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Ares Security Corporation SBIR Phase II Award, March 2022

A SBIR Phase II contract was awarded to Ares Security Corporation in March, 2022 for $725,000.0 USD from the U.S. Department of Defense and United States Air Force.

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Contents

sbir.gov/node/2239289
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Ares Security Corporation
Ares Security Corporation
0
Government Agency
U.S. Department of Defense
U.S. Department of Defense
0
Government Branch
United States Air Force
United States Air Force
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Award Type
SBIR0
Contract Number (US Government)
FA8649-22-P-07230
Award Phase
Phase II0
Award Amount (USD)
725,0000
Date Awarded
March 9, 2022
0
End Date
March 10, 2023
0
Abstract

ARES Security Corporation has teamed with Motorola Solutions and Bevilacqua Research Company to research advanced solutions for the BDOC automated decision support. The over-arching objective for the incident response actions initiated by a BDOC operator is to be highly effective in preventing and mitigating the impact of security incidents. In the BDOC, systems, information, communications, and procedures must seamlessly work together to support incident response when seconds matter. To that end, this proposal is focused on the following R/R&D objectives: Integration of commercial technology in novel ways to provide automated decision support. Explore ways to leverage knowledge gained from thousands of vulnerability assessments in an AI engine providing real time automated decision support. Evaluation of how BDOC operator cognitive overload can be reduced through AI enabled intuitive GUI/COP, dynamic QRCs, and integrated incident response. Research the application of real time and predictive video analytics in providing automated decision support. Determine methods that will allow the USAF to move beyond traditional stand-alone video management systems and retrospective forensics video search capabilities.    Understand the issues associated with evolving and sometime inaccurate incident information when providing dynamic updates to QRCs. During Phase I, we demonstrated the feasibility of using intelligent video object detection and AI to provide BDOC operators automated decision support for intercepting a gate runner. In Phase II we will extend this work into a prototype that can be put in the hands of the BDOC operator for evaluation. The technical solution is robust and includes the challenges of integrating video capture, video analytics, edge detection, simulation of thousands of threat scenarios, knowledge graphs that capture response CONOPS, real time AI driven decision support, situational awareness, a common operational picture, dynamic QRCs, and a fully operational BDOC C2 solution.  

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