Methods and systems for recommending agricultural activities

US11113649B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11113649-B2
Application numberUS-201514846661-A
CountryUS
Kind codeB2
Filing dateSep 4, 2015
Priority dateSep 12, 2014
Publication dateSep 7, 2021
Grant dateSep 7, 2021

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  1. Title

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  2. Abstract

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  5. First independent claim

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Abstract

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A computer-implemented method for recommending agricultural activities is implemented by an agricultural intelligence computer system in communication with a memory. The method includes receiving a plurality of field definition data, retrieving a plurality of input data from a plurality of data networks, determining a field region based on the field definition data, identifying a subset of the plurality of input data associated with the field region, determining a plurality of field condition data based on the subset of the plurality of input data, identifying a plurality of field activity options, determining a recommendation score for each of the plurality of field activity options based at least in part on the plurality of field condition data, and providing a recommended field activity option from the plurality of field activity options based on the plurality of recommendation scores.

First claim

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What is claimed is: 1. A computer-implemented method for providing an improvement in recommending agricultural activities determined based on crop-related data and field condition data and using an agricultural intelligence computer system in communication with a processor, a memory and a database, the method comprising: receiving, from a database over an interface coupled to a processor and a memory of an agricultural intelligence computer system, a plurality of field definition data; retrieving a plurality of input data from a plurality of data networks; determining a plurality of field regions based on the field definition data; identifying a subset of the plurality of input data associated with the plurality of field regions; determining a plurality of field condition data based on the subset of the plurality of input data; identifying a plurality of field activity options; determining, for each of the plurality of field regions, a recommended field activity option, of the plurality of field activity options, based at least in part on the plurality of field condition data; determining, for each of the plurality of field regions, a recommended crop type, of a plurality of recommended crop options, based at least in part on the plurality of field condition data; determining, for each field region of the plurality of field regions, a recommendation score, of a plurality of recommendation scores, based at least in part on the plurality of field condition data; determining, for each of the plurality of field regions, a tillage practice option, of a plurality of recommended tillage practice options, based at least in part on the plurality of field condition data; providing, and displaying on a display device of the agricultural intelligence computer system, a graphical user interface that displays a page including: a first pull-down menu that allows selecting, for each field region of the plurality of field regions, a particular recommended field activity option from the plurality of field activity options, a second pull-down menu that allows selecting, for each field region of the plurality of field regions, a particular recommended crop type from the plurality of recommended crop options; a third pull-down menu that allows selecting, for each field region of the plurality of field regions, a particular recommendation score from the plurality of recommendation scores, a fourth pull-down menu that allows selecting, for each field region of the plurality of field regions, a particular tillage practice from the plurality of recommended tillage practice options and determined based on the plurality of field activity options and associated recommendation scores; automatically generating an update based on the particular recommended field activity option, the particular recommended crop type, the particular recommendation score and the particular tillage practice, and updating, based on the update, the graphical user interface to reflect options selected for each field region of the plurality of field regions; transmitting the update for the plurality of field regions to one or more agricultural machines in real time, so that each agricultural machine, of the one or more agricultural machines, executes instructions, included in the update, in a field region of the plurality of field regions; performing, by the agricultural intelligence computer system, a historical data analysis based on user's farming practices within a current season and for historical seasons; determining, by the agricultural intelligence computer system, a relative maturity value of crops based on expected heat units over a growing season in light of a planting date, the user's farming practices, and field-specific and environmental data; calculating, by the agricultural intelligence computer system, expected heat units for crops and determining a development of maturity of the crops as heat is a proxy for energy received by the crop. 2. The method of claim 1 , further comprising: defining a precipitation analysis period; retrieving a set of recent precipitation data, a set of predicted precipitation data, and a set of temperature data associated with the precipitation analysis period from the subset of the plurality of input data; determining a workability index based on the set of recent precipitation data, the set of predicted precipitation data, and the set of temperature data; and identifying a recommended agricultural activity based, at least in part, on the workability index. 3. The method of claim 1 , further comprising: determining an initial crop moisture level; receiving a plurality of daily high and low temperatures; receiving a plurality of crop water usage; determining a soil moisture level for the field region; and recommending a plurality of crops for planting based on the determined soil moisture level. 4. The method of claim 1 , further comprising: receiving a plurality of pest risk data wherein each of the plurality of pest risk data includes a pest identifier and a pest location; receiving a plurality of crop identifiers associated with a plurality of crops; receiving a plurality of pest spray information associated with the crop identifiers; determining a pest risk assessment, of a plurality of pest risk assessments, associated with each of the plurality of crops; and recommending a spray strategy based on the plurality of pest risk assessments. 5. The method of claim 1 , further comprising: receiving a plurality of historical agricultural activities associated with each of the field region from a user device; and providing a recommended field activity option based at least in part on the plurality of historical agricultural activities. 6. The method of claim 1 , further comprising: utilizing a grid-based model to obtain localized field condition data. 7. A networked agricultural intelligence system for providing an improvement in recommending agricultural activities determined based on crop-related data and field condition data and using a computer system, the networked agricultural intelligence system comprising: a plurality of data network computer systems; an agricultural intelligence computer system comprising a processor and a memory in communication with said processor, said processor configured to: receive a plurality of field definition data; retrieve a plurality of input data from the plurality of data network computer systems; determine a plurality of field regions based on the field definition data; identify a subset of the plurality of input data associated with the plurality of field regions; determine a plurality of field condition data based on the subset of the plurality of input data; identify a plurality of field activity options; determine, for each of the plurality of field regions, a recommended field activity option, of the plurality of field activity options, based at least in part on the plurality of field condition data; determine, for each of the plurality of field regions, a recommended crop type, of a plurality of recommended crop options, based at least in part on the plurality of field condition data; determine, for each field region of the plurality of field regions, a recommendation score, of a plurality of recommendation scores, based at least in part on the plurality of field condition data; determine, for each of the plurality of field regions, a tillage practice option, of a plurality of recommended tillage practice options, based at least in part on the plurality of field condition data; provide, and displaying on a display device of the agricultural intelligence computer system, a graphical user interface that displays a page including: a first pull-down menu that allows selecting, for eac

Assignees

Inventors

Classifications

  • Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) · CPC title

  • Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling · CPC title

  • Workflow analysis · CPC title

  • Agriculture; Fishing; Forestry; Mining · CPC title

  • Precision agriculture · CPC title

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What does patent US11113649B2 cover?
A computer-implemented method for recommending agricultural activities is implemented by an agricultural intelligence computer system in communication with a memory. The method includes receiving a plurality of field definition data, retrieving a plurality of input data from a plurality of data networks, determining a field region based on the field definition data, identifying a subset of the …
Who is the assignee on this patent?
Climate Corp
What technology area does this patent fall under?
Primary CPC classification G06Q10/0633. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Sep 07 2021 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).