Patents by Inventor Charles David Brummitt
Charles David Brummitt has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11946922Abstract: In various embodiments, methods, systems, and computer program products are provided for estimating greenhouse gas emissions. In particular, methods, systems, and computer program products are presented for the task of quantifying emissions reduction from changes in stocks of soil organic carbon (SOC). The methods apply more generally to tasks that involve quantification of a total or average across a population of land (and/or possibly any space and any time) using measurements at a sample from that population. The sample may not be representative or unbiased. In some examples, estimating greenhouse gas emissions may apply to quantifying the total stock of SOC in land, the total nitrous oxide emissions in land and a time interval.Type: GrantFiled: December 15, 2022Date of Patent: April 2, 2024Assignee: INDIGO AG, INC.Inventors: Brian Segal, Charles David Brummitt
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Patent number: 11776071Abstract: 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.Type: GrantFiled: March 11, 2021Date of Patent: October 3, 2023Assignee: INDIGO AG, INC.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, Gerard Keating, Lauren Moores, William Pate
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Publication number: 20230147951Abstract: In various embodiments, methods, systems, and computer program products are provided for estimating greenhouse gas emissions. In particular, methods, systems, and computer program products are presented for the task of quantifying emissions reduction from changes in stocks of soil organic carbon (SOC). The methods apply more generally to tasks that involve quantification of a total or average across a population of land (and/or possibly any space and any time) using measurements at a sample from that population. The sample may not be representative or unbiased. In some examples, estimating greenhouse gas emissions may apply to quantifying the total stock of SOC in land, the total nitrous oxide emissions in land and a time interval.Type: ApplicationFiled: December 15, 2022Publication date: May 11, 2023Inventors: Brian Segal, Charles David Brummitt
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Patent number: 11592431Abstract: In various embodiments, methods, systems, and computer program products are provided for estimating greenhouse gas emissions. In particular, methods, systems, and computer program products are presented for the task of quantifying emissions reduction from changes in stocks of soil organic carbon (SOC). The methods apply more generally to tasks that involve quantification of a total or average across a population of land (and/or possibly any space and any time) using measurements at a sample from that population. The sample may not be representative or unbiased. In some examples, estimating greenhouse gas emissions may apply to quantifying the total stock of SOC in land, the total nitrous oxide emissions in land and a time interval.Type: GrantFiled: April 20, 2022Date of Patent: February 28, 2023Assignee: Indigo Ag, Inc.Inventors: Brian Segal, Charles David Brummitt
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Publication number: 20220365061Abstract: In various embodiments, methods, systems, and computer program products are provided for estimating greenhouse gas emissions. In particular, methods, systems, and computer program products are presented for the task of quantifying emissions reduction from changes in stocks of soil organic carbon (SOC). The methods apply more generally to tasks that involve quantification of a total or average across a population of land (and/or possibly any space and any time) using measurements at a sample from that population. The sample may not be representative or unbiased. In some examples, estimating greenhouse gas emissions may apply to quantifying the total stock of SOC in land, the total nitrous oxide emissions in land and a time interval.Type: ApplicationFiled: April 20, 2022Publication date: November 17, 2022Inventors: Brian Segal, Charles David Brummitt
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Patent number: 11263707Abstract: 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.Type: GrantFiled: August 7, 2018Date of Patent: March 1, 2022Assignee: INDIGO AG, INC.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, Gerard Keating, Lauren Moores, William Pate
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Publication number: 20210224927Abstract: 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.Type: ApplicationFiled: March 11, 2021Publication date: July 22, 2021Inventors: 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, Gerard Keating, Lauren Moores, William Pate
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Publication number: 20190050948Abstract: 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.Type: ApplicationFiled: August 7, 2018Publication date: February 14, 2019Inventors: 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, Charles Vincent Michell, JR., 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, Gerard Keating, Lauren Moores, William Pate