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Download Data Dissemination for Environment Monitoring Visalakshmi Suresh Prof. Paul Watson
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Data Dissemination for Environment Monitoring Visalakshmi Suresh Prof. Paul Watson MESSAGE • EPSRC funded research. • Consortium • Newcastle University, Leeds University, Imperial College, Cambridge and Southampton University • Advisory Board : Collaboration with Industry Overview ¾ Novel and Emerging ITS sensing devices ¾ Data acquisition and Processing ¾ Real Time Data Fusion Architecture ¾ Real Time Data Dissemination ¾ Historic Data Mining using Collaborative Tools ¾ Conclusion Novel and Emerging ITS sensing devices Pervasive Sensors ¾ ¾ ¾ ¾ ¾ Highly modular, mobile/fixed CO, NO2, Noise and Traffic Temperature and Humidity Accelerometer and GPS Mobile and Fixed ¾ ¾ ¾ ¾ ¾ ¾ Battery 6months @1min average ~£200 components cost Motes ~100m apart Zigbee wireless 5 hops Gateway: Indoor/outdoor. LAN or autonomous (GPRS) Novel and Emerging ITS sensing devices Legacy Systems A Technology •Vehicles •People •Systems MESSAGE Decision Support System Network Status Modelling Historic Analysis Real-time Analysis Evaluation and Assessment Disseminate/inform STRATEGY POLICY Data Acquisition Real Time Mashups Locations Real Time Monitoring Data Aggregation Pollution Hotspots AURN -- Legacy System Demonstration Real Time Dissemination Real Time and Historic Integration OSPM Dispersion Model Technology Traffic and air quality Model Validation A Traffic and air quality Model Validation A Current Research • Integrating Models with Monitored data (Image Source: TORG, Newcastle University) Data Display Marts ¾ V: Visualisation ¾ RTEP: Real-Time Event Processor ¾ CCLAV: Critical Congested Link Assessment ¾ CA: Congestion Assessments ¾ TTEE: Traffic Tail-pipe Emissions Estimation ¾ RPPL: Receptor Point Pollution Level Collaborative Workbench Historic Data analysis eScience Central • • • • Store Analyse Automate Share System Architecture Layered Approach D issem ination WWW A pplications Live Pollution M onitoring Live C ongestion M onitoring Pollution H otspots Live D ispersion H istoric D ata M ining Services D ata Service IaaS Softw are Services R esources Layer Softw are D atabase Servers D ataw arehouse eScience central O SPM .. G rid C om m unication Layer Pervasive Sensors SC O O T AURN M ET Vehicles M odels Summary • Designed for data intensive applications • Features for continuous evolution • Integration of heterogeneous data sources • Effective control and added values to ITS implementation Questions? Visalakshmi Suresh [email protected] Prof. Paul Watson [email protected]
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