The Climate Corporation

Apple Inc.

John Gates

Patrice Olivier Gautier

Ivan Krstic

Karthik Narayanan

Raghunandan K Pai

James C Wilson

Sudhakar N Mambakkam

Eric Daniel Friedman

Selvarajan Subramaniam

Ramarathnam Santhanagopal

Prabhakaran Vaidyanathaswami

Steven De Gryze

Harish Sangireddy

Robert P Ewing

Juan Lopez Arriaza

Asra Nizami

John Browning Burdick

Michael S Byrns

Jennifer Holt

Kofikuma Dzotsi

Maria Antonia Terres

Wang Zhan

Andrew Robert McGowan

Subfield moisture model improvement in generating overland flow modeling using shallow water calculations and kinematic wave calculations is disclosed. In an embodiment, a computer-implemented data processing method comprises: receiving precipitation data and infiltration data for an agricultural field; obtaining surface water depth data, surface water velocity data, and surface water discharge data for the same agricultural field; determining subfield geometry data for the agricultural field; executing a plurality of water calculations and wave calculations using the subfield geometry data to generate an overland flow model that includes moisture levels for the agricultural field; based on, at least in part, the overland flow model, generating and causing displaying a visual graphical image of the agricultural field comprising a plurality of color pixels having color values corresponding to the moisture levels determined for the agricultural field. Output of the overland flow model is provided to control computers of seeders, planters, fertilizer spreaders, harvesters, or combines to control seeding, planting, fertilizing or irrigation activities in the field.

Sub field moisture model improvement using overland flow modeling with shallow water computations

In an embodiment, an agricultural intelligence computing system stores a digital model of crop growth, the digital model of crop growth being configured to compute nutrient requirements in soil to produce particular yield values based, at least in part, on data unique to an agricultural field. The system receives agronomic field data for a particular agronomic field, the agronomic field data comprising one or more input parameters for each of a plurality of locations on the agronomic field, nutrient application values for each of the plurality of locations, and measured yield values for each of the plurality of locations. The system computes, for each location of the plurality of locations, a required nutrient value indicating a required amount of nutrient to produce the measured yield values. The system identifies a subset of the plurality of locations where the computed required nutrient value is greater than the nutrient application value. The system computes, for each of the subset of the plurality of locations, a residual value comprising a difference between the required nutrient value and the nutrient application value. The system generates a residual map comprising the residual values at the subset of the plurality of locations. Using the residual map and the one or more input parameters for each of the plurality of locations, the system generates and stores particular model correction data for the particular agronomic field.

Digital nutrient models using spatially distributed values unique to an agronomic field

Some embodiments of the invention provide a program for recovering access to a service associated with an account. The program provides a login credential to log into the account to receive the associated service. Next, the program receives an access continuation parameter (ACP) after logging into the account. The program then accesses the service and receives a rejection of a subsequent access to the service. The program then provides the ACP in lieu of the login credential to continue to receive the service.

Account access recovery system, method and apparatus

Display of graphical maps of agricultural fields, coded with color or other indicators of values of data pertaining to agronomy at high resolution, and updated on a daily basis or on demand by recalculating agronomy models with the high-resolution data, is disclosed. Map displays may include multiple layers that relate to different agronomy metrics, and GUI widgets that are programmed to receive selection of values indicating different field properties or layers to display. In an embodiment, a computer-implemented data processing method providing an improvement in efficient calculation of digital data representing physical properties of agricultural fields, the method comprising receiving digital input specifying a request to display a map image of a specified agricultural field for a particular day; in response to receiving the input, calculating an interpolated digital image of the specified agricultural field with a plurality of different field properties, by: dividing a digital map of the specified field into a plurality of grids each having a same size and a same area; obtaining, from digital storage, a plurality of data for the different field properties and assigning the data as covariates; grouping the grids into a specified number of clusters based on values of the covariates; pseudo-randomly selecting a specified number of one or more sample values in each of the clusters; evaluating a digital fertility model using the sample values and storing a plurality of output values from the digital fertility model; interpolating a plurality of model values for the grids; generating and causing displaying a visual graphical image of the specified agricultural field including color pixels corresponding to each of the model values.

Digital visualization of periodically updated in-season agricultural prescriptions

A system for generating digital models of nitrogen availability based on field data, weather forecast data, and models of water flow, temperature, and crop uptake of nitrogen and water is provided. In an embodiment, field data and forecast data are received by an agricultural intelligence computing system. Based on the received data, the agricultural intelligence computing system models changes in temperature of different soil layers, moisture content of different soil layers, and loss of nitrogen and water to the soil through crop uptake, leaching, denitrification, volatilization, and evapotranspiration. The agricultural intelligence computing system creates a digital model of nitrogen availability based on the temperature, moisture content, and loss models. The agricultural intelligence computing system may then send nitrogen availability data to a field manager computing device and/or use the nitrogen availability data to create notifications, recommendations, agronomic models, and/or control parameters for an application controller.

Generating digital models of nutrients available to a crop over the course of the crop's development based on weather and soil data

Subfield moisture model improvement using overland flow modeling with shallow water computations

Digital visualization of periodically updated in-season agricultural fertility prescriptions

In an embodiment, a computer-implemented method of assimilation of soil moisture data is disclosed. The method comprises receiving, by a processor, a digital data model related to soil moisture with a plurality of parameters for a given geographical location. The method also comprises identifying a time-based or event-based trigger for a first of the plurality of parameters. The method further comprises receiving, by the processor, a plurality of values for the plurality of parameters measured from soil samples for a series of time points. Finally, the method comprises applying sequential data assimilation through the series of time points as soon as the plurality of measured values are received for each of the series of time points, by executing an optimization method to optimize values of the plurality of parameters with respect to the plurality of measured values for each of the time points, thereby obtaining a plurality of optimized values for the plurality of parameters for each of the time points, when the time-based or event-based trigger is satisfied for one of the series of time points, reducing the search space associated with the first parameter in executing the optimization method.

Sequential data assimilation to improve agricultural modeling

Some embodiments provide an account-access recovery method that receives a request to recover access to an account. The method also assesses recent usage of a device that is associated with the account. The method also, based on the assessment, selects a recovery process from a group of different recovery processes for regaining access to the account. The method also provides the selected recovery process to a party that is requesting the access recovery.

Selectively specifying account access recovery process based on account activity

In an embodiment, the techniques herein include receiving a request for a suggested distribution rate of a particular field-distributed commodity in a particular geographical area. Based on that request, two or more rate models for distribution of the particular field-distributed commodity are computed, where one rate model is a user-tolerance model. The suggested distribution rate of the particular field-distributed commodity is determined by performing Bayesian updating where the user-tolerance model is treated as a prior distribution and distributions for each of the other rate models of the two or more rate models for distribution of the particular field-distributed commodity in the particular geographical area are treated as input data in the Bayesian updating. The determined suggested distribution rate of the particular field-distributed commodity is then sent in response to the received request.

Agricultural management recommendations based on blended model

Some embodiments of the invention provide a program for recovering access to an account. The program receives an access recovery parameter (ARP) after providing a first credential to log into an account and providing a notification of a second credential necessary for accessing another resource. The program then receives a request to modify the first credential and receives the second credential. Next, after authenticating the second credential, the program uses the ARP to modify the first credential without providing the first credential.

Growing community of inventors

San Francisco, CA, United States of America

John Gates