Odysseus™ Network:

ISC Deploys Recovery Experts for Hurricane Irma

Hurricane Irma hit the Florida Keys as a Category 4 storm and a second landfall on Marco Island as a Category 3.  Irma caused billions of damage throughout Florida and Georgia.  In response, ISC mobilized its disaster recovery experts to support communities in assessing the damages to vital infrastructure and government assets and provide technical assistance in the delivery of Federal disaster assistance programs, to include FEMA Public Assistance.  ISC is proud to be able to help those communities in need.

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ISC Mobilizes for Hurricane Harvey Recovery

In August 2017, Hurricane Harvey devastated the State of Texas becoming the costliest hurricane to date with an estimated $200 billion in damages.  ISC’s disaster recovery experts have mobilized to Texas to support local communities, utilities, and other vital critical infrastructure sector assets across eastern Texas and the greater Houston area.  ISC provide will provide technical assistance in assessing damages and  the delivery of Federal disaster assistance programs, to include FEMA Public Assistance.  ISC is proud to be able to help those communities in need.

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ISC Mitigates Ohio

ISC was selected by the Franklin County Emergency Management Agency to provide technical consulting services for the update of the county’s hazard mitigation plan.  The county will be utilizing ISC’s Odysseus system to enhance the current plan and assist with future updates.  Franklin will also be utilizing ISC’s UAV drone services to to analyze hazard risks and assess hazard mitigation alternatives.

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ISC Conducts Community Preparedness Survey for San Diego

In preparation for the 10 year anniversary of the Witch Creek, Harris, and Guejito Wildfires that occurred in October 2007, ISC was selected by San Diego Office of Emergency Services to conduct a survey of county residents to determine how well County residents are prepared for a disaster or emergency. The survey will utilize scientific research methods to obtain a 95% confidence level with a margin of error of 3%.

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