, the farmer may be allowed to overwrite the unsuccessful validation and continue operation despite the warning. The output signal may include further metadata, such that the operator may be informed via a display about possible ramifications (i.e suboptimal efficacy, loss of yield, loss of warranty). In such case the operator may have to actively confirm such action. Such confirmation may be stored in the memory storage 504, any intermediary device and/or the remote server once the machine 512 connects to the server.

[0168] If the validation is completed and not successful, the output signal may include data associated with adjusted operation settings. For instance: application is herbicide, temperature is too high, validation failed, options to increase herbicide dosage, water level or lowered spray nozzles will be provided via output signal. Operation will be started, if a confirmation signal for one of the options is retrieved.

[0169] Validation may be clustered into three categories: green for valid operation instructions, yellow for operation instructions that may impact operation success and red for operation instructions that cannot be validated due to the high risk of negative impact. Similar options for adjusting the settings may be flagged. Such validation may be operation measure specific and prepared by the server as part of the field specific data transferred or stored directly by the validation device 500. If no field specific validation data or validation rule may be available (because no connection to the server) and the operator wants to perform an operation, default operation values may be used and the operator may be notified about such non-validated default mode.

[0170] In addition or alternatively to the above embodiment, the computing unit 502 may retrieve one or more signals indicative of one or more parameters related to the machine and/or to the farming operation, analyzes the one or more signals retrieved from the machine 512 and determines based on the field data, in particular the validation data and/or one or more validation rules, whether any one or more of the parameters lie within an acceptable range or value and if the one or more parameters lie within an acceptable range, provides output signals usable for validating and/or specifying the farming operation to the machine via the connectivity interface. This way it is enabled to control and/or monitor the farming operation not only prior to starting the farming operation, but also during performance of the farming operation.

[0171] For instance during the performance of the farming operation, data from the machine may be continuously retrieved. Such data may be retrieved from machine sensors, field sensors, machine implements sensors or other machine sensors. The data may be analyzed and checked based on the field specific data, in particular the validation data and/or one or more validation rules, during the farming operation. For example: [0172] Check if application rate is correct for current part of the field (setpoint and actual application rate are considered) [0173] Check if sections are correctly set (for overlapping, distance requirements and on/off applications) [0174] Check if temperature is within defined ranges [0175] Check if wind is within defined ranges (also dependent on product, nozzles, driving speed) [0176] Check if driving speed is within defined ranges (also dependent on nozzles and pressure and application rate->all parameters need to be aligned to have good droplet size) [0177] Check if date and time for performing the farming operation is within defined ranges for the current field

[0178] The validation loop may include dynamic factors that can be validated during application operation on the field. In that case sensors of the machinery deliver data such as weather data, machinery data (e.g. speed, pressure in the nozzle system, . . . ) or other data available on-board of the machine during operation in the field from in-field sensors or in case of server connectivity being present from the server may be provided. The validation instructions may in such case include a tailored set of validation parameters relevant for the specific operation and respective operation ranges. E.g. if the temperature on the field rises to a value higher than allowed for a certain period of time the validation instructions may lead to a respective warning triggered by the system. Similarly, if wind speed increases over certain period of time the validation instructions may lead to a respective warning triggered by the system. Such dynamic warning may be clustered in line with static warnings and may trigger active confirmation screens for the user.

[0179] In any case the on-field operation data such as as-applied-maps, overwritten warnings, user interaction, validation results, sensor readings . . . will be stored on memory sorage 504 and transferred to the server. Once the server receives information relating to overwritten warnings, a further process may be triggered that assesses the impact of such overwrite. For instance if the farmer has overwritten red warnings, the server system may trigger a notification to the farmer signifying the cause and optionally the loss of warranty. Further for instance if the farmer has overwritten yellow warnings, the server system may trigger a notification to the farmer signifying the cause for the yellow warning and an estimation of a worst-case impact on application success. The field may be monitored regarding such specific impact and should it materialize no warranty incident may be triggered. In any other case warranty incident may be triggered. The additional insights gathered from this process may also influence or be contained in future field specific data transferred to the machinery. E.g if in a previous application a warning was overwritten this may impact the field specific data for a future application.

