2232959
Project Grant
Overview
Grant Description
Sttr Phase I: Swine Automatic Lameness Sensor (SALS) - The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase 1 project is to provide an in-farm sensing system that will notify sow (adult female swine) farmers of early signs of animal lameness, and thereby reduce early sow mortality and enhance farm productivity.
The technology uses artificial intelligence to analyze pig locomotion in order to spot subtle patterns indicative of lameness. Early detection of lameness will enable farmers to take corrective actions rather than waiting for lameness to deteriorate to sow death or culling. Early culling or sow death is a major economic cost to farmers and a large fraction of death and culls is due to animal lameness.
Successful application of the technology being developed in this project promises to reduce early sow mortality and culling, leading to additional litters per sow and so provide a significant economic boost to farmers. With patent applications for key components of the sensing system, farmers will install sensors in hallways and obtain health measures for each sow when she moves between rooms. The projected annual revenue is $3.0 million.
This Small Business Technology Transfer (STTR) Phase I project proposes combining an imaging sensor with artificial intelligence to create a unique sensing system to unobtrusively and remotely diagnose lameness in sows (adult female swine) as they traverse hallways. This project seeks to validate two key technical contributions.
First, precise 3D animal posture and locomotion are estimated for sows moving beneath a ceiling-mounted sensor. High accuracy is achieved through a novel annotation technique that overcomes difficulties in inaccurate manual location of skeletal landmarks. Second, a data-driven approach is used to train a deep neural network to learn the most discriminating combinations of posture and gait for determining lameness in walking sows. A self-supervised neural network sidesteps the need for extensive manual annotation and expert annotation is only required for lameness assessment.
Together, these two contributions will enable a transformative technical capability of a remote sensor that can automatically diagnose early-stage lameness in sows. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
The technology uses artificial intelligence to analyze pig locomotion in order to spot subtle patterns indicative of lameness. Early detection of lameness will enable farmers to take corrective actions rather than waiting for lameness to deteriorate to sow death or culling. Early culling or sow death is a major economic cost to farmers and a large fraction of death and culls is due to animal lameness.
Successful application of the technology being developed in this project promises to reduce early sow mortality and culling, leading to additional litters per sow and so provide a significant economic boost to farmers. With patent applications for key components of the sensing system, farmers will install sensors in hallways and obtain health measures for each sow when she moves between rooms. The projected annual revenue is $3.0 million.
This Small Business Technology Transfer (STTR) Phase I project proposes combining an imaging sensor with artificial intelligence to create a unique sensing system to unobtrusively and remotely diagnose lameness in sows (adult female swine) as they traverse hallways. This project seeks to validate two key technical contributions.
First, precise 3D animal posture and locomotion are estimated for sows moving beneath a ceiling-mounted sensor. High accuracy is achieved through a novel annotation technique that overcomes difficulties in inaccurate manual location of skeletal landmarks. Second, a data-driven approach is used to train a deep neural network to learn the most discriminating combinations of posture and gait for determining lameness in walking sows. A self-supervised neural network sidesteps the need for extensive manual annotation and expert annotation is only required for lameness assessment.
Together, these two contributions will enable a transformative technical capability of a remote sensor that can automatically diagnose early-stage lameness in sows. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF22551
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
East Lansing,
Michigan
48823-4384
United States
Geographic Scope
Single Zip Code
Related Opportunity
22-551
Analysis Notes
Amendment Since initial award the End Date has been extended from 04/30/24 to 08/31/24 and the total obligations have increased 7% from $275,000 to $295,000.
Motion Grazer Ai was awarded
Project Grant 2232959
worth $295,000
from National Science Foundation in May 2023 with work to be completed primarily in East Lansing Michigan United States.
The grant
has a duration of 1 year 3 months and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
SBIR Details
Research Type
STTR Phase I
Title
STTR Phase I:Swine Automatic Lameness Sensor (SALS)
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase 1 project is to provide an in-farm sensing system that will notify sow (adult female swine) farmers of early signs of animal lameness, and thereby reduce early sow mortality and enhance farm productivity. The technology uses artificial intelligence to analyze pig locomotion in order to spot subtle patterns indicative of lameness. Early detection of lameness will enable farmers to take corrective actions rather than waiting for lameness to deteriorate to sow death or culling.Early culling or sow death is a major economic cost to farmers and a large fraction of death and culls is due to animal lameness.Successful application of the technology being developed in this project promises to reduce early sow mortality and culling, leading to additional litters per sow and so provide a significant economic boost to farmers.With patent applications for key components of the sensing system, farmers will install sensors in hallways and obtain health measures for each sow when she moves between rooms. The projected annual revenue is $3.0 million._x000D_ _x000D_ This Small Business Technology Transfer (STTR) Phase I project proposes combining an imaging sensor with artificial intelligence to create a unique sensing system to unobtrusively and remotely diagnose lameness in sows (adult female swine) as they traverse hallways.This project seeks to validate two key technical contributions. First, precise 3D animal posture and locomotion are estimated for sows moving beneath a ceiling-mounted sensor.High accuracy is achieved through a novel annotation technique that overcomes difficulties in inaccurate manual location of skeletal landmarks.Second, a data-driven approach is used to train a deep neural network to learn the most discriminating combinations of posture and gait for determining lameness in walking sows.A self-supervised neural network sidesteps the need for extensive manual annotation and expert annotation is only required for lameness assessment.Together, these two contributions will enable a transformative technical capability of a remote sensor that can automatically diagnose early-stage lameness in sows._x000D_ _x000D_ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
DH
Solicitation Number
NSF 22-551
Status
(Complete)
Last Modified 7/23/24
Period of Performance
5/1/23
Start Date
8/31/24
End Date
Funding Split
$295.0K
Federal Obligation
$0.0
Non-Federal Obligation
$295.0K
Total Obligated
Activity Timeline
Transaction History
Modifications to 2232959
Additional Detail
Award ID FAIN
2232959
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
DWBFHYLTN9R7
Awardee CAGE
None
Performance District
MI-07
Senators
Debbie Stabenow
Gary Peters
Gary Peters
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| Research and Related Activities, National Science Foundation (049-0100) | General science and basic research | Grants, subsidies, and contributions (41.0) | $275,000 | 100% |
Modified: 7/23/24