AI in the US Navy Includes Underwater Entity Detection

Militaries around the world are starting to increase investments in artificial intelligence and machine learning capabilities. The top military defense contractors in the US, Europe, and Israel are all working on AI software to sell into the defense sector. That said, the military adoption of AI is as of right now slow in comparison to that of contractors.

In this article, we’ll be covering the AI applications that military defense contractors intend to sell for use in the US Navy. Many of the applications covered in this report appear to currently be in the exploratory or testing phases.

The defense contractors discussed in this report offer software for the following use cases for artificial intelligence in the Navy:

• Alion Science & Technology and Hydroid – Entity Detection and Classification
• L3 Technologies and Raytheon – Precision-guided Munitions
• Lockheed Martin and Rite Solutions – Cross-platform Data Access and Analysis

We’ll run through each of these companies and their AI-based software, munitions, and vehicles one by one, starting with Alion Science & Technology:

Entity Detection and Classification

Alion Science & Technology Offers Findr, with Machine Vision

Alion Science & Technology offers Findr, which it claims can help the Navy detect and characterize entities using machine vision.

Alion claims the Navy can integrate the software into the navigation system of an autonomous vehicle to sense and track targets through obstructions in the working environment.

The company states the machine learning model behind the software was trained on traditional Doppler radar data showing the nature and activity of the entity during observation from various angles and in various lighting conditions. These images would have been labeled as targets or non-targets. These labeled images would then be run through the software’s machine learning algorithm.

This would have trained the algorithm to discern the sequences and patterns of 1’s and 0’s that, to the human eye, form the image of a target and non-target as displayed on the radar.

The user could then upload radar images that are not labeled into Findr. The algorithm behind the software would then be able to identify images representing targets from non-targets. The system then alerts a human employee of potential targets in the area in real time.

Alion lists GSA Federal Systems Integration and Management Center and the Naval Undersea Warfare Center as clients.

Chris Milroy is Director of Artificial Intelligence at Alion. He holds a BA in Economics, Philosophy from the University of Chicago. Previously, Milroy served as Chief Scientist of the Nascent Technology Center at Engility Corporation.

Hydroid’s REMUS AUVs Help Navy Detect Threats

Hydroid offers the Remote Environmental Monitoring Unit System, or REMUS, series of autonomous underwater vehicles (AUVs), which it claims can help the Navy detect threats using machine vision.

Hydroid claims the Navy can integrate the REMUS software into existing intelligence and surveillance and reconnaissance systems above water.

The company states that the REMUS AUV would be able to detect and identify threats to depths of as much as 6,000 meters underwater.

Hydroid claims to have helped the U.S. Navy find and destroy underwater mines. The Navy used REMUS AUVs together with land-based systems to launch mine countermeasure (MCM) exercises. According to the case study, Hydroid increased the Navy’s warfare capabilities by keeping adversaries “guessing.” We were unable to find any more tangible results for the application, although it would likely be difficult to quantify the results of such an application.

Hydroid also lists Microsoft co-founder Paul Allen and the Woods Hole Oceanographic Institution as some of their past clients.

Andrew Keefer is Software Engineer at Hydroid. He holds a BS in Physics and Physical Oceanography from the University of Rhode Island. Previously, Keefer served as Software Engineer at Teledyne Benthos.

Read the source article at: Emerj.

from AI Trends http://bit.ly/2Uru5Jh
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