On a US Navy ship somewhere in the Atlantic, a calibration test fails. A request for remote technical help is sent to help desk staff onshore. They look for clues in the test data, but the clues are too subtle. The staff must escalate the help request to the next level of support. An expert electrical engineer, taking time away from high-level design tasks, analyzes the data using custom-developed scripts. Meanwhile, until the data is analyzed, there’s a risk of lost mission capability.
A ship’s signals intelligence system generates an abundance of such data daily and even hourly; to ensure mission readiness, an alert system for data monitoring and analysis is essential. At Charles River Analytics, engineers are developing DATEM (Distributed Analysis Tool for Enterprise Monitoring) to address this need. Incorporating cutting-edge machine learning (ML) technology, DATEM not only monitors and analyzes data about the health and status of a critical system, but also communicates the results in a human-understandable form and recommends corrective action.
The Navy has invested $2.39 million and almost 6 years in the development of this high-priority project. DATEM’s first major success was the Cable Calibration Tool (CCT). The CCT 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. Charles River exceeded expectations in developing CCT, achieving real-time integration of the prototype with government systems. The CCT prototype detected 91% of faults, and outperformed the existing approach by 35%, a notable success rate. Charles River developed the CCT to Technology Readiness Level 8, the highest possible until experience under mission conditions. The CCT is now in daily use by the Navy.
Charles River engineers are currently applying their expertise to create the Rapid Analysis Dashboard (RAD). The RAD will provide a unified view of data collected from a variety of Navy sources, which will enable rapid analysis of supply and demand for parts. The RAD will be fielded in an operational environment later this year.
CCT and the RAD may be applicable or adaptable for other Navy systems that collect similar data. DATEM also has potential for non-military use: Information technology and operations management companies could add DATEM’s fault detection and alert capabilities to their existing products. DATEM tools could also provide monitoring and alert services for the Internet of Things (IoT), which is predicted to include more than 64 billion devices by 2025 and generate $4 billion to $11 billion in economic value.
The development of DATEM draws on Charles River’s expertise in data visualization, probabilistic reasoning technology, causal modeling, neural networks, and intelligent systems. Widely regarded as a success story, DATEM is a cornerstone of Charles River’s emerging leadership in applying ML to health and status data.
Contact us to learn more about DATEM and our capabilities in artificial intelligence and machine learning.
This material is based upon work supported by the Naval Information Warfare Systems Command under Contract No. N68335-18-C-0358. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Naval Information Warfare Systems Command.