Prepare for the Possibility: Response and Recovery Steve Goddard Computer Science & Engineering University of Nebraska-Lincoln.

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Presentation transcript:

Prepare for the Possibility: Response and Recovery Steve Goddard Computer Science & Engineering University of Nebraska-Lincoln

Outline Tool Suite Overview Tool Suite Overview Architecture and tool description Architecture and tool description Leveraging prior results Leveraging prior results Reduces cost and time to deliver Reduces cost and time to deliver Reduces schedule and technology risk Reduces schedule and technology risk Applying the Technology Suite Applying the Technology Suite Example Scenario Example Scenario Demonstration of GIS technology and related prototype tools Demonstration of GIS technology and related prototype tools Risk Communication Risk Communication Recovery Process Recovery Process

Distributed Architecture and Tools

Early Alert Tool

Incident Management Tool

Distribution and Tracking Tool

Simulation Engines The macro-level simulator provides simulations of the distribution of contaminated foods and support for the QTRIM model. The macro-level simulator provides simulations of the distribution of contaminated foods and support for the QTRIM model. The micro-level simulator modes food engineering/food processing operations. The micro-level simulator modes food engineering/food processing operations. Integrate industry standard simulators with models, where possible. Integrate industry standard simulators with models, where possible. E.g., SuperPro Designer E.g., SuperPro Designer Need to capture the engine but not necessarily the GUI Need to capture the engine but not necessarily the GUI

Leveraging Prior Results: National Agricultural Decision Support System HTTP IIOP RMI TCP Data cache Distributed Spatial and Relational Data e.g., Climatic Variables, Agricultural Statistics HTTP IIOP RMI TCP Presentation (User Interface) e.g., Web Interface, Java applet Knowledge Layer e.g., Exposure Analysis, Risk Assessment Data cache Knowledge Layer e.g., Data Mining, Exposure Analysis, Risk Assessment Data cache Distributed Spatial and Relational Data e.g., Climatic Variables, Agricultural Statistics Data cache e.g., Drought Indices, Regional Crop Losses Information Layer Data cache e.g., Drought Indices, Regional Crop Losses Information Layer

Leveraging Prior Results: National Agricultural Decision Support System

National Agricultural Decision Support System (NADSS) Tools The NADSS tools apply risk analysis methodologies to the study of drought and its impact on crops Integration of basic models with data generates “information” for analysis by decision makers Information can be gathered at any resolution for which we have data

Building a Risk Assessment By combining several domain specific factors from our “information layer” we are able to create maps displaying the risk of crop failure for states, regions or counties By combining several domain specific factors from our “information layer” we are able to create maps displaying the risk of crop failure for states, regions or counties An expert adjusts weight factors for each variable The risk calculator combines the variables The result is a “spatial” view of risk

Applying the Technology Suite Example Scenario Example Scenario Demonstration of GIS technology and related prototype tools Demonstration of GIS technology and related prototype tools

Here’s Jeff!! Jeff does his demo…. Jeff does his demo….

Risk Communication ?? ??

Here’s Mario!! Mario does his thing…. Mario does his thing….

Recovery ?? ??