SBIR-STTR Award

Deep BioThreatID
Profile last edited on: 7/18/2018

Program
SBIR
Agency
DARPA
Total Award Amount
$224,421
Award Phase
1
Principal Investigator
John Kaufhold
Activity Indicator

Company Information

Deep Learning Analytics LLC

4601 North Fairfax Drive Suite 1200
Arlington, VA 22203
   (571) 969-5638
   N/A
   www.deeplearninganalytics.com
Multiple Locations:   
Congressional District:   08
County:   Arlington

Phase I

Phase I year
2017
Phase I Amount
$224,421
United States Department of Defense personnel make direct contact with unfamiliar and potentially harmful plants, insects, arachnids, and reptiles (i.e. biothreats), impairing personnel readiness and mission effectiveness. These threats endanger personnel, disrupt operations and destabilize ecosystems around the world, often requiring expensive remediation. Currently the DoD employs specialized field and medical staff and implements comprehensive training programs to manage these threats. This expensive approach relies heavily on availability of scarce, highly trained medical service staff and other expert personnel. An effective BioThreatID application capable of identifying plants, insects, arachnids, and reptiles from photographs on a small mobile device without a network connection could provide a cost-effective means to improve safety, health, and effectiveness of DoD and associated personnel, while reducing DoD dependence on expensive expertise. Deep Learning Analytics will combine new data with state of the art deep learning algorithms. Deep Learning Analytics will optimize those algorithms for resource-constrained operation to allow them to be deployed on low size, weight and power devices, e.g. mobile phones. This enables a handheld BioThreatID application to visually identify plants, insects, arachnids, and reptiles in the field in diverse global ecosystems, giving DoD personnel a practical, accessible means of identifying these threats.

Phase II

Phase II year
---
Phase II Amount
---