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FACT: Fast and Accurate Detection of Counterfeit Microelectronics

Award Information
Agency: Department of Homeland Security
Branch: N/A
Contract: 70RSAT23C00000006
Agency Tracking Number: 22.1 DHS221-003-0037-II
Amount: $998,099.48
Phase: Phase II
Program: SBIR
Solicitation Topic Code: DHS221-003
Solicitation Number: 22.1
Solicitation Year: 2022
Award Year: 2023
Award Start Date (Proposal Award Date): 2023-05-22
Award End Date (Contract End Date): 2025-05-21
Small Business Information
5824 Westslope Dr.
Austin, TX 78731
United States
DUNS: 117474177
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Beau Bakken
 Principal Engineer
 (612) 655-4806
Business Contact
 Beau Bakken
Title: Principal Engineer
Phone: (612) 655-4806
Research Institution

As outsourced microelectronic manufacturing grows, the safety and security of U.S. consumers becomes increasingly threatened by potential counterfeit electronics. Current counterfeit inspection techniques are labor intensive, time consuming, and impractical to use by field agents located on remote sites, away from major facilities, and with limited expertise. The proposed work, Fast and Accurate Detection of Counterfeit Microelectronics (FACT) by Caspia Technologies will develop a system that utilizes a handheld device capable of rapidly and non-invasively detecting counterfeit microelectronics using visual imagery to be used by Customs and Border Protection (CBP) agents located at U.S. Ports of Entry (POEs). The handheld device, (such as a cell phone or handheld camera), is connected to a cloud-based data processing platform hosting artificial intelligence and machine learning algorithms for automated counterfeit analysis. This real-time system architecture is quick and easy-to-use for operators with no imaging nor testing expertise. In Phase I, Caspia successfully demonstrated the feasibility of machine/deep learning algorithms to evaluate microelectronic imagery for key physical anomalies on a cloud-based platform accessible from a handheld device. In Phase II, Caspia will demonstrate the prototype FACT solution in a POE test environment with the proposed handheld device and enhanced machine learning algorithms hosted on the cloud. A roadmap that takes the program through Phase III will be part of the Phase II delivery. The proposed activities will progress commercialization goals of offering a cost-effective, accurate, non-invasive, real-time counterfeit detection system for market areas where safety and security are trusted within electronics.

* Information listed above is at the time of submission. *

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