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Award Detail

Doing Business As Name:IMAGINAG TECH, LLC
  • Shoshana Ginsburg
  • (303) 956-7387
Award Date:06/10/2021
Estimated Total Award Amount: $ 997,350
Funds Obligated to Date: $ 997,350
  • FY 2021=$997,350
Start Date:06/15/2021
End Date:05/31/2023
Transaction Type: Cooperative Agreements
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.041
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:SBIR Phase II: An Automated Drone-Based Cattle Monitoring Service
Federal Award ID Number:2036703
DUNS ID:081304732
Program:SBIR Phase II
Program Officer:
  • Peter Atherton
  • (703) 292-8772

Awardee Location

Street:2495 DEBORAH DR
Awardee Cong. District:11

Primary Place of Performance

Organization Name:IMAGINAG TECH, LLC
Street:4339 University Pkwy
City:University Heights
County:University Heights
Cong. District:11

Abstract at Time of Award

The broader impact of this Small Business Innovation Research (SBIR) Phase II project will result from the development of disruptive technologies that use drones and artificial intelligence to monitor livestock. Almost 75% of United States cattle are purchased by taking out bank loans, and lenders need to audit cattle inventories for collateral verification and appraisal purposes. Additionally, more than 140,000 ranchers need to monitor their herds and detect cattle illnesses before infections spread. The proposed technology will leverage aerial imaging and artificial intelligence to count cattle, characterize cattle weight, and diagnose cattle illnesses up to one week before clinical symptoms appear. The ability to count herds regularly will enable ranchers to discover cattle rustling issues early and provide banks with a reliable way to perform collateral verification on ranches and feedlots, ensuring that banks can continue extending livestock operations the loans that they need to survive. The ability to detect cattle illnesses early is expected to reduce cattle mortalities, the economic cost of antibiotic use, and possibly antibiotic resistance in humans. Ultimately, the proposed technology that will be developed for monitoring cattle promises to also transform the way that land and marine wildlife, fisheries, and endangered species are monitored. This Small Business Innovation Research (SBIR) Phase II project will provide cattlemen and bankers with an efficient way to detect and count cattle on pastures and ranches, estimate livestock weight, and identify ill cows before they spread infection further. Despite daily monitoring of cattle herds, small discrepancies and losses are undiscoverable, and bovine illnesses are often left undetected until they spread, infecting more cattle and requiring large-scale administration of antibiotics. Machine learning and image processing tools will be developed that (a) automatically analyze natural and thermal drone images to count cattle on multi-topography ranches and estimate livestock weight and (b) discriminate between healthy and ill cattle based on aerial radiometric imaging. The outcomes will be (1) a ready, drone-agnostic solution for counting cattle and estimating their weight and (2) a pilot-tested drone-and-software system for monitoring cattle health via radiometric imaging and notifying cattlemen about cows with suspected illness in real-time. 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.

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