DATANOVA SCIENTIFIC LLC — Department of Homeland Security SBIR Phase I: H-SB016.1-007

Description

We propose Real-time Intelligent Determination of Resilience (RIDER), a cognitive cloud product that consumes real-time data to generate a predictive and proactive risk and resilience posture with site-specific granularity. RIDER utilizes existing FEMA resources in a novel and innovative way for site-specific predictive and proactive risk generation. This statistical risk will be combined with prioritized open data sources (like Twitter) to generate an accurate and current resilience assessment. RIDER will utilize cognitive computing to exploit the open data sources and the FEMA data. The various datasets will be fused together using a deductive semantic model. The RIDER product will produce various visualizations such as heat maps to assess overall resilience of a community. It will also be able to zoom into a specific site or infrastructural component, and be able to provide a detailed logical proof of what affected that site's resilience; this feature is important for the end user to obtain insight from the system. RIDER will also be able to ascertain the conditions under which the risk is acceptable or unacceptable for a given site. The proposed solution addresses the urgent need for resilience assessment in various markets like local governments, the DoD, and commercial insurance companies. Local governments can use RIDER to assess their community's resilience. The DoD is interested in protecting its mission critical infrastructure in various global force deployments. Flood insurance in coastal communities can be optimized greatly using the site-specific, granular, and real time operation of RIDER.