Navy Program Will Use AI on Drone Images to Predict Fleet Maintenance Needs

The aircraft carrier USS Dwight D. Eisenhower (CVN 69), front, the amphibious assault ship USS Bataan (LHD 5) and the amphibious transport dock ship USS New York (LPD 21) transit the Arabian Sea, April 2, 2020.

The aircraft carrier USS Dwight D. Eisenhower (CVN 69), front, the amphibious assault ship USS Bataan (LHD 5) and the amphibious transport dock ship USS New York (LPD 21) transit the Arabian Sea, April 2, 2020. Brennen Easter/Navy

Simple Technology Solutions will use Google Cloud to build a machine learning tool trained on drone images.

The Navy has been using drones to inspect the maintenance needs of its fleet and is getting ready to add some artificial intelligence and machine learning in the mix to help it prioritize repairs and predict future needs.

Thursday morning, Google Cloud and Simple Technology Solutions, or STS, announced an award through the Navy’s Small Business Innovation Research program to add predictive analytics to the branch’s maintenance program.

Once up and running, the AI tool will use images taken by inspection drones to identify maintenance needs—particularly rust and corrosion—and prioritize the most pressing repairs. Eventually, the tool will be expected to predict future maintenance needs, as well.

For Phase I of the project, STS will use the Google Cloud AutoML tool to build a machine learning model trained on unclassified corrosion data from Navy inspection drone data, as well as public sources. Navy corrosion experts will work hand-in-hand with STS engineers to properly label images as they are ingested to ensure the model is trained accurately.

Phase I work has already begun using drones from commercial company DroneUp, a Google Cloud spokesperson told Nextgov.

“The ultimate goal, however, is to move from detection to prediction by expanding the subjects and sensors, and eventually integrating with Navy systems,” STS Chief Technology Officer Aaron Kilinski said.

To get there, the team will likely incorporate “additional Navy assets, data sets, sensors and integration with Navy systems,” the spokesperson said.

“This is about automation, saving time and money, and keeping inspectors out of harm’s way,” Kilinski said.

The project was awarded through the SBIR program “due to the technology innovation and potential for commercialization,” the release states, citing the two main focuses of the program—getting cutting-edge research into the military and supporting the broader economy through technology transfer.

“The manual inspection of Navy ships and vessels is a time-intensive, costly process that can drive up costs and slow down deployment,” said Mike Daniels, vice president of global public sector for Google Cloud. “We’re proud to work with the U.S. Navy and empower them with Google Cloud technology to transform corrosion inspections for greater efficiency and safety.”

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