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© 2012 IBM Corporation Next Generation Intelligent Cyber-Physical System for Integrated Environment Monitoring and Management ASFPM 2012
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© 2012 IBM Corporation 2 Decision, Information and Knowledge We make decisions everyday. Decisions have consequences – Cereal or waffle for breakfast – Take IH-35 or IH-410 – Buy a house on the lake front or on the hills – Close this low water crossing or not, time of closure – Build this levee or not, height of the levee Knowledge + Information -> Decision Information is often embedded in the data – Data could be “noisy” The information age is represented by our increasing capability of collecting data, distilling information, so as to assist decision making
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© 2012 IBM Corporation 3 Empowerment of Information Amazon.com: $48 billion revenue in 2011. Sell almost everything on earth Compared to traditional brick-and-mortar retailers on consumer electronics – Model selections, price, reviews, … Amazon is one of the biggest IT companies in the world. Estimated half million servers in data centers around the world
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© 2012 IBM Corporation 4 Data Could Come from Unexpected Sources The next WorldView satellite has the resolution of 31cm (currently 46cm) Capable of revisiting same place on earth in about 1.1 days Constellation enables revisit of any location within 1 day
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© 2012 IBM Corporation 5 Smarter Planet Instrumented – Data collection Interconnected – Data in motion Intelligent – Extract insight from data, effective data dissemination InstrumentedInterconnectedIntelligentSmarter
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© 2012 IBM Corporation 6 Instrumented: REON InstrumentedInterconnectedIntelligentSmarter
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© 2012 IBM Corporation 7 River and Estuary Observatory Network (REON)
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© 2012 IBM Corporation 8 Instrumented: Smart Levee InstrumentedInterconnectedIntelligentSmarter
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© 2012 IBM Corporation 9 Levee Experiment in 2008: 15+ sensor systems tested Collapse Sat. 14:02 Orientation sensor on Friday http://www.youtube.com/watch?v=lwBrJi9ly5c
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© 2012 IBM Corporation 10 Levee Experiment 2009 + Live Operational Levee Operational levee Experimental levee Infrared cam detects water saturation http://www.youtube.com/watch?v=pTnXscZ9MEE http://www.youtube.com/watch?v=KbNpVip8aaI
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© 2012 IBM Corporation 11 Deep Analytics to Understand Data for Better Forecasting IBM Research & SPSS statistical modeling, outlier detection and forecasting IBM High Performance Computing accelarating wave impact forecasting model Partners for domain knowledge; hydrological and levee stability forecasting (e.g. DHV, Deltares)
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© 2012 IBM Corporation 12 Interconnected: IBM InfoSphere Streams InstrumentedInterconnectedIntelligentSmarter
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© 2012 IBM Corporation 13 IBM InfoSphere Streams Large volume of data must be processed at high speed Avoids storing-retrieval-processing paradigm Data are constantly in motion Flexible and ease in reconfiguration to enable real time decision making
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© 2012 IBM Corporation 14 Highlights of Streams Complete software environment for stream data processing Consume all types of streaming digital data with a flexible programming model and powerful programming environment Complemented by IBM Research stream analytics research Blue Gene Node Blue Gene Node Blue Gene Node x86 blade X86 bladex86 Blade TCP-IP / Ethernet Transport Streams Data Fabric Processing Element Container PE Sink Source PE Sink PE Sink
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© 2012 IBM Corporation 15 Streams Example: Trend Calculation
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© 2012 IBM Corporation 16 Intelligent: Models InstrumentedInterconnectedIntelligentSmarter
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© 2012 IBM Corporation 17 Benefit of a Good Model A (mathematical) model is a compact and rigorous form on our knowledge and understanding regarding a subject A model can help us to “connect the dots” (spatially) and “look into the future” (temporally) – Flooding at one location v.s. the other location – Future forecast based on current and past observations Classic models in hydrology and hydraulics Good Models require investment – Flexibility of deployment – Ride on the wave of Moore’s law
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© 2012 IBM Corporation 18 SPRINT: Simulation Program for RIver NeTworks Collaboration between IBM Research and University of Texas Austin Center of Research in Water Resources Objective: – Address the computational bottle network of large scale river basin simulation (regional or continental scale) Highlights: – Extend the modeling capability from main stems to upstream tributaries – Use the latest computer science techniques and computer hardware to achieve over 100x of real-time when simulating large river basin
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© 2012 IBM Corporation 19 SPRINT: Demo Guadalupe-San Antonio River basin simulation Statistics: – Over 3,500 reaches – 15,000 km total length – Modeled by 110K nodes Capable of simulating a 10-day event on a desktop at the speed of over 100× of real time Why we need faster model simulation – Model calibration
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© 2012 IBM Corporation 20 Calibration Challenge
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© 2012 IBM Corporation 21 Calibration Challenge
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© 2012 IBM Corporation 22 Intelligent: Intelligent Operations Center InstrumentedInterconnectedIntelligentSmarter
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© 2012 IBM Corporation 23 IBM Intelligent Operations Center for Smart Cities provides integrated insight… Smarter Operations – across departments and agencies Leverage information with real-time visibility of key data to drive better decisions Anticipate performance to identify, manage and mitigate incidents that impact operations Coordinate resources and processes to respond to situations rapidly and effectively …within a particular service area or managing across many services
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© 2012 IBM Corporation 24 Emergency Management provides a central point to capture events and provide responders with operational insight InfrastructureHuman Planning and Management “In Rio de Janeiro, we are applying technology to benefit the population and effectively transitioning to a smarter city” Mayor of Rio de Janeiro Eduardo Paes Automated alerts notify emergency personnel when changes occur in the flood and landslide forecast Smarter Emergency Management Leverage accurate information to create near real-time situational awareness at the command center level Anticipate and proactively plan to improve strategic collaboration and tactical decision making Coordinate responder resources to enable a faster, more effective and efficient response
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© 2012 IBM Corporation 25 On Premise: Build on workload optimized platforms Leverage infrastructure readiness services Shared Services: Work together across multiple cities Share services using preconfigured systems Cloud Delivery: Log on to your smarter city environment Customize interfaces, reports and data inputs Multiple deployment choices that offer flexibility and agility “It’s about transforming the way we do business, so we can invest that money in front-line service delivery” Chief Superintendent Avon & Somerset Police Inspired By
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© 2012 IBM Corporation 26 Final Remarks We need information to make sensible decisions. Information is often embedded in the data IBM Research has long tradition as the premier research institution on information technology We are actively working with partners on many aspects of data collection, data processing, and modeling – To provide more meaningful information in a timely manner to the decision makers InstrumentedInterconnectedIntelligentSmarter
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