Predictive Interactive Visual Analytics for CCI: Planning, Response, and Resiliency
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- Marianna Robinson
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1 Predictive Interactive Visual Analytics for CCI: Planning, Response, and Resiliency SFU, JIBC UBC UW Purdue Penn St. Stanford Ind U VaTech NC UNCC A&T Navajo Tech UT Austin UHD JSU GaTech FIU U Stuttgart Swansea U
2 VACCINE Mission Provide visual analytic and scalable solutions for all 2.3 million extended homeland security personnel 185,000 DHS personnel, 350,000 law enforcement personnel, 750,000 homeland security practitioners, 2.3 million extended personnel Achieve excellence in visual analytics and visualization sciences Educate homeland security stakeholders and the next generation of talent
3 Research Approach and Plan Evolving, effective, and enduring research by tight integration with stakeholders Driven by our stakeholders all 2.3 million extended public and private homeland security professionals Visual Analytics Interactive visual/cognitive analytic environments based on novel research in visual analytics, Full-scale exercise February 2008 algorithms, information transformation, cognitive and interaction science, creating precise information environments
4 Some VACCINE Regional and Corporate Partners Indiana Department of Homeland Security Indiana State Department of Health Indianapolis Public Safety Charlotte Mecklenburg Police Department Lafayette, West Lafayette, Purdue Police Departments Tippecanoe County EMA & Sherriff s Department Harrisburg, PA Police Coast Guard Sector Boston, Seattle, LA Joint Harbor Operations Command Center Port of Seattle Indianapolis Public Safety USCG District 9 Motorola Harris Corporation Boeing Next Wave Systems, LLC Banfield, The Pet Hospital Raytheon MacDonald, Dettwiler and Associates Oculus Info Inc. Kx Systems Bank of America Duke Energy World Vision International Gates Foundation Kimberly Clark Hallmark March 2011
5 VACCINE Government Partners U.S. Coast Guard Federal Emergency Management Agency Customs and Border Patrol National Geospatial Intelligence Agency National Science Foundation Army Research Office Department of Defense Department of Health and Human Services U.S. Dept. of State National Institute of Justice National Maritime Intelligence Center Defence Research & Development Canada Foreign Broadcast Information Service US-CERT Oak Ridge National Laboratories US Army Corps of Engineers- ERDC Pacific Northwest National Laboratory ARL CERDEC & ARDEC US Attorney s Office (David Capp)
6 What We Do Enable effective decision making through interactive visual analytic environments Enable effective communication of information Provide quantitative, reliable, reproducible evidence Enable user to be more effective from planning to detection to response to recovery Enable proactive and predictive visual analytics
7 Example of Visual Analytics for Strategic Planning, Risk Management, and Recovery Trend analysis, clustering, anomaly detection Interactive, multi-day, month, day, type investigation Purpose: Planning for resiliency Long-term analysis Predictive analytics Training Detection and investigation Response Recovery, remediation
8 Example: USCG D9 Search And Rescue Operational Analysis Interactive visual analytics of multivariate performance metrics for each unit s activities Interactive linked spatial temporal display, calendar view, and timeline views
9 System Overview Calendar View Time Series View Distress Menu Time Slider
10 System Features: SAR Risk Profile Time taken by CG stations to deploy an asset to the Great Lakes to respond to a SAR incident.
11 Risk Assessment Scenario Station B Parent Station A Station X
12 Risk Assessment Scenario contd. March 2011
13 Risk Assessment Scenario contd. Close AUXOP Station X Set asset speed
14 Risk Assessment Scenario contd. Median time = 92 min. 4 cases take >120 min.
15 Risk Assessment Scenario contd. Median time = 110 min.! 16 cases take >120 min. 4 cases take >120 min. If only parent station absorbs station X s cases
16 Risk Assessment Scenario contd. Average response time risk profile when station X is operational
17 Risk Assessment Scenario contd. Hotspot emerges in the area of operation of Station X Average response time risk profile when station X is closed
18 Visual Analytics Uses for Public Safety Trend analysis, clustering, anomaly detection Interactive, multi-day, month, day, type investigation Purpose: Planning for resiliency Long-term analysis Predictive analytics Training Detection Investigation Response Recovery, remediation
19 VACCINE Public Safety Consortium Tippecanoe County Emergency Management Agency Indianapolis Metropolitan Police Department Tippecanoe County Sheriff s Department Purdue Police Department Pending Ohio State U. Police, U. Nebraska Police VACCINE R&D DHS S&T Indianapolis Department of Homeland Security Lafayette Fire Department Transition Lafayette Police Department Indianapolis Fire Department West Lafayette Police Department
20 Technologies in the Transition Cycle VALET - Visual Analytics Law Enforcement Toolkit Deployed for Test & Evaluation Feedback Lafayette PD, W. Lafayette PD, Purdue PD, Tippecanoe County Sheriff GARI - Gang Graffiti Automatic Recognition and Interpretation Initial Prototype Deployment Scheduled May 2011 Indianapolis Gang Task Force, Lafayette PD, Purdue PD CGSaRVA - Coast Guard Search and Rescue Visual Analytics Deployed for Operational Use USCG LANT MERGE - Mobile Emergency Response Guide Initial Prototype Deployment Scheduled May 2011 Indianapolis Fire, Lafayette Fire Ulearning (Captico)- Training portal for S&T and COE Technologies Deployed for Test & Evaluation Feedback - March 2011
21 Technologies in the Transition Cycle JigSaw VA for Exploring and Understanding Document Collections (Georgia Tech) Deployed for Test & Evaluation Feedback Dec Indianapolis PD, PROTECT - Port Resilience Operational / Tactical Enforcement to Combat Terrorism Collaboration with CREATE Prototype July 26, 2011 COE Explorer Exploring the Centers of Excellence (Purdue, SFU) Collaboration with CCICADA CrimeViz - Sensemaking about criminal activity in space and time (Penn St) Testing in progress with Harrisburg PD Prototype deployment planned for Q Harrisburg PD, JIBC ISIS - Infovis System for Investigating Intrusions (Stanford) Awaiting deployment to US CERT
22 Some Visual Analytic Examples Integrated predictive models and decision making Spatiotemporal visual analytics Predictive visual analytics Public health and pandemics Realtime plume decision support Mobile apps
23 Example Decision Analysis Linked Displays Example with 3 Decisions Partnership with FAZD Differences from each decision Interactive exploration and combination of decisions
24 Scalable Visual Analytics for Law Enforcement VALET Toolkit Linked statistical and spatial visualization for analysis Scalable from desktops to mobile devices for off-field and in-field investigation Compare datasets for potential correlations Datasets: West Lafayette crime, traffic Tippecanoe County arrests, incidents Desktop VALET Partners: WLPD, LPD, TCSD Team: Purdue, UNCC, Rutgers, PSU March 2011 Mobile VALET
25 Visual Analytics Law Enforcement Toolkit (VALET)- Tippecanoe County Example Linked Predictive Crime Models by Type Day vs. Night Thefts 2008 (red) vs (blue background) Aggravated Theft
26 We Have an App For That! March 2011 Our Mobile Tools VALET Evacuation Planning Rosetta Phone Hazmat app Gang graffiti app Tatoo app
27 For Further Information
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