Machine-learning tools supplied to U.S. Navy by Charles River Analytics


June 14, 2022

Lisa Daigle

Assistant Managing Editor

Military Embedded Systems

CAMBRIDGE, Mass. Engineering firm Charles River Analytics reports that its engineers are developing technology it calls DATEM [Distributed Analysis Tool for Enterprise Monitoring] for the US Navy that uses innovative machine-learning (ML) technology to monitor and analyze data about the health and status of a critical system, and then communicates the results in a human-understandable form and recommends corrective action.

The first major success for the DATEM project — in which the Navy has invested $2.39 million and almost six years so far — has been the Cable Calibration Tool (CCT), which identifies and localizes faults in the Ship’s Signal Exploitation Equipment (SSEE) signal chain, the most technologically advanced cryptologic collection system operated by the Navy. According to information from Charles River Analytics, its CCT prototype detected 91% of faults, and outperformed the existing approach by 35%; Charles River developed the CCT to Technology Readiness Level 8, the highest possible level until experience under mission conditions. The CCT is now used every day by the Navy.

Charles River engineers have turned their attention to creating the Rapid Analysis Dashboard (RAD), which will enable a unified view of data collected from a variety of Navy sources in order to perform rapid analysis of supply and demand for parts. It is expected that the RAD will be fielded in an operational environment later in 2022.

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