Machine learning in agricultural planting, growing, and harvesting contexts
US11263707B2 · kind B2 · utility
Assignee
Inventors
- David Patrick Perry
- Geoffrey Albert von Maltzahn
- Robert Berendes
- Eric Michael Jeck
- Barry Loyd Knight
- Rachel Ariel Raymond
- Ponsi Trivisvavet
- Justin Y H Wong
- Neal Hitesh Rajdev
- Marc-Cedric Joseph Meunier
- Casey James Leist
- Pranav Ram Tadi
- Andrea Lee Flaherty
- Charles David Brummitt
- Naveen Neil Sinha
- Jordan Lambert
- Jonathan Hennek
- Carlos Becco
- Mark Allen
- Daniel Bachner
- Fernando Derossi
- Ewan Lamont
- Rob Lowenthal
- Dan Creagh
- Steve Abramson
- Ben Allen
- Jyoti Shankar
- Chris Moscardini
- Jeremy Crane
- David Weisman
Key dates
| Filing date | Aug 7, 2018 |
| Grant date | Mar 1, 2022 |
| Priority date | — |
| Expiry date | Oct 5, 2038 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02P90/84
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.