2330500
Project Grant
Overview
Grant Description
Sbir Phase I: Early Disease Prediction with Cattle Muzzles Using Artificial Intelligence, Facial Recognition, and Camera Capturing Technology -this small business innovation research (SBIR) phase I project addresses the need for technologies that can benefit the production, protection, and health of agricultural animals, like cattle. The profit margins for cattle owners are very thin. Treating a disease costs cattle owners on average about $80 per head.
By the time an owner can tell their cattle are infected, it is typically too late to prevent infection and the spread of the disease in the pen and feedlot. With the successful implementation of the proposed technology, cattle owners will save on average about $80 per head. For an average 500-head owner, pinkeye can impact 90% of the individual cattle herd if one individual animal is infected, costing over $15K to treat in the case of an outbreak.
The proposed technology aims to reduce the cost to only the cost of one vaccine since the proposed system should alert the owner about this risk early, allowing early isolation before the disease is able to spread. The proposed solution would enable early disease detection, help to secure the US food supply chain, reduce the emission of greenhouse gasses, and benefit the US economy by preventing cattle loss. This small business innovation research (SBIR) phase I project proposes to demonstrate the feasibility of a novel artificial intelligence (AI) technology to detect bovine respiratory disease early on in a small pilot study.
The company will develop an app (beta-version) that can automatically take pictures of cattle, use AI to analyze the muzzle, and then immediately send a notification of infected cattle to the cattle owner. When new calves that are sick enter a feedlot setting, they typically are not as active as healthy calves. There are also visible symptoms such as droopy ears, nasal discharge, and watery eyes.
However, since the calves might be stressed due to travel, these symptoms do not necessarily mean the calf is sick, making it challenging to identify sick cattle. If successful, the proposed solution would reliably identify sick cattle and thereby enable early, targeted treatment. 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.- subawards are not planned for this award.
By the time an owner can tell their cattle are infected, it is typically too late to prevent infection and the spread of the disease in the pen and feedlot. With the successful implementation of the proposed technology, cattle owners will save on average about $80 per head. For an average 500-head owner, pinkeye can impact 90% of the individual cattle herd if one individual animal is infected, costing over $15K to treat in the case of an outbreak.
The proposed technology aims to reduce the cost to only the cost of one vaccine since the proposed system should alert the owner about this risk early, allowing early isolation before the disease is able to spread. The proposed solution would enable early disease detection, help to secure the US food supply chain, reduce the emission of greenhouse gasses, and benefit the US economy by preventing cattle loss. This small business innovation research (SBIR) phase I project proposes to demonstrate the feasibility of a novel artificial intelligence (AI) technology to detect bovine respiratory disease early on in a small pilot study.
The company will develop an app (beta-version) that can automatically take pictures of cattle, use AI to analyze the muzzle, and then immediately send a notification of infected cattle to the cattle owner. When new calves that are sick enter a feedlot setting, they typically are not as active as healthy calves. There are also visible symptoms such as droopy ears, nasal discharge, and watery eyes.
However, since the calves might be stressed due to travel, these symptoms do not necessarily mean the calf is sick, making it challenging to identify sick cattle. If successful, the proposed solution would reliably identify sick cattle and thereby enable early, targeted treatment. 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.- subawards are not planned for this award.
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=NSF23515
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Overland Park,
Kansas
66223-1253
United States
Geographic Scope
Single Zip Code
Myaniml was awarded
Project Grant 2330500
worth $274,866
from National Science Foundation in July 2024 with work to be completed primarily in Overland Park Kansas United States.
The grant
has a duration of 1 year and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I: Early Disease Prediction with Cattle Muzzles Using Artificial Intelligence, Facial Recognition, and Camera Capturing Technology
Abstract
This Small Business Innovation Research (SBIR) Phase I project addresses the need for technologies that can benefit the production, protection, and health of agricultural animals, like cattle. The profit margins for cattle owners are very thin. Treating a disease costs cattle owners on average about $80 per head. By the time an owner can tell their cattle are infected, it is typically too late to prevent infection and the spread of the disease in the pen and feedlot. With the successful implementation of the proposed technology, cattle owners will save on average about $80 per head. For an average 500-head owner, pinkeye can impact 90% of the individual cattle herd if one individual animal is infected, costing over $15k to treat in the case of an outbreak. The proposed technology aims to reduce the cost to only the cost of one vaccine since the proposed system should alert the owner about this risk early, allowing early isolation before the disease is able to spread. The proposed solution would enable early disease detection, help to secure the US food supply chain, reduce the emission of greenhouse gasses, and benefit the US economy by preventing cattle loss.
This Small Business Innovation Research (SBIR) Phase I project proposes to demonstrate the feasibility of a novel artificial intelligence (AI) technology to detect Bovine Respiratory Disease early on in a small pilot study. The company will develop an app (beta-version) that can automatically take pictures of cattle, use AI to analyze the muzzle, and then immediately send a notification of infected cattle to the cattle owner. When new calves that are sick enter a feedlot setting, they typically are not as active as healthy calves. There are also visible symptoms such as droopy ears, nasal discharge, and watery eyes. However, since the calves might be stressed due to travel, these symptoms do not necessarily mean the calf is sick, making it challenging to identify sick cattle. If successful, the proposed solution would reliably identify sick cattle and thereby enable early, targeted treatment.
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
AI
Solicitation Number
NSF 23-515
Status
(Complete)
Last Modified 7/8/24
Period of Performance
7/1/24
Start Date
6/30/25
End Date
Funding Split
$274.9K
Federal Obligation
$0.0
Non-Federal Obligation
$274.9K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2330500
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
DKEHMSBLPPH1
Awardee CAGE
None
Performance District
KS-03
Senators
Jerry Moran
Roger Marshall
Roger Marshall
Modified: 7/8/24