[0180] FIGS. 7a to c show different configurations of the validation device for validating agricultural farming operations.

[0181] The validation device 500 of FIG. 7a is a mobile device configured to retrieve field specific data from the remote server, to run the method for validating agricultural farming operations and to provide output signals usable for validating and/or specifying the farming operation. In such an embodiment a mobile connection interface of the machine 512 may be configured to send or obtain data from the mobile device 500 or to retrieve or receive data from the mobile device 500. The interface 510 enabling connection of the mobile device 500 with the machine 512 may be based on a wireless connectivity interfaces such as Wifi or Bluetooth. The mobile device 500 may be communicatively connected to the machine 512 via wireless local connection (Bluetooth, wifi, . . . ). The mobile connection interface of the machine 512 may be connected to the machine hardware via a wired connection such as a CAN BUS using protocols such as ISOBUS and J1939. Serial or other connections and other protocols can also be use for a connection of the mobile device 500 to the machine 512. The mobile device 500 can further provide extended functionality to the machine 512. Such functionalities include the method for validating farming operations as well as additional functionalities such as displaying data and allowing for user interaction via a HMI such as a touch screen. For that the mobile device 500 may include memory storage 504 configured to provide the field specific data to the computing unit 502, computing unit 502 configured to execute the method for validating farming operations and to provide output signals usable for validating and/or specifying the farming operation, a display 526 configured to display output signals usable for validating and/or specifying the farming operation and the interfaces 506, 510 to the remote server 508 or the machine 512 respectively.

[0182] The validation device 500 of FIG. 7b is an embedded device configured to retrieve field specific data from the remote server, to run the method for validating agricultural farming operations and to provide output signals usable for validating and/or specifying the farming operation. Such embedded device may be connected to the machine via connectivity interfaces and to the remote server via a network interface. The connectivity interface to the machine may be based on a CAN BUS and the network interface may be based on Bluetooth, Wifi or a cellular network.

[0183] The embedded device of FIG. 7b is a dedicated device configured to retrieve field specific data from the remote server, to run the method for validating agricultural farming operations and to provide output signals usable for validating and/or specifying the farming operation. Additional functionalities such as displaying data and allowing for user interaction via a HMI may be provided by additional hardware components. For instance, a HMI including a display may be provided by a separate mobile device.

[0184] The embedded device of FIG. 7c is a fully integrated device configured to perform the method for validating farming operations. In this embodiment existing hardware on the machine may be updated with software instructions to perform the method for validating farming operations. The fully integrated device may already provide for the required interfaces to perform the method. The fully integrated device may include the connectivity interface to control unit(s) of the machine, the HMI of the machine and the network interface. This way existing hardware may be used and extended with software that retrieves data from the server, runs the validation logic and displays on the user interface.

[0185] The validation device of FIG. 7c is a partially embedded device configured to run the method for validating agricultural farming operations and to provide output signals usable for validating and/or specifying the farming operation. The mobile device is configured to retrieve field specific data from the remote server and provide it to the partially embedded device. A mobile connection interface of the machine or the validation device may be configured to send or obtain data from the mobile device or to retrieve or receive field specific data from the mobile device.

