Using machine learning-based seed harvest moisture predictions to improve a computer-assisted agricultural farm operation
US11017306B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 23, 2019 |
| Grant date | May 25, 2021 |
| Priority date | — |
| Expiry date | Nov 25, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q50/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments generate digital plans for agricultural fields. In an embodiment, a model receives digital inputs including stress risk data, product maturity data, field location data, planting date data, and/or harvest date data. The model mathematically correlates sets of digital inputs with threshold data associated with the stress risk data. The model is used to generate stress risk prediction data for a set of product maturity and field location combinations. In a digital plan, product maturity data or planting date data or harvest date data or field location data can be adjusted based on the stress risk prediction data. A digital plan can be transmitted to a field manager computing device. An agricultural apparatus can be moved in response to a digital plan.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.