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Real-time Flood Forecasting and Reporting

Award Information
Agency: Department of Homeland Security
Branch: N/A
Contract: HSHQDC-17-C-00020
Agency Tracking Number: HSHQDC-16-R-00012-H-SB016.1-005-0018-II
Amount: $749,998.80
Phase: Phase II
Program: SBIR
Solicitation Topic Code: H-SB016.1-005
Solicitation Number: HSHQDC-16-R-00012
Solicitation Year: 2016
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-03-20
Award End Date (Contract End Date): 2019-03-19
Small Business Information
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
 Chris Ulmer
 Director, Engineering
 (310) 320-3088
Business Contact
 Gordon Drew
Title: Chief Financial Officer
Phone: (310) 320-3088
Research Institution

To address the DHS need to rapidly predict, detect, and react to ever-changing flood conditions, Physical Optics Corporation (POC) proposes to develop a new Real-time Flood Forecasting and Reporting (RAFFAR) system based on a combination of commercial off-the-shelf (COTS) wireless networking technologies and existing proprietary POC sensors. The system will offer a means to deploy a scalable mesh network across a broad area that allows sensors to relay information through open data exchange standards to an operation center for monitoring of both flood conditions and heavy rain conditions that serve as predictors of floods. After collection, the information will be relayed to handheld devices through wireless emergency alerting. In Phase I, POC demonstrated the feasibility of RAFFAR by building and testing a preliminary prototype network and performing an analysis of a full-size network roll-out. At the end of the Phase I effort, the RAFFAR system reached TRL-6. In Phase II, POC plans to manufacture sufficient sensors to deploy a 100+ unit network for extensive outdoor testing. The successful completion of this project at the end of Phase III will benefit the nation in both government and commercial sectors by providing real-time disaster data so that first responders can react appropriately based on the best possible information. Commercial applications for this technology include applications in disaster prevention and recovery, manufacturing and equipment monitoring, and irrigation management.

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

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