The F-35 Is About to Get A Lot Smarter

A California company is looking to accelerate the Defense Department’s embrace of artificial intelligence, starting with some of its most important aircraft.

War in the 21st century runs on data, a lot of it in the case of the F-35 Joint Strike Fighter. The Mission Data Files that inform F-35 deployments and missions can take up to 18 months to compile, bringing in info on everything from enemy radar and anti-aircraft missiles to waveforms and cyber weapons. Now the Pentagon has hired a California company to shrink that compilation time to just one month, using artificial intelligence.

The company, C3, sees itself as a sort of AI tailor, stitching together different methodologies — from simple machine learning to more sophisticated deep learning—and combining heterogeneous forms of data that don’t play well together—from images to diagnostic valuations to text—into products that are specific to the problem. Some might be heavier on deep learning, some on machine, in which case the company works to accelerate the laborious task of data labeling.

They’ve been quietly doing business with the Defense Department for 15 months, after an initial outreach from the Defense Innovation Unit. Already they’re involved in nine projects, mostly related to predictive maintenance for aircraft such as the E-3 Sentry AWACS, the C-5 Galaxy, the F-16, and soon, the F-35, predicting when a part or computer system might fail on the basis of weather, deployment, mission, the age and condition of its components, and so forth.

Of course, the F-35 already has an onboard diagnostic system, the Autonomic Logistics Information System, or ALIS. Nikhil Krishnan, C3’s vice president for products, said their software won’t replace ALIS, or anything that Lockheed Martin or its F-35 subcontractors have already built. Instead, it aims to combine information from those sources to create a better, fuller picture of what’s going on with the plane.

Beside ALIS, Krishnan said, C3’s software will devour  “operational data, sorties, it could include weather, the history of the part, was there repair work done on it before? We’re really on a higher level than any of these subsystems, including ALIS.” The hope is to be able to preposition parts and maintainers to make fast repairs or modifications not only in response to what the plane has been through but, perhaps, what it’s about to go through as well.

All that is separate from C3’s work on  Mission Date File optimization, which is set to complete development next summer. The file serves as a sort of threat library. “It’s the data on board that proactively notifies the pilot of the aircraft of upcoming threats. The problem today is that it takes way too long to actually generate that Mission Data File. We can apply the data aggregation capabilities that C3 has and AI to make that process an order of magnitude faster so the data are more current,”  said Edward Abbo, C3’s President and CTO.

Read the full article on Defense One.

Find more information on C3IOT here.