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Research Area 3: Fusion: Tools & Approaches Project 3.2: Fusion of Spatial-Temporal Sensor Data

Research Area 3: Fusion: Tools & Approaches Project 3.2: Fusion of Spatial-Temporal Sensor Data. Daniel Zeng Associate Professor & Honeywell Fellow Director, Intelligent Systems & Decisions Lab MIS Department University of Arizona December 11, 2008 NCBSI Tucson. Challenges.

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Research Area 3: Fusion: Tools & Approaches Project 3.2: Fusion of Spatial-Temporal Sensor Data

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  1. Research Area 3: Fusion: Tools & ApproachesProject 3.2: Fusion of Spatial-Temporal Sensor Data Daniel Zeng Associate Professor & Honeywell Fellow Director, Intelligent Systems & Decisions Lab MIS Department University of Arizona December 11, 2008 NCBSI Tucson

  2. Challenges

  3. Projects in Research Area 3

  4. Project 3.2: Fusion of Spatial-Temporal Sensor Data • Motivation • Analyzing sensor data with prominent spatial and temporal components and developing related predictive models are of great practical importance to • identify immediate concerns • provide clear situational awareness

  5. Project 3.2 Technical Objectives • Develop novel spatial-temporal data analytical techniques to identify and summarize patterns from dynamic and noisy data generated by sensor networks • Evaluate different formalisms and computational techniques for representing and reasoning about uncertainties in data of different granularity and modality

  6. Approaches for Spatial-Temporal Sensor Data Integration • Novel prospective spatial-temporal data clustering techniques • “Hotspot” identification • Markov switching for temporal change detection • SVC-based spatial-temporal change detection • Exploratory factors and dynamic changes • Theory-based spatial-temporal correlation measures and inference mechanisms • Integrating “evidence” from multiple data streams

  7. Major Types of Hotspot Analysis • Retrospective Models: Static Hotspot Analysis • Given a baseline (data points/events/cases on a map indicating the normal situation) and new cases of interest, a spatial “Before and After” comparison • Question: Where?? • Prospective Models: Dynamic Hotspot Analysis • Baseline unknown • Data feed continuously arriving • Question: When and Where??

  8. Spatial-Temporal Correlation Analysis • To formalize the intuitive notion of correlation • “persons residing in or near a dead crow cluster in the current or prior 1-2 weeks were 2-3 times more likely to become a WNV case than those not residing in or near such clusters” (Johnson et al. 04) • To identify significant correlations among multiple types of events with spatial and temporal components

  9. Representing & Reasoning about Data Uncertainty • Experimenting with a set of formal methods • Bayesian networks • Granular computing • Supporting a range of datasets to facilitate data fusion and integrated reasoning • Sensor-generated data • Existing records-based databases • Fusion architecture • Data fusion? Result fusion?

  10. Spatial-Temporal Visualizer (STV) • Providing synchronized, integrated views of spatial temporal data elements • GIS View • Periodic Pattern View • Timeline View • Hotspot analysis capabilities built-in • SOA Implementation

  11. Benefits to DHS • Providing a spatial-temporal data analysis and fusion framework for situational awareness and actionable intelligence • Providing noise-tolerant data representation and evidence-based fusion techniques for data with different resolutions and modalities • Enabling additional operational opportunities when the processed capabilities are in place

  12. Deliverables and Timelines 1Q: Data characterization and analysis contexts 2Q: Sensor data spatial-temporal clustering 3Q: Data uncertainty representation 4Q: Sensor data clustering with unified uncertainty representation Y2: Sensor data correlation analysis and fusion methods Y3: Sensor data uncertainty reasoning Y4-6: Sensor data granularity representation and reasoning; evidence-based integrated analytics; evaluation

  13. Linkage Among Area 3 Projects

  14. Linkage with Other BSI Projects

  15. Ongoing/Leveraged Research • NSF, “A National Center of Excellence for Infectious Disease Informatics”; “Transnational Public Health Informatics Research” • Multi-source syndromic surveillance, and early warning systems • CDC’s “BioPHusion” Project • Information fusion & public health situational awareness • “Smart Carts”– RFID applications in Retailing • Spatial-temporal pattern discovery & path clustering

  16. Thanks!

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