[0186] As lined out above different hardware configurations may be used to implement the validation device. For instance hardware already available on the machine may be used or an additional validation device that can be connected to the machine, like a sprayer or a seeder or any other agricultural machine used for farming operations may be used. The validation device may include a memory storage, a connectivity interface to the machinery such as the implement, the tractor or sensors, a network interface to the remote server and the computing unit. The validation device may be fitted to the machine as an additional hardware device, built in as stationery part or implemented in a separate mobile device. The communications to the machine may be be based on publicly available protocols, such as ISOBUS and J1939, or any other suitable protocols. In the case, where connectivity interfaces for the validation device are needed, near field communication such as Bluetooth or far field communication protocols may be used. To enable farming operation for a specific field, field-specific data including field specific operation instructions may be transferred from the server to the memory storage of the validation device. Such transfer may be conducted directly or via an intermediate device such as an additional dongle or a smart phone.

[0187] FIG. 8 shows an example of a data flow between different components of the distributed computing system of FIG. 1.

[0188] Before the farmer intends to execute the farming operation, field specific data may be transferred from the remote server 508 to validation device 500, in particular the memory storage 504 of the validation device 500. As shown in FIGS. 7a to 7c the validation device may be configured in different hardware set-ups. Such data transfer is signified by reference numeral 600.

[0189] FIG. 9 illustrates the header of an example data package 700 that may be exchanged in step 600. Field-specific data may include a field data related to the field location the farming operation is to be performed. This may include data related to the position of the field such as longitude and latitude values e.g. in WGS84 combined with a field boundary and buffer zones applicable to the field. Field-specific data may include a machine data associated with the machine and specifying e.g. a machine type, a machine setup such as in case of a sprayer number of tanks, valves or nozzles, or calibration data related to e.g. calibration intervals or results of previous calibrations. Field-specific data may include a farming operation data related to the operation to be performed on the field. Such operation data may include for instance for the application of a crop protection product an identifier for the cop protection product to be applied, a time range for performing the application, field condition ranges for performing the application, a spatially resolved application map and/or driving instructions.

[0190] Field specific data may include validation data and/or validation rules 702. The validation data and/or validation rules may relate to parameters related to the machine and/or to the farming operation. The validation data and/or validation rules may be based on parameters related to the machine and/or to the farming operation. The validation data and/or validation rules may indicate an acceptable range or value for the parameters related to the machine and/or to the farming operation. The validation data and/or validation rule may include instructions for validating the stored field data as soon as the machinery is started for performing the agricultural operation. Such validation may be based on static or dynamic validation factors.

[0191] On activation of the machine 512 to perform the farming operation, the operation activation signal may be provided from the machine 512 to the validation device 500. Such data transfer is signified by reference numeral 602.

[0192] On retrieval of the operation activation signal, the validation device 500 may initiate the method for validating farming operations. On initiation the field specific data, in particular the validation data and/or validation ruled stored in the memory storage 504 may be loaded to the computing device. The validation device may request from the machine 512 one or more signals indicative of one or more parameters related to the machine and/or to the farming operation. Such data transfer is signified by reference numeral 604.

[0193] On retrieval of the request, the machine 512 may provide one or more signals indicative of one or more parameters related to the machine and/or to the farming operation to the validation device 500. Such data transfer is signified by reference numeral 606. FIG. 9 illustrates the header of an example data package 704 that may be exchanged in step 606.

[0194] On retrieval of one or more signals indicative of one or more parameters related to the machine and/or to the farming operation, the validation device 500 determines, via the computing unit 502, whether any one or more of the parameters lie within an acceptable range or value, which range or value is specified using field specific data. Based on such determination the output signal usable for validating and/or specifying the farming operation is generated. The output signal may be provided to the machine 512. Such data transfer is signified by reference numeral 608. FIG. 9 illustrates the header of an example data package 706 that may be exchanged in step 608.

[0195] The output signal may be associated with a validation signal signifying the start of the farming operation. The output signal may be associated with operating parameters to control operation of the machine. The output signal may be associated with operating parameters to control operation of the machine associated with a confirmation request to be confirmed by an operator of the machine. The output signal may be associated with a denial signal signifying to stop or not start farming operation with the machine.

