Methods and systems for managing agricultural activities

Patent metadata

Field	Value
Publication number	US-10667456-B2
Application number	US-201514846422-A
Country	US
Kind code	B2
Filing date	Sep 4, 2015
Priority date	Sep 12, 2014
Publication date	Jun 2, 2020
Grant date	Jun 2, 2020

Abstract

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

What is claimed is:

1. A computer-implemented method for providing an improvement in modifying managing agricultural activities that are currently implemented using an agricultural intelligence computer system in communication with a memory, the method comprising:
receiving a plurality of field definition data;
retrieving a plurality of input data from a plurality of data networks; wherein the plurality of input data comprises elevation data;
determining a field region based on the field definition data;
identifying a plurality of temperature grids for the field region;
identifying a plurality of weather stations for the plurality of temperature grids, wherein a weather station of the plurality of weather stations is located at a weather station location, of a plurality of weather station locations, in a temperature grid of the plurality of temperature grids;
computing a plurality of weight values based on the plurality of weather station locations of the plurality of weather stations such that weather stations, of the plurality of weather stations, that are more proximate to their respective grids have higher weights than weather stations, of the plurality of weather stations, that are less proximate to their respective grids; receiving a plurality of temperature readings from the plurality of weather stations;
based on the plurality of temperature readings and the plurality of weight values computed for the plurality of weather stations, computing a plurality of weighted temperatures;
based on the elevation data, computing a plurality of relative elevations for the plurality of temperature grids;
determining a plurality of relative differences in elevations by comparing the plurality of relative elevations for the plurality of temperature grids to elevations of the plurality of weather stations; wherein a relative difference in elevation, of the plurality of relative differences in elevations, for a weather station from the plurality of weather stations is computed as an averaged difference between the plurality of relative elevations for the plurality of temperature grids and an elevation of the weather station;
generating a plurality of adjusted weighted temperatures by adjusting the plurality of weighted temperatures according to the plurality of relative differences in elevations;
determining an initial crop moisture level;
receiving a plurality of daily high and low temperatures;
receiving a plurality of crop water usage;
based on, at least in part, the initial crop moisture level, the plurality of daily high and low temperatures, and the plurality of crop water usage, determining a soil moisture level;
computing a plurality of field condition data based on the plurality of adjusted weighted temperatures, the soil moisture level, and the plurality of relative elevations; and
providing the plurality of field condition data to a user device.

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 a 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
providing a workability value to the user device based on the workability index.

3. The method of claim 2 , further comprising:
receiving a prospective field activity; and
determining the workability index based partially on the prospective field activity.

4. The method of claim 1 , further comprising:
receiving a plurality of alert preferences from the user device;
identifying a plurality of alert thresholds associated with the plurality of alert preferences;
monitoring a subset of the plurality of input data; and
alerting the user device when at least one of the alert thresholds is exceeded.

5. The method of claim 1 , further comprising receiving a plurality of field definition data from at least one of a user device and an agricultural machine device.

6. A networked agricultural intelligence system for improving managing agricultural activities 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 from a user device;
retrieve a plurality of input data from a plurality of data networks; wherein the plurality of input data comprises elevation data;
determine a field region based on the field definition data;
identify a plurality of temperature grids for the field region;
identify a plurality of weather stations for the plurality of temperature grids, wherein a weather station of the plurality of weather stations is located at a weather station location, of a plurality of weather station locations, in a temperature grid of the plurality of temperature grids;
compute a plurality of weight values based on the plurality of weather station locations of the plurality of weather stations such that weather stations, of the plurality of weather stations, that are more proximate to their respective grids have higher weights than weather stations, of the plurality of weather stations, that are less proximate to their respective grids;
receive a plurality of temperature readings from the plurality of weather stations;
based on the plurality of temperature readings and the plurality of weight values computed for the plurality of weather stations, compute a plurality of weighted temperatures;
based on the elevation data, compute a plurality of relative elevations for the plurality of temperature grids;
determining a plurality of relative differences in elevations by comparing the plurality of relative elevations for the plurality of temperature grids to elevations of the plurality of weather stations; wherein a relative difference in elevation, of the plurality of relative differences in elevations, for a weather station from the plurality of weather stations is computed as an averaged difference between the plurality of relative elevations for the plurality of temperature grids and an elevation of the weather station;
generating a plurality of adjusted weighted temperatures by adjusting the plurality of weighted temperatures according to the plurality of relative differences in elevations;
determining an initial crop moisture level;
receiving a plurality of daily high and low temperatures;
receiving a plurality of crop water usage;
based on, at least in part, the initial crop moisture level, the plurality of daily high and low temperatures, and the plurality of crop water usage, determining a soil moisture level;
computing a plurality of field condition data based on the plurality of adjusted weighted temperatures, the soil moisture level, and the plurality of relative elevations; and
providing the plurality of field condition data to a user device;
compute a plurality of field condition data based on the plurality of adjusted weighted temperatures and the plurality of relative elevations; and
provide the plurality of field condition data to the user device.

7. A networked agricultural intelligence system in accordance with claim 6 wherein the processor is further configured to:
define a precipitation analysis period;
retrieve 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 a subset of the plurality of input data;
determine a workability index based on the set of recent precipitation data, the set of predicted precipitation dat

Assignees

• Climate Corp

Inventors

• Ethington James
• Pollak Eli J
• D'Orgeval Tristan
• Krumme Katherine
• Levey Evin
• Wimbush Samuel Alexander
• Andrejko Erik
• Brega Moorea Lee
• Aldor-Noiman Sivan

Classifications

• G06Q10/06 Primary

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

• G06Q50/02

  Agriculture; Fishing; Forestry; Mining · CPC title

• A01B79/005 Primary

  Precision agriculture · CPC title