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Smarter Cities Research in Ireland 20120113
1.
IBM Research and
Development - Ireland Smarter Cities Research Lisa Amini, PhD Distinguished Engineer and Director IBM Research and Development – Ireland © 2010 IBM Corporation © 2011 IBM Corporation
2.
IBM Research and
Development - Ireland A legacy of World-Class Research 1944: 1948: 1956: 1957: 1964: 1966: 1967: 1970: 1971: Mark 1 SSEC RAMAC FORTRAN System/360 One-Device Fractals Relational Database Speech Recognition Memory Cell Nobel Prizes: 1973: 1979: 1980: 1986: 1987: 1990: 1994: 1993: RS/6000 SP Winchester Disk Thin Film RISC Scanning Tunneling High Temperature Chemically SIGe 1996,97: Deep Blue Recording Microscope Superconductivity Amplified Photoresists Heads 1997: 1998: 1998: 2004: 2006: 2008: Copper Silicon-on-Insulator Microdrive 2002: Blue Gene 5-stage Carbon Nanotube World’s First Petaflop Supercomputer Interconnect Millipede The fastest Ring Oscillator Wiring supercomputer in the world © 2011 IBM Corporation
3.
IBM Research and
Development - Ireland IBM Research: 3 New Labs Established in 2010 ! Smarter Cities ! Risk Analysis ! Exascale and Hybrid Computing Dublin China Zurich Almaden Watson Haifa Tokyo Austin India Brazil ! Natural Resources ! Smarter Devices Melbourne ! Human Systems/Events ! Natural Resources ! Disaster management ! Healthcare/Life Sciences IBM Research Labs 1998 - 2007 IBM Research – New Presence Since 2010 © 2011 IBM Corporation
4.
IBM Research and
Development - Ireland Smarter Cities Technology Centre ! !"#"$%&'($)*(+","-./0")1( – !"#$%&'"()*+,-.-/+01-+2)")$23()2"/+014+567+58&9:8;"+*)<)&8=)2"++ – >$2?)#+.4-+%@+A!+,-.,+BC!5+D+567+58&9:8;"E+ ! 23/"%4#"( – F$#$+G';';?/+G$3(';)+&)$2;';?/+H=:I'J$:8;/+K;#)&&'?);#+L8;#28&/+ 7)8"=$:$&+M;$&@"'"+$;*+N'"9$&'J$:8;/+C)$&O:I)+"@"#)I"+$;*+$;$&@:3"/+ K;P82I$:8;+$;*+Q;8R&)*?)+G$;$?)I);#/+5)I$;:3+6)%/+C)$"8;';?+ – >2$;"=82#$:8;+53');3)/+6$#)2+G$;$?)I);#/+S8R)2+5@"#)I"+ https://researcher.ibm.com/researcher/view_researchers.php © 2011 IBM Corporation
5.
IBM Research and
Development - Ireland How can we help cities transform ? 1. Sensor data assimilation! – Data diversity, heterogeneity – Data accuracy, sparsity – Data volume! ! 2. Modelling human demand! – Understand how people use the city infrastructure! – Infer demand patterns! 3. Operations & Planning! – Factor in uncertainty! – Organise and open data and knowledge, to engage citizens, empower universities and enable business! © 2011 IBM Corporation
6.
IBM Research and
Development - Ireland Outline Sensor data assimilation • Continuous assimilation of real-time traffic data Transportation Understanding/Modeling human demand • Characterizing urban dynamics from digital traces Operations & Planning Water • Leveraging mathematical programming for planning in an uncertain world Operations & Planning Multi-domain • Organising data and information to better engage citizens, empower universities and enable businesses to help drive overall growth © 2011 IBM Corporation
7.
IBM Research and
Development - Ireland Continuous assimilation of real-time traffic data Eric Bouillet, PhD Research Staff Member, Analytics & Optimization Smarter Cities Technology Centre IBM Research and Development - Ireland © 2010 IBM Corporation © 2011 IBM Corporation
8.
IBM Research and
Development - Ireland Noisy GPS Data • To become useful, GPS data has to be related to the underlying infrastructure (e.g., road or rail network) by means of map matching algorithms, which are often computationally expensive • In addition, GPS data is sampled at irregular possibly large time intervals, which requires advanced analytics to reconstruct with high probability GPS trajectories • Finally, GPS data is not accurate and often needs to be cleaned to remove erroneous observations. © 2011 IBM Corporation
9.
IBM Research and
Development - Ireland Real-Time Geomapping and Speed Estimation GPS probe Matching map artifact Estimated path Estimated speed & heading © 2011 IBM Corporation
10.
