Google Cloud (Mountain View, California, USA) and Simple Technology Solutions (STS) (Washington, DC, USA)—a Google Cloud partner and small business specializing in multi-cloud solutions for the federal government—announced that they are working with the U.S. Navy to modernize the maintenance and repairs inspection process for its vessels and facilities.
STS will use Google Cloud artificial intelligence (AI) and machine learning (MI) technologies on inspection drone-captured images to detect, prioritize, and predict maintenance needs. As part of its first phase, STS will train its AI and ML models to identify corrosion, which will streamline the labor-intensive manual inspection process and drastically reduce safety risks.
According to Google Cloud, this is how the process will work: first, STS will leverage public domain and inspection drone images to build a high-quality AL/ML model; second, it will collaborate with Navy corrosion expects to label and train the data; and third, it will iteratively train and validate the model using custom inspection drone flight data, which will be uploaded using Google Cloud storage so that the models can be improved and updated on a continuing basis.
“This is about automation, saving time and money, and keeping inspectors out of harm’s way,” says Aaron Kilinski, chief technology officer for STS. “The initial goal for Phase I is to build a model that detects corrosion in drone images with a very high degree of accuracy. The ultimate goal, however, is to move from detection to prediction by expanding the subjects and sensors, and eventually integrating with Navy systems.”
“The manual inspection of Navy ships and vessels is a time-intensive, costly process that can drive up costs and slow down deployment,” says 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.”