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Tracking Nuclear Threats in Security Camera Networks (TNT-SCAN)

Award Information
Agency: Department of Homeland Security
Branch: N/A
Contract: 70RWMD19C00000001
Agency Tracking Number: FY18.1-H-SB018.1-010-0001-II
Amount: $1,009,985.78
Phase: Phase II
Program: SBIR
Solicitation Topic Code: H-SB018.1-010
Solicitation Number: FY18.1
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-08-12
Award End Date (Contract End Date): 2021-08-11
Small Business Information
625 Mount Auburn Street, Cambridge, MA, 02138-4555
DUNS: 115243701
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Camille Monnier
 (617) 491-3474
Business Contact
 Mark Felix
Phone: (617) 491-3474
Research Institution
Implementing continuous nuclear and radiological monitoring systems that support automatic detection and tracking of potential nuclear threats is traditionally associated with a high operational burden. Sensors are typically monitored by dedicated personnel, who must investigate detection events in a timely manner. High nuisance alarm rates can rapidly overwhelm already taxed law enforcement personnel, and ambiguities in a signal's origin limit the reliability of actionable information, particularly in a cluttered urban environment with many moving objects. Charles River Analytics and Passport Systems propose to develop a system for Tracking Nuclear Threats in Security Camera Networks (TNT-SCAN) that enables continuous, real-time monitoring of radiological sources in complex urban environments. The system augments an existing network of video cameras with a distributed network of commercial off-the-shelf (COTS) radiation detectors. A video processing subsystem detects and tracks objects in video streams provided by a third-party video management system (VMS) and passes track data to a radiation processing subsystem, which detects, localizes, and identifies threat sources. A graphical user interface provides security personnel with interactive threat reports that include historical track data, enabling efficient review, verification, and escalation of detection events. The proposed system builds on multiple recent advances in video analytics and radiation detection technologies, including a multi-modal approach to monitoring that has been demonstrated in complex, mixed-traffic environments. The envisioned end product represents a natural extension of existing product lines developed by our team, and is expected to appeal strongly to stakeholders of relevant security systems.

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

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