SBIR-STTR Award

Evaluation of Unmanned Aerial Systems Technology for Pine Beetle Detection
Award last edited on: 6/23/2023

Sponsored Program
SBIR
Awarding Agency
DOD : AF
Total Award Amount
$799,973
Award Phase
2
Solicitation Topic Code
AF191-004
Principal Investigator
Gareth Block

Company Information

Third Insight (AKA: Visual Semantics Inc)

4309 Adirondack Summit Drive
Austin, TX 78738
   (936) 647-5517
   N/A
   www.thirdinsight.ai
Location: Single
Congr. District: 25
County: Travis

Phase I

Contract Number: FA3002-19-P-A139
Start Date: 3/6/2019    Completed: 3/6/2020
Phase I year
2019
Phase I Amount
$50,000
Third Insight has developed a plug-and-play software platform called "HALO" that gives commercial, off-the-shelf (COTS) drones the ability to navigate autonomously in GPS-denied environments. HALO is a light-weight 3D computer vision and machine learning application that can be installed on-board COTS drones (for full autonomy) or on mobile devices or computers that are connected to the drone via remote control. Operating in GPS-denied environments is critical not just for defense, but also for commercial customers in the airline, insurance, construction, and other markets, who have an urgent need to fly UAVs indoors and in cluttered, outdoor spaces where GPS may not be available. Letters of Support are included from AFCENT, who has selected Third Insight's HALO platform as a potential solution to address USAF urgent needs during forward deployment. AFCENT has identified key customer discovery requirements that Third Insight would accomplish within this Phase I SBIR. HALO is a dual-purpose technology that Third Insight is developing for USAF and commercial UAV-based aircraft inspection markets. Letters of Support are also included from Two-Star General Dawn Ferrel and Third Insight's commercial partner, Flatirons Solutions, who are providing complementary support to this SBIR through other contracts.

Phase II

Contract Number: FA3002-19-P-A169
Start Date: 7/14/2019    Completed: 10/31/2021
Phase II year
2019
Phase II Amount
$749,973
This Phase II effort supports an AFIMSC/AFWERX pilot study to test the feasibility of utilizing small-scale unmanned aircraft system (UAS) platforms outfitted with image capturing sensors to perform early detection of pine beetle infestations within a pine forest. The pilot study will test the hypothesis that remote controlled UAS can be a more efficient and more cost-effective means to detect and control an incipient pine beetle attacks before infestations expand to epidemic proportions. Machine learning algorithms will be used to: fuse visible(EO), long-wave infrared (LWIR), hyperspectral, and 3D laser-range finding (LIDAR) imaging data; discriminate between tree species and other ground cover; predict "health indices" that measure tree stress from aerial views of forests; deliver these results visually within a GIS software application to support planning by USAF and US Fish & Wildlife personnel. Imaging data will be obtained from ponderosa pine-dominated forests outside Austin, Texas and at the United States Air Force Academy (USAFA) in Colorado.