AFIMSC innovation project utilizing UAS and machine learning receives SBIR award from Air Force

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On Thursday, March 12, an Air Force Installation and Mission Support Center (AFIMSC) innovation project received a $3 million Small Business Innovation Research program award from the Air Force. 

Through the project, drones and machine learning are used to revolutionize how the Air Force Civil Engineer Center collects data for its environmental mission. The drone project was one of the first innovation initiatives that the innovation office pursued after it was established in Nov. 2018.

“This speaks to the ability we have to commit and work with a company,” says Dr. Will Roper, assistant secretary of the Air Force for acquisition, technology and logistics, in announcing the award.

“The stakes couldn’t be higher and (this award) shows the type of agility and flexibility we have in the Air Force.”

The initiative is a result of a partnership between AFIMSC, Air Force Innovation Hub Network (AFWERX) and a small business called Aerial Applications that provides UAS services and mapping software. For AFIMSC, the award represents its first innovation partnership.

“We’ve achieved tremendous success very quickly, which could not have been possible without teammates who work well together,” says Marc Vandeveer, AFIMSC chief innovation officer.

Presented to Aerial Applications, the SBIR award brings the amount of government investments to $6 million over four years. Aerial Applications has also secured $50 million in funding from industry and venture capitalists, raising the total investment to $56 million.

“The fact that this project won the award is a testament to the Air Force’s renewed focus on innovation and moving our capabilities forward with strong commercial partnerships and powerful execution of our dollars,” says Emilie Miller, a project manager in the AFIMSC Innovation Office.
 
In fall 2019, AFIMSC and Aerial Applications began field testing the project by flying a UAS equipped with light detection and ranging, multi-spectral sensors and machine-learning algorithms to map, survey and inventory habitat for the golden-cheeked warbler at Camp Bullis, Texas.

More field tests at Camp Bullis are planned for later this month. Vandeveer says the initial project will expand to include other species and will be applied to more than 20 different uses in at least 12 locations.

Miller believes that as a result of the SBIR award and additional funding, the technology will eventually be applied to a variety of installation and mission support requirements outside of environmental management.

“Through our strategic partnership with Aerial Applications and their capabilities, we’re looking forward to proving this technology’s value and scalability across the Air Force,” Miller adds.

“We’re so excited. We have shown we can accomplish amazing things through perseverance, go-getter attitudes and making connections to find the right path forward.”

Photo below: ​An unmanned aerial system flies over Camp Bullis, Texas, during a field test Sept. 4, 2019. The UAS was equipped with Light Detection and Ranging, multi-spectral sensors and machine-learning algorithms to map, survey and inventory habitat for the golden-cheeked warbler. The field test will help the Air Force determine if UAS technology can characterize habitat better, faster and cheaper than current methods. (U.S. Air Force photo by Malcolm McClendon)