The Department of Homeland Security has awarded funding worth $1 million each to Alakai Defense Systems and Physical Sciences Inc. to further develop their machine learning platforms to help improve the detection of explosives, narcotics, chemical agents and other threats as part of the second phase of the Small Business Innovation Research program.
“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,” Thoi Nguyen, program manager for the Next Generation Explosive Trace Detection program at DHS’ science and technology directorate, said in a statement published Friday.
Alakai will continue to develop its Agnostic Machine Learning Platform for Spectroscopy designed to detect hazardous chemicals from spectroscopic instruments as part of the two-year SBIR Phase II contract.
PSI will use the SBIR funding to continue to work on its deep learning algorithm meant to detect and classify opioids, narcotics and trace explosives for optical spectroscopic platforms.
DHS said it expects the awardees to come up with a prototype for demonstration and evaluation for Phase III funding. Under the third phase, the companies will seek private funding to bring their technologies to market.