Agronomic variation and team performance analysis

• US 10,311,527 B2
• Filed: 11/18/2014
• Issued: 06/04/2019
• Est. Priority Date: 01/14/2014
• Status: Active Grant

• Current Assignee: Deere & Company
• Original Assignee: Deere & Company
• Inventors: Pfeiffer, Dohn W., Deutsch, Timothy A., Reid, John F., Foessel, Alex D.
• Primary Examiner(s): Kuddus, Daniel A
• Application Number:
  US14/546,725
• Publication Number:
  US 20150199775A1
• Time in Patent Office: 1,659 Days
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G06Q 50/02 Agriculture; Fishing; Forestry; Mining

Abstract

Performance information indicative of operator performance of a mobile machine is received. A performance opportunity space is identified, indicative of possible performance improvement. Savings identified in the performance opportunity space are quantified.

Claims

1. A computing system, comprising:

a hardware processor;

a variation opportunity space engine configured to control the hardware processor to identify an agronomic variation opportunity based on agronomic variation data indicative of variation of sensed agronomic parameters that are sensed by sensors on a mobile machine as the mobile machine moves across a piece of land; and

a prescriptive component system comprising;

an opportunity-to-component map that maps the agronomic variation opportunity to a set of prescriptive machine configuration components that modify a configuration on the mobile machine, a set of prescriptive machine control components that modify the mobile machine to automate portions of the control of the mobile machine, and a set of prescriptive data gathering components that modify operation of the sensors on the mobile machine to change a definition with which the agronomic parameters are sensed; and

an opportunity-to-component mapping engine that controls the hardware processor to access the opportunity-to-component map to identify at least one of the set of prescriptive machine configuration components, machine control components or data gathering components based on the agronomic variation opportunity, and wherein, upon identifying the at least one component, the prescriptive component system controls the hardware processor to automatically generate machine control data to modify the mobile machine base on the identified at least one prescriptive component.

2. The computing system of claim 1, and further comprising:

a user interface component that outputs a component identifier that identifies the at least one prescriptive component.

3. The computing system of claim 1 wherein the variation opportunity space engine comprises:

an agronomic variation identifier component configured to receive the agronomic parameters and identify a variation value, corresponding to each agronomic parameter, indicative of variation of each agronomic parameter as the mobile machine moves across a field.

4. The computing system of claim 3 wherein the variation opportunity space engine comprises:

a variation opportunity space identifier component configured to identify a variation opportunity space for the field based on the identified variation values; and

an opportunity aggregation component that identifies a combined opportunity space based on the variation opportunity space for the field and variation opportunity spaces for a plurality of additional fields.

5. The computing system of claim 1 and further comprising:

a financial opportunity space engine configured to estimate a financial impact corresponding to the modified configuration of the at least one component on the mobile machine and to output a financial analysis including the financial impact.

6. A computer implemented method, comprising:

receiving, by a hardware processor, agronomic variation information indicative of sensed agronomic information in a plurality of different categories, the sensed agronomic information being sensed by a set of sensors on a mobile machine as the mobile machine moves across a given portion of land;

controlling, by the hardware processor, an opportunity space engine to quantify a set of agronomic variation opportunities, across the plurality of different categories, based on the agronomic variation information;

controlling, by the hardware processor, a prescriptive component system to access an opportunity-to-component map that maps the set of agronomic variation opportunities to a set of prescriptive machine configuration components that change a configuration of the mobile machine, a set of prescriptive machine control components that modify the mobile machine to automate portions of the control of the mobile machine, and a set of prescriptive data gathering components that modify operation of the sensors on the mobile machine to change a definition with which the agronomic parameters are sensed;

controlling, by the hardware processor, an opportunity-to-component mapping engine to identify at least one perspective component of the set of prescriptive machine configuration components, machine control components or data gathering components based on the quantified set of agronomic variation opportunities;

automatically controlling the mobile machine to apply different level of automated machine control to the mobile machine based on the at least one perspective component and the quantified set of agronomic variation opportunities; and

controlling, by the hardware processor, a user interface component to output the quantified set of agronomic variation opportunities and a control output indicative of the different level of machine control based on the identified at least one perspective component.

7. The method of claim 6 wherein receiving agronomic variation information comprises:

receiving a set of agronomic variation parameters indicative of different types of agronomic information across a given field; and

calculating an agronomic variation value corresponding to each type of agronomic information, for the given field.

8. The method of claim 7 wherein quantifying a set of agronomic variation opportunities comprises:

combining the agronomic variation values to obtain a composite agronomic variation parameter corresponding to the given field; and

classifying an agronomic opportunity space for the given field based on the composite agronomic variation parameter.

9. The method of claim 8 wherein identifying the at least one of the components comprises:

combining the composite agronomic variation parameter for the given field with composite agronomic variation parameters from the fields to obtain an aggregated agronomic variation opportunity space; and

accessing the opportunity-to-component map to identify components that reduce the aggregated agronomic variation opportunity space.

10. The method of claim 9 and further comprising:

obtaining financial information corresponding to the agronomic variation opportunity and the identified component;

estimating a financial savings realized by controlling the at least one of the set of components on the mobile machine in accordance with the agronomic variation opportunity;

generating a financial analysis, based on the financial information, indicative of a cost of controlling the at least one of the set of components and the financial savings; and

outputting the financial analysis.

11. A computing system, comprising:

a hardware processor;

a variation opportunity space engine configured to identify, by the hardware processor, an agronomic variation opportunity based on agronomic variation data indicative of variation of a sensed agronomic parameter that is sensed by a sensor on a mobile machine as the mobile machine moves across a piece of land, the sensor being configured to generate a sensor signal indicative of a value of the sensed agronomic parameter at a first rate; and

a prescriptive component system configured to;

control a recommendation engine, by the hardware processor, to identify a set of prescriptive sensor definition components, based on the agronomic variation opportunity, as components that change the first rate at which the sensor signal is generated to a second rate, based on a variation in the sensed agronomic parameter; and

control the mobile machine to modify the sensor definition level at which the sensor senses the sensed agronomic parameter, based on the identified set of prescriptive sensor definition components, from the first rate to the second rate.

12. The computing system of claim 11 wherein the prescriptive component system is configured to increase the rate at which the sensor signal is generated from the first rate to the second rate, which is a higher rate than the first, based on a level of variation in the sensed agronomic parameter.