US 12,457,923 B2
System and method for estimating crop yield for an agricultural harvester using a machine-learned model
Daenio Cleodolphi, Piracicaba (BR); João Augusto Marcolin Lucca, São Pedro (BR); Matheus Eduardo Dos Santos, Piracicaba (BR); and Ricardo Breda Porcelli, Itapira (BR)
Assigned to CNH Industrial America LLC, New Holland, PA (US)
Filed by CNH Industrial America LLC, New Holland, PA (US)
Filed on Oct. 28, 2022, as Appl. No. 17/976,372.
Claims priority of application No. 10 2021 021948 3 (BR), filed on Oct. 31, 2021.
Prior Publication US 2023/0139169 A1, May 4, 2023
Int. Cl. A01D 34/00 (2006.01); A01D 45/10 (2006.01)
CPC A01D 34/006 (2013.01) [A01D 45/10 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computing system for estimating crop yields for agricultural harvesters, the computing system comprising:
one or more processors; and
one or more non-transitory computer-readable media that collectively store:
a machine-learned yield estimation model configured to receive data associated with one or more operation-related conditions for an agricultural harvester and process the data to determine a yield-related parameter indicative of a crop yield for the agricultural harvester, wherein the yield-related parameter comprises a mass flow rate through a portion of the agricultural harvester; and
instructions that, when executed by the one or more processors, configure the computing system to perform operations, the operations comprising:
obtaining the data associated with one or more operation-related conditions;
inputting the data into the machine-learned yield estimation model; and
receiving a value for the yield-related parameter as an output of the machine-learned yield estimation model.