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Real-time Information Contextual Correlation and Analysis Software System

Award Information
Agency: Department of Homeland Security
Branch: N/A
Contract: HSHQDC17C00016
Agency Tracking Number: HSHQDC-16-R-00012-H-SB016.1-008-0010-II
Amount: $749,346.42
Phase: Phase II
Program: SBIR
Solicitation Topic Code: H-SB016.1-008
Solicitation Number: HSHQDC-16-R-00012
Timeline
Solicitation Year: 2016
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-03-31
Award End Date (Contract End Date): 2019-03-30
Small Business Information
Electro-Optics Systems Division 1845 West 205th Street
Torrance, CA 90501-1510
United States
DUNS: 153865951
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Wenjian Wang
 Principal Scientist
 (310) 320-3088
 EOSProposals@poc.com
Business Contact
 Gordon Drew
Title: Chief Financial Officer
Phone: (310) 320-3088
Email: gedrew@poc.com
Research Institution
N/A
Abstract

To address the DHS need for a new data analytics engine to correlate social media comments and activity with incident command data, Physical Optics Corporation (POC) proposes, in Phase II, to advance a new Real-time Information Contextual Correlation and Analysis (RICCA) software system proven feasible in Phase I. RICCA is based on unstructured data analysis and integration and event context modeling. Its advanced contextual analytics engine enables automated processing flow to retrieve social media data from multiple outlets (Facebook, Twitter, YouTube), extract environmental, social, meteorological, political, economic, and other factors relevant to an event of interest, correlate them in geo-space and time with data stored in a computer-aided-dispatch (CAD) system, and generate alerts for first responders and emergency/incident/crisis management. The innovation in unstructured data processing and integration and multi-resolution event context modeling can improve incident command's situational awareness and understanding. In Phase I, POC demonstrated the feasibility of RICCA by developing a set of operational scenarios, identifying the external factors in social media and operational incident data, developing core analytics modules, and implementing algorithms to measure performance and improvements. In Phase II, POC plans to mature the RICCA prototype and its correlation and analysis algorithms for the target scenario established in Phase I and support a pilot protocol by which a social media feed is correlated with operational incident data. Validation and trust algorithms will also be developed to support more timely and targeted response actions and allow for escalation preparedness.

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

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