STS will use Google Cloud artificial intelligence and machine learning technologies on inspection drone-captured images to detect, prioritize, and predict its maintenance needs.
STS will train Google Cloud AI and ML models on tens of thousands of images to identify corrosion as part of the first phase with the Navy. Using imagery and Google AI/ML technologies, STS will try to reduce the labor burden and safety risk associated with maintenance inspections.
“The initial goal for Phase I is to build a model that detects corrosion in drone images with a very high degree of accuracy,” according to Aaron Kilinski, chief technology officer, STS. “The ultimate goal, however, is to move from detection to prediction by expanding the subjects and sensors, and eventually integrating with Navy systems.”
The U.S. Navy currently spends billions per year on maintaining and repairing its fleet of vessels and other platforms like aircraft and facilities. It is a largely manual, labor-intensive process.