[0196] On retrieval of the output signal by the machine for performing the farming operation, the machine may control farming operation based on the retrieved output signal. If the output signal provides the machine with a validation or conditional validation, the control system of the machine 512 may operate according to the provided operation parameters. If the output signal provides the machine with no validation or conditional validation, the control system of the machine 512 may block performance of the farming operation.

[0197] During performance of the farming operation, the machine 512 may provide one or more signals indicative of one or more parameters related to the machine and/or to the farming operation to the validation device 500. Such data transfer is signified by reference numeral 610. On retrieval of such signals, the validation device may generate respective output signals and provide such output signals to control operation of the machine 500 during performance of the farming operation. Such data transfer is signified by reference numeral 612. This way it can be ensured that the farming operation by way of control of machine 500 performing the farming operation is performed in a robust and reliable manner.

[0198] The word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. A single processor or controller or other unit may fulfil the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Any reference signs in the claims should not be construed as limiting the scope.

[0199] Various examples have been disclosed above for a method for performing an agricultural farming operation at a geographical location using a machine operatively coupled to a computing unit; a machine for performing the agricultural farming operation; a computer software product implementing any of the relevant method steps herein disclosed; a computing unit comprising the computer program code for carrying out the method herein disclosed; and a computing unit operatively coupled to a memory storage comprising the computer program code for carrying out the method herein disclosed. Those skilled in the art will understand however that changes and modifications may be made to those examples without departing from the spirit and scope of the accompanying claims and their equivalents. It will further be appreciated that aspects from the method and product embodiments discussed herein may be freely combined.

[0200] Summarizing and without excluding further possible embodiments, at least the following embodiments listed as clauses may be envisaged:

