Innovating for National Security
Empowering MASINT through collaboration and cutting-edge methodologies.
Innovating for National Security
Empowering MASINT through collaboration and cutting-edge methodologies.
Empowering MASINT through collaboration and cutting-edge methodologies.
Empowering MASINT through collaboration and cutting-edge methodologies.

At the US MASINT Foundation, our mission is to ensure the long-term impact of Measurement and Signature Intelligence (MASINT). Our vision is to create an inclusive, dynamic community built on collaboration and forward-thinking approaches. Our goal is to ensure MASINT’s long-term impact by fostering a practitioner network that thrives on innovation, develops new methodologies, and supports the ever-evolving demands of national security. In this new era, we believe that the traditional models must evolve. By partnering with government, industry, and academia, the foundation is committed to shaping the future of MASINT, making it more relevant, more accessible, and more effective in meeting the challenges of tomorrow.
Predictive Acoustic Signature Analysis for Mechanical Health Monitoring was a collaborative research project between the U.S. MASINT Foundation and the Digital Transformation Center, focused on developing a low-cost acoustic sensing platform for early mechanical health monitoring.
The project ultimately established a semi-automated workflow for identifying mechanical degradation, monitoring system health, and characterizing differences between similar mechanical systems, providing a foundation for future predictive maintenance and machine learning applications.
Nicholas Manzo is a software developer and recent graduate of Sinclair Community College, where he earned an Associate of Applied Science in Software Development. His experience includes embedded systems, Python-based analytics, database-driven applications, and software development using C++, Python, Java, and SQL.
As a summer intern with the US MASINT Foundation, Nicholas contributed to the development of embedded sensing systems and analytics-driven software while gaining hands-on experience integrating hardware, data acquisition, and machine learning concepts to solve engineering challenges.
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US MASINT Foundation
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