AGRONOMIC VARIATION AND TEAM PERFORMANCE ANALYSIS

• US 20150199775A1
• Filed: 11/18/2014
• Published: 07/16/2015
• 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.
• Granted Patent: US 10,311,527 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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 variation opportunity space engine configured 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 configured to identify a set of prescriptive components for the mobile machine based on the agronomic variation opportunity, wherein the prescriptive components, when deployed on the mobile machine, address the variation in the agronomic parameters.

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

a user interface component that outputs a component identifier that identifies the set of prescriptive components.

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 4 prescriptive component system comprises:

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

an opportunity-to-component mapping engine configured to access the opportunity-to-component map and identify the set of prescriptive components based on the combined opportunity space.

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

a financial opportunity space engine configured to estimate a financial impact corresponding to deployment of the identified set of prescriptive components on the mobile machine and to output a financial analysis including the financial impact.

7. A method, comprising:

receiving 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;

quantifying a set of agronomic variation opportunities, across the plurality of different categories, based on the agronomic variation information;

identifying a set of prescriptive components based on the set of agronomic variation opportunities; and

outputting the quantified set of agronomic variation opportunities and the corresponding prescriptive components.

8. The method of claim 7 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.

9. The method of claim 8 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.

10. The method of claim 9 wherein identifying a set of prescriptive 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 a mapping between agronomic variation opportunity and prescriptive components to identify prescriptive components that reduce the aggregated agronomic variation opportunity space.

11. The method of claim 10 wherein identifying the set of prescriptive components further comprises:

identifying at least one of a machine automation and control component that automates control of a portion of the mobile machine, machine configuration component that identifies a machine configuration for the mobile machine, and a data gathering component that senses the agronomic information at a given definition.

12. The method of claim 10 and further comprising:

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

estimating a financial savings realized by using the prescriptive components;

generating a financial analysis, based on the financial information, indicative of a cost of the prescriptive components and the financial savings estimated by using the prescriptive components; and

outputting the financial analysis.

13. A computing system, comprising:

a metric calculator system configured to receive individual operator performance information, the individual operator performance information being received for a plurality of different operators on a predefined team of operators, the individual operator performance information being indicative of a comparison of individual operator performance in controlling a given mobile machine, of a plurality of different mobile machines operated by the plurality of different operators on the team, to reference performance data, the metric calculator system being configured to calculate a performance score for each of the plurality of different operators on the team based on the individual operator performance information;

a team score aggregator configured to combine the performance scores for each of the plurality of different operators on the team to obtain a team performance score; and

a user interface component configured to output the team performance score with a user input mechanism that is actuated to view detailed information corresponding to each of the plurality of operators.

14. The computing system of claim 13 wherein the metric calculator system comprises:

a calculator component that generates a set of individual performance metrics, comprising a plurality of individual performance metrics, for each operator on the team; and

a team member composite score generator configured to combine the set of individual performance metrics for each operator on the team to obtain a composite score for each operator on the team.

15. The computing system of claim 14 wherein the team score aggregator is configured to calculate a set of team metrics, different from the set of individual performance metrics, for the team and to combine the set of team metrics with the composite scores for the operators on the team to obtain a composite performance score for the team.

16. The computing system of claim 15 and further comprising:

a comparison component that generates a comparison display indicative of a comparison of the composite performance score for the team against composite performance scores for other teams.

17. The computing system of claim 14 wherein the calculator component is configured to identify a type of mobile machine being operated by a given operator and calculate a set of individual performance metrics that varies based on the type of mobile machine identified.

18. The computing system of claim 17 wherein the calculator component is configured to identify a first operator on the team operating a harvester and a second operator on the team operating a tractor and to calculate a first set of individual performance metrics for the operator of the harvester and a second set of performance metrics for the operator of the tractor.

19. The computing system of claim 13 wherein the user interface component comprises:

a user interface device configured to output the team score to at least one operator on the team in near real time.

20. The computing system of claim 13 wherein the user interface component comprises:

a user interface device configured to output the team score to a team coordinator, that coordinates one or more different teams, in near real time.

21. The computing system of claim 13 wherein the user interface component comprises:

a user interface device configured to output the team score to a remote server system.

22. A method, comprising:

sensing individual operator performance parameters for a plurality of different operators, each operating a different mobile machine, on a predefined team of operators;

comparing the individual operator performance parameters to reference performance data;

generating a performance score for each of the plurality of different operators on the team based on the comparison;

generating a team performance score based on a combination of the performance scores for each of the plurality of different operators on the team; and

outputting the team performance score.

23. The method of claim 22 wherein generating a performance score for each of the plurality of different operators on the team comprises:

generating a plurality of individual performance metrics, for each operator on the team; and

generating a composite performance score for each operator on the team based on a combination plurality of individual performance metrics for each operator on the team.

24. The method of claim 23 wherein sensing includes identifying a type of mobile machine operated by each operator and wherein generating a plurality of individual performance metrics comprises generating the individual performance metrics based on the identified type of mobile machine.

25. The method of claim 22 and further comprising:

comparing the team performance score for the team against team performance scores for one or more other teams; and

generating comparison user interface output indicative of the comparison.

26. The method of claim 24 wherein generating a plurality of individual performance metrics comprises:

identifying a first operator on the team operating a harvester;

identifying a second operator on the team operating a tractor;

calculating a first set of individual performance metrics for the operator of the harvester; and

calculating a second set of performance metrics for the operator of the tractor.

27. The method of claim 22 wherein outputting comprises at least one of:

outputting the team performance score to at least one operator on the team in near real time;

outputting the team performance score to a team coordinator, that coordinates one or more teams, in near real time; and

outputting the team score to a remote server system.