Clause 1. A method for performing an agricultural farming operation at a geographical location using a machine, preferably a method for validating an agricultural farming operation prior to and/or during executing an agricultural farming operation at a geographical location using a machine, the machine being operatively coupled to a computing unit, which method comprises: [0201] analyzing, via the computing unit, or providing to one or more signals retrieved from the machine; the one or more signals being indicative of one or more parameters related to the machine and/or to the farming operation; [0202] determining, via the computing unit, whether any one or more of the parameters related to the machine and/or to the farming operation lie within an acceptable range or value, which acceptable range or value is specified using field specific data that are provided at a memory storage operatively coupled to the computing unit; and [0203] generating, via the computing unit, an output signal in response to the determination; wherein the output signal is usable for validating and/or specifying the farming operation preferably to monitor and/or control the machine.
Clause 2. The method of clause 1, wherein the field specific data have an expiry date beyond which date the computing unit is prevented from using said field specific data.
Clause 3. The method of clause 1, wherein the field specific data are provided via a data transfer from a remote server.
Clause 4. The method of clause 3, wherein the computing unit is operatively coupled to a network interface, and wherein data transfer is performed via the network interface.
Clause 5. The method of any of the above clauses, wherein the computing unit is operatively coupled to a connectivity interface.
Clause 6. The method of clause 5, wherein the network interface and the connectivity interface are the same device.
Clause 7. The method of any of the above clauses, wherein the farming operation involves dissemination of at least one agricultural substance.
Clause 8. The method of clause 7, wherein specifying of the farming operation comprises selection of any one or more of the at least one agricultural substance for dissemination at the geographical location, preferably the selection at least partly being performed dependent upon any one or more of the parameters, or in response to the output signal.
Clause 9. The method of clause 7 or clause 8, wherein specifying of the farming operation comprises determining the quantity and/or concentration of any one or more of the at least one agricultural substance for dissemination at the geographical location, preferably the quantity and/or concentration at least partly being determined dependent upon any one or more of the parameters, or in response to the output signal.
Clause 10. The method of any of the above clauses, wherein specifying of the farming operation comprises determining at least one distance value for conducting the farming operation.
Clause 11. The method of any of the above clauses, wherein validating of the farming operation comprises determining whether the farming operation can be safely and/or efficiently conducted.
Clause 12. The method of any of the above clauses, wherein validating of the farming operation comprises determining whether the machine is adequately equipped for conducting the farming operation.
Clause 13. The method of any of the above clauses, wherein validating the farming operation involves performing a static validation which is performed by the computing unit under static or near static conditions of the machine, such as, prior to conducting the farming operation.
Clause 14. The method of any of the above clauses, wherein validating the farming operation involves performing a dynamic validation that involves one or more checks or determinations that are performed by the computing unit while the machine is being used during conducting the farming operation.
Clause 15. The method of any of the above clauses, wherein a location of the geographical location is determined via a geolocation module operatively coupled to the computing unit.
Clause 16. The method of any of the above clauses, wherein the output signal is provided to a Human Machine Interface (“HMI”), operatively coupled to the computing unit, for communicating the validated and/or specified farming operation.
Clause 17. The method of any of the above clauses, wherein the farming operation is prevented from being conducted in response to the output signal.
Clause 18. The method of clause 17, wherein the prevented farming operation is user overridable.
Clause 19. The method of clause 18, wherein an exception signal is generated via the computing unit when the prevented farming operation is overridden.
Clause 20. The method of clause 19, wherein the exception signal is provided at the memory storage and/or at the remote server.
Clause 21. The method of any of the above clause 1 to clause 16, wherein the farming operation is conducted and/or controlled in response to the output signal.
Clause 22. The method of clause 21, wherein the farming operation is conducted and/or controlled via the computing unit, preferably by the computing unit controlling at least one actuator and/or at least one end effector unit related to the machine.
Clause 23. The method of clause 21 or clause 22, wherein the computing unit provide update data at the memory storage and/or to the remote server, the update data comprising any of the one or more signals and/or any of the one or more parameters related to the geographical location, and/or the validation and/or specification of the farming operation at the geographical location.
Clause 24. The method of clause 20 and clause 23, wherein the exception signal is provided as a part of the update data.
Clause 25. The method of clause 23 or clause 24, wherein the update data is used for generating updated field specific data usable by the computing unit for a future farming operation at or around the geographical location.
Clause 26. A machine for performing an agricultural farming operation, the machine being configured according to any of the above method clauses, and the machine being configured such to perform the method steps according to any of the above clauses.
Clause 27. A computer program, or a non-transitory computer readable medium storing the program, comprising instructions which, when the program is executed by a suitable computing unit, cause the computing unit to carry out the method steps of any of the above method clauses.
Clause 28. A machine for performing an agricultural farming operation at a geographical location, the machine being operatively coupled to a computing unit, and the computing unit being operatively a memory storage, the machine being adapted such that the computing unit is configured to: [0204] analyze one or more signals retrieved from the machine; the one or more signals being indicative of one or more parameters related to the machine and/or to the farming operation; [0205] determine whether any one or more of the parameters lie within an acceptable range or value, which range or value is specified using field specific data that are provided at the memory storage; and [0206] generate an output signal in response to the determination; wherein the output signal is usable for validating and/or specifying the farming operation.
Clause 29. A computer program, or a non-transitory computer readable medium storing the program, comprising instructions which, when the program is executed by a suitable computing unit operatively coupled to: a memory storage, and a machine for performing an agricultural farming operation at a geographical location, causes the computing unit to: [0207] analyze one or more signals retrieved from the machine; the one or more signals being indicative of one or more parameters related to the machine and/or to the farming operation; [0208] determine whether any one or more of the parameters lie within an acceptable range or value, which range or value is specified using field specific data that are provided at the memory storage; and [0209] generate an output signal in response to the determination; [0210] wherein the output signal is usable for validating and/or specifying the farming operation.
Clause 30. A computing unit comprising the computer program code for carrying out the method steps of any of the above method clauses.
Clause 31. A computing unit operatively coupled to a memory storage comprising the computer program code for carrying out the method steps of any of the above method clauses.