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Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture

Donald Danforth Plant Science Center
Program: 
ARPA-E Award: 
$4,399,595
Location: 
St. Louis, MO
Project Term: 
09/24/2019 to 12/23/2021
Project Status: 
ACTIVE
Technical Categories: 
Critical Need: 
In the last decade, big data has enabled high-yield production of bioenergy crops. The drawback in agricultural systems data is that researchers are grappling with large, complex, multidimensional datasets comprised of thousands of data layers captured weekly or daily in dynamic outdoor environments. Converting all of these measurements into knowledge and actionable outcomes that keeps up with farmer and researcher demand is difficult. Tools that can automatically detect patterns in this data are needed to guide agricultural researchers to better inform experimental design and data analysis.
Project Innovation + Advantages: 
In the last decade, big data has enabled high-yield production of bioenergy crops. The drawback in agricultural systems data is that researchers are grappling with large, complex, multidimensional datasets comprised of thousands of data layers captured weekly or daily in dynamic outdoor environments. Converting all of these measurements into knowledge and actionable outcomes that keeps up with farmer and researcher demand is difficult. Tools that can automatically detect patterns in this data are needed to guide agricultural researchers to better inform experimental design and data analysis.
Potential Impact: 
The team proposes to create a novel AI processing pipeline for supplementing phenomics analysis that will facilitate participation by a wide range of disciplines, address gaps in computing sciences and computational tools for creating and analyzing complex phenomics datasets, and produce world class benchmark datasets.
Security: 
By addressing challenges in phenomic data analysis, the project will enhance global energy security.
Environment: 
The accelerated production of new domestic biofuels could reduce energy-related emissions and improve energy efficiency.
Economy: 
The proposed project will provide additional tools for analyzing, combining, and understanding phenomics datasets that will be applicable not only to the agriculture and energy sectors of the U.S. economy but broadly to any sector using dense and/or complex sensor datasets.
Contacts
ARPA-E Program Director: 
Dr. David Babson
Project Contact: 
Dr. Todd Mockler
Release Date: 
11/15/2018