SBIR/STTR Research Award

Visual AI for Controlled Environment Agriculture

Award identifier ae083890505f1d75cdf566498fee58de526cfe12a5cd9ee12ad9db6492a17a56Awarding agency National Aeronautics and Space Administration

Award amount

$125,000

Program and phase

STTR · Phase I

Award year

2021

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Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
Bloomfield Robotics, Inc.
Proposal award date
2021-05-17
Contract end date
2022-06-19
UEI
CY75H99CJMV7
Solicitation number
STTR_21_P1
Topic code
T6

Research abstract

Crop inspection is as essential today as it was at the birth of agriculture. Then and now, growers move among the fields to visually inspect plants, identifying and assessing the presence of infection and disease, deficiencies in water and nutrients, impact of environmental factors, the timing of harvests and predicting the expected yield.nbsp;However, human inspection is subject to the limitations of human attention, varying levels of skill and knowledge, and the biases of the person doing the inspection. Bloomfield built Flash to allow specialty crop growers to inexpensively, easily and continuously inspect their crops, plant-by-plant, to gain the benefits of close inspection while reducing and eliminating the deficiencies of human inspection. To date, Bloomfield has inspected grapes in 12 vineyards across 4 states, with plans to inspect vineyards in the EU and apple orchards in the US and UK. nbsp; nbsp; Bloomfield will adapt itsrsquo; existing deep learning, camera-enabled, cloud-based plant assessment tool, Flash, to design and build a self-contained, computing at the edge variant for Controlled Environment Agriculture (CEA) to meet NASArsquo;s needs that will determine:nbsp;(1) Plant stresses and/or infestationnbsp; (2) Plant performance against expectationsnbsp; (3) Recommendations for improving plant health and performance in the unique and challenging environment of spaceThese will require the achievement of three objectives:nbsp;(1) Prove continuous, precise, accurate and reliable deep learning image-based plant health and performance assessment works in CEAnbsp; (2) Prove a novel multi-spectral imaging tool also capable of capturing precise images for deep learning analysis (3) Prove a plant inspection tool using multi-spectral imaging under controlled lighting conditions capable of functioning reliably and continuously on the edge nbsp; This STTR provides Bloomfield with the opportunity to meet NASArsquo;s needs while advancing Bloomfieldrsquo;s product road map of providing value not just outdoors but also CEA.nbsp;

Technology keywords

Not reported

Agency intelligence

National Aeronautics and Space Administration

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