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  November 9, 2020 | International, Aerospace

  BAE Systems secures US Army 'A-Team' technology development deals

  by Carlo Munoz BAE Systems has secured several US Army research and development pacts that are designed to help create advanced technologies to team manned, unmanned, and autonomous aircraft in future combat operations. The company's FASTLabs research directorate was awarded the army contracts, totalling USD9 million, which will focus technology development projects for human-machine interface, resource capability, and situational awareness management on the service's Advanced Teaming Demonstration Program (A-Team). The three focus areas in which BAE Systems' engineers were contracted to take on under the A-Team programme are “designed to advance manned and unmanned teaming (MUM-T) capabilities that are expected to be critical components in the U.S. Army's Future Vertical Lift (FVL) program,” according to a company statement issued on 3 November. Company officials anticipate the development of a “highly automated system to provide situational awareness, information processing, resource management, and decision making that is beyond human capabilities”, the statement said. “These advantages become exceedingly important as the Army moves toward mission teams of unmanned aircraft that will be controlled by pilots in real time,” it added. A majority of BAE Systems' A-Team work will leverage the company's Future Open Rotorcraft Cockpit Environment Lab, which will host “simulation tests and demonstrations with products from different contractors” vying to integrate their MUM-T applications into the army's FVL programme. Teaming of manned and unmanned aerial assets was a key objective of the army's initial capstone exercise for Project Convergence. https://www.janes.com/defence-news/news-detail/bae-systems-secures-us-army-a-team-technology-development-deals

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  August 28, 2020 | International, Naval

  Navy Turns To AI To Save Billions In Fight Against Rust

  By KELSEY ATHERTON ALBUQUERQUE: The Navy is using Google Cloud to speed up a basic but time consuming task: finding and identifying rust. This approach has already been applied to inspect wind turbines and find potholes in roads, and promises advantages both in speed of inspection and in future predictive maintenance. “The AI technology behind this enabled the US Navy to quickly and seamlessly examine tens of thousands of images to prioritize the needs to be repaired immediately and or later on,” Mike Daniels, vice president of Global Public Sector, Google Cloud, told me in an interview. While Google was unwilling to disclose the exact value of the contract, the promise is that speedy, AI-enabled inspections will lower labor and material costs of inspection and repair enough to more than justify the expenditure on inspection AI. “The tools we're providing can not only save the Navy billions each year, but significantly improve readiness and speed deployment,” said Daniels. “And this is a physical job right now. We're improving results for the inspectors.” If AI-facilitated rust inspection can reduce the amount of time a ship needs to stay in harbor for repairs, it can narrow the window in which catastrophic disasters, like the fire which tore apart the Bonhomme Richard, can happen. This work is being done through Simple Technology Solutions (STS), who was awarded the work as a Phase 1 Small Business Innovation Research project. To train the AI, STS flew a drone on inspections to get images of rust. Next, STS combined these drone-filmed images with public domain images of ships, and uploaded both sets to a Google Cloud server. Specifically, the inspections will look for broad area rust and corrosion, as well as subtler damage that human eyes might skip over, like pitting or focused damage. Using native machine learning built into the Google Cloud, STS could then train the algorithm to process, understand and identify rust in the images. This is an iterative process, one where every uploaded inspection improves the accuracy of the next inspection. “There's no classified data that's going to be handled as part of this project,” said Daniels, noting that Google offers a high level of protection for images stored in its cloud by default. As we have seen in the past, aggregated unclassified data can sometimes be enough to reveal classified information, but the immediate utility of cloud-powered inspections should offset any distant concern of weakness revealed through corrosion maintenance. Most importantly, the inspection tool promises savings in time. A widely-cited 2014 report from the US Navy attributed the cost of fighting rust and corrosion at $3 billion. Some of that cost is hard to shake: the paint used to cover rust-scrapped areas can cost as much as $250 a gallon. Catching corrosion quickly and early shortens the amount of time humans need to work to fix a vessel, and should reduce the area that needs repair for each inspection. https://breakingdefense.com/2020/08/navy-turns-to-ai-to-save-billions-in-fight-against-rust/

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  June 21, 2021 | International, Aerospace

  Insights From Aerospace & Defense Leaders | Aviation Week Network

  As part of our Aerospace & Defense Community Forum, Aviation Week Network spoke with leaders across the Aerospace & Defense industry about their companies, the state of the industry currently and where it is headed in the future. See what they had to say.