The Department of Homeland Security (DHS) Small Business Innovation Research (SBIR) Program recently awarded funding to two small businesses to develop non-contact, inexpensive machine learning training and classification technologies. Integrated machine learning platforms can significantly reduce time, redundancy, cost, and improve the accuracy in detecting threats such as explosives, chemical agents, and narcotics.

“S&T embraces the significant advances in artificial intelligence and machine learning capabilities and their ability to enhance threat detection,” said Kathryn Coulter Mitchell, DHS Senior Official Performing the Duties of the Under Secretary for Science and Technology. “The SBIR Program provides the opportunity for S&T to partner with innovative small businesses and develop machine learning tools critical to addressing threat detection needs. I am looking forward to seeing the technologies that will be developed by these SBIR efforts.”

Physical Sciences Inc. (PSI), based in Andover, MA, and Alakai Defense Systems, Inc. (Alakai), based in Largo, FL, each received approximately $1 million in SBIR Phase II funding to develop technologies that can rapidly and accurately identify unknown spectrometer signals as safe or threatening. The DHS SBIR Program, managed by Program Director Dusty Lang and administered at the DHS Science and Technology Directorate (S&T), selected PSI and Alakai to participate in Phase II of the program subsequent to demonstration of feasibility in Phase I, for each companies’ compact, accurate and rapid classification Machine Learning Module for Detection Technologies solutions.

Under Phase II, PSI will continue to develop their deep-learning algorithm for detection and classification of trace explosives, opioids, and narcotics on surfaces, for optical spectroscopic systems. PSI will extend the algorithm’s capabilities from infrared reflectance spectroscopy to include Raman spectroscopy, as well as a proposed operational module prototype, which will have a classification accuracy of greater than 90 percent.

During their Phase II efforts, Alakai, will continue development of the Agnostic Machine Learning Platform for Spectroscopy (AMPS) that rapidly and accurately detects trace quantities of hazardous and related chemicals from a variety of spectroscopic instruments.

“Our impetus for developing these machine-learning modules stems from the Transportation Security Administration’s operational needs for threat signature fusion, the ability to learn, detect and classify new threats without being explicitly programmed, and, ultimately, increase accuracy of detection,” said Thoi Nguyen, DHS S&T Program Manager for the Next Generation Explosive Trace Detection (NGETD) Program. “With experienced industrial partners like Alakai and PSI, and our strong collaboration with TSA, we hope these efforts will contribute to wider applications of machine learning across the Homeland Security mission space.”

At the completion of the 24-month Phase II contract, SBIR awardees will have developed a prototype to demonstrate the advancement of the technology, spearheading the potential for Phase III funding.

Under Phase III, SBIR performers will seek to secure funding from private and/or non-SBIR government sources, with the eventual goal to commercialize and bring to market the technologies from Phases I and II.

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NEW YORK, Jan. 26, 2021 /PRNewswire/ — Fulcrum Analytics announced their Agile Analytics Lab has been recognized as the Best Big Data Analytics Platform by the 2020 Tech Ascension Awards. 

Fulcrum’s award-winning Agile Analytics Lab is a cloud-based, big data analytics platform supplemented with professional services that allows clients to experiment with software, data sources, and technology not available within their own organization. The Agile Analytics Lab is customized to each client, providing access to the tools and data sources specifically in demand for the organization’s developing data science needs.

The Tech Ascension Awards has recognized the very best innovations in b2c and b2b technology. In the second year of the Tech Ascension Awards, only the most cutting-edge companies stood above the rest. The Tech Ascension awards judged applicants based on technology innovation and uniqueness, market research (analyst reports, media coverage, customer case studies), hard performance stats, and competitive differentiators. The class-leading vendors that received recognition from the Tech Ascension Awards proved their technology solves critical industry challenges and produces invaluable business outcomes for their customers. 

“We are thrilled that our Agile Analytics Lab has been named Best Big Data Analytics Platform by The Tech Ascension Awards,” said Richard Vermillion, CEO of Fulcrum Analytics. “We are proud of the Lab’s role in making our clients’ data science teams more agile. Our Lab provides the technical environment they need to process massive datasets and experiment with cutting edge software and methodologies, without the barrier of having to make large scale investments.”

About Fulcrum Analytics
Fulcrum Analytics has stood at the forefront of data and analytics for over twenty-five years. Fulcrum offers sophisticated data science solutions, groundbreaking applications, and winning strategies that help companies achieve their targeted results. Fulcrum takes on the toughest data challenges to create meaningful business impact and move businesses forward every day. For more information about Fulcrum Analytics, please visit www.fulcrumanalytics.com

About the Tech Ascension Awards
The Tech Ascension Awards elevate companies that possess cutting-edge, innovative technology that solve critical challenges in their respective markets. Applicants are judged based on technology innovation and uniqueness, market research (analyst reports, media coverage, customer case studies), hard performance stats, and competitive differentiators. The awards recognize leaders in cybersecurity, DevOps, big data and consumer technology. For information about the Tech Ascension Awards, please visit www.techascensionawards.com.

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