Invention Grant
- Patent Title: Identifying ground types from interpolated covariates
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Application No.: US17180695Application Date: 2021-02-19
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Publication No.: US11704576B1Publication Date: 2023-07-18
- Inventor: John A. McEntire , Thomas A. Dye
- Applicant: ARVA INTELLIGENCE CORP.
- Applicant Address: US UT Park City
- Assignee: ARVA INTELLIGENCE CORP.
- Current Assignee: ARVA INTELLIGENCE CORP.
- Current Assignee Address: US UT Salt Lake City
- Agency: Kerr IP Group, LLC
- Main IPC: G06F11/30
- IPC: G06F11/30 ; G06N5/01 ; G06N20/00 ; G06Q50/02 ; G06F16/29 ; G06F18/214 ; G06F18/21 ; G06F18/2413 ; G06F18/243

Abstract:
A system and method for identifying ground types from one or more interpolated covariates. The method proceeds by accessing soil composition information for plots of land, in which the soil composition information includes measured soil sample results, environmental results, soil conductivity results or any combination thereof. The method continues by identifying covariates from the soil composition information. Subsequently, the method interpolates covariates associated with different locations with an interpolation training model. Voxels are generated that are each associated with interpolated covariates having a corresponding geographical location. The method trains a random forest training model with the interpolated covariates. The voxels traverse the trained random forest model to identify clusters of voxels that are co-associated. The method identifies a ground type by combining the co-associated clusters. Each ground type is associated with a crop zone, a soil fertility, or a farm management recommendation.
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