US 12,416,620 B1
Optimal sampling with soil stratification
Elijah Benjamin Hoffman, Oakland, CA (US); Christopher William Hardin Fedor, Durham, NC (US); Leland David Bernstein, Brooklyn, NY (US); Thomas A. Dye, Austin, TX (US); and John A. McEntire, Park City, UT (US)
Assigned to ARVA INTELLIGENCE CORP., Salt Lake City, UT (US)
Filed by ARVA INTELLIGENCE CORP., Salt Lake City, UT (US)
Filed on Mar. 7, 2023, as Appl. No. 18/118,648.
Application 18/118,648 is a continuation in part of application No. 17/160,286, filed on Jan. 27, 2021, granted, now 11,610,272, issued on Mar. 21, 2023.
Application 18/118,648 is a continuation in part of application No. 17/171,887, filed on Feb. 9, 2021, granted, now 11,715,024, issued on Aug. 1, 2023.
Application 18/118,648 is a continuation in part of application No. 17/180,695, filed on Feb. 19, 2021, granted, now 11,704,576, issued on Jul. 18, 2023.
Application 18/118,648 is a continuation in part of application No. 17/203,670, filed on Mar. 16, 2021, granted, now 11,704,581, issued on Jul. 18, 2023.
Claims priority of provisional application 62/995,484, filed on Jan. 29, 2020.
Claims priority of provisional application 62/995,674, filed on Feb. 7, 2020.
Claims priority of provisional application 62/995,948, filed on Feb. 20, 2020.
Claims priority of provisional application 63/100,545, filed on Mar. 17, 2020.
Int. Cl. G06F 11/30 (2006.01); G01N 33/24 (2006.01); G06Q 50/02 (2012.01)
CPC G01N 33/24 (2013.01) [G06Q 50/02 (2013.01); G01N 33/245 (2024.05)] 20 Claims
OG exemplary drawing
 
1. A method for determining optimal sampling parameters, the method comprising:
generating, at a crop prediction engine, a voxel grid for a soil organic carbon (SOC) area, wherein the voxel grid is associated with a map;
identifying, at the crop prediction engine, a plurality of strata parameters, in which each strata parameter includes a stratification boundary associated with the SOC area;
identifying, at the crop prediction engine, a number of strata within the stratification boundary;
inputting, at the crop prediction engine, a plurality of soil samples for the SOC area;
defining, at the crop prediction engine, a plurality of specifications for a plurality of Monte Carlo simulations including:
one or more strata sampling weights, and
a margin of error;
iterating through the plurality of Monte Carlo simulations by increasing a sample count between each iteration, wherein each of the plurality of Monte Carlo simulations includes:
repeatedly sampling, at the crop prediction engine, wherein each sampling includes:
selecting, at the crop prediction engine, at least one strata parameter from the plurality of strata parameters for the Monte Carlo simulation,
selecting, at the crop prediction engine, a sample count for each of the selected at least one strata parameter,
selecting, at the crop prediction engine, a plurality of random samples for each selected strata parameter,
aggregating, at the crop prediction engine, the plurality of random samples for each selected strata parameter;
determining, at the crop prediction engine, that the aggregated plurality of random samples achieved the sample count for each selected strata parameter, and
generating, at the crop prediction engine, an empirical sampling distribution for each Monte Carlo simulation; and
determining, at the crop prediction engine, an optimal sampling plan from the empirical distribution generated for each of the plurality of Monte Carlo simulations, wherein the optimal sampling plan has a lowest sample count and satisfies the margin of error.