IBM Research and
Development - Ireland Our Dublin Experience (2011) • Complex system & analytics challenges Parkin g • Data diversity, heterogeneity capacit y • Data accuracy, sparsity Timetabl C 700 intersections ar • Data volume 4,000 loop detectors es 20,000 tuples / min Routes & SCATS maps Induction loop 1,000 buses Accessibi 3,000 GPS / min lity Bus AVL (GPS) CC TV 200 CCTV cameras • Active relationship with DCC • Deployed in Dublin’s DoT Bik e © 2011 IBM Corporation
11.
IBM Research and
Development - Ireland Actuating the city • Real-time, proactive traffic control! • Traffic control recommender! • Recommend actions under uncertainty! • Dynamic traffic light actuation strategy • Traffic Management Towards a Low Carbon Society! • Traffic (congestion) is a significant contributor to CO2 emissions! • We are building a method, system and tools for adaptively influencing traffic in real-time to reduce carbon dioxide CO2- and black carbon (BC) emissions caused by road transport in urban and inter-urban areas.! Journey Pattern 046A0001; Bus Stop 6059; from 7h to 23h. weekdays Journey Pattern 046A0001; Bus Stop 2017; from 7h to 23h. weekdays 0.2 0.12 0.15 0.1 0.1 0.08 0.06 0.05 • Pilot cities include Glasgow, UK and Graz, Austria! 0.04 0 0.02 5 0 5 10 10 1 15 15 1 0 1 20 10 20 30 20 20 30 0 1 : 0 Hour of the Day 25 −20 −10 0 • FP7 EU-funded project starting September 2011! 10 −30 25 −20 −10 0 : 0 4 : Delay in Minutes Hour of the Day 3 : Best suggested route −30 Delay in Minutes 0 5 0 3 0 continuously updated 5 based on changes in arrival departure times • Interactive, dynamic personal journey advisor! of buses and current position of subscriber • Addresses complex, dynamic, multimodal transit network! 1 1 1 : 1 2 : 0 1 2 © 2011 IBM Corporation
12.
IBM Research and
Development - Ireland Our Dublin Experience (2011) • Complex system & analytics challenges Parkin g • Data diversity, heterogeneity capacit y • Data accuracy, sparsity Timetabl C 700 intersections ar • Data volume 4,000 loop detectors es 20,000 tuples / min Routes & SCATS maps Induction loop 1,000 buses Accessibi 3,000 GPS / min lity Bus AVL (GPS) CC TV 200 CCTV cameras • Active relationship with DCC • Deployed in Dublin’s DoT Bik e © 2011 IBM Corporation
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IBM Research and
Development - Ireland Outline Sensor data assimilation • Continuous assimilation of real-time traffic data Transportation Understanding/Modeling human demand • Characterizing urban dynamics from digital traces Operations & Planning Water • Leveraging mathematical programming for planning in an uncertain world Operations & Planning Multi-domain • Organising data and information to better engage citizens, empower universities and enable businesses to help drive overall growth © 2011 IBM Corporation
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IBM Research and
Development - Ireland Understanding urban dynamics from digital traces Francesco Calabrese, PhD Research Staff Member, Analytics & Optimization Smarter Cities Technology Centre IBM Research and Development - Ireland © 2010 IBM Corporation © 2011 IBM Corporation
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IBM Research and
Development - Ireland Pervasive Technologies Datasets as Digital Footprints Understand how people use the city's infrastructure! ! Mobility (transportation mode) ! ! Consumption (energy, water, waste)! ! Environmental impact (noise, pollution)! ! Potentials! ! Improve city’s services! ! Optimize planning! ! Minimizing operational costs! ! Create feedback loops with citizens to reduce energy consumption and environmental impact! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Understanding Urban Dynamics • Research goals • Understanding human behavior in terms of mobility demand • Analyzing and predicting transportation needs in short & long terms • Outcome • Design adaptive urban transportation systems • Support urban planning and design • Examples of projects • How geography influences the way people interact • How travel demand changes over space and time • How social events impact mobility in the city © 2011 IBM Corporation
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IBM Research and
Development - Ireland Mobile phones to detect human mobility and interactions Angle of Arrival (AOA) Timing Advance (TA) The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may Example of extracted trajectory over 1 week Received Signal Strength (RSS) !F. Calabrese, M. Colonna, P. Lovisolo, D. Parata, C. Ratti, Real-Time Urban Monitoring Using Cell Phones: a Case Study in Rome, IEEE Transactions on Intelligent Transportation Systems, 2011.! ! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Regional partitioning based on level of interaction Findings • Spatial cohesiveness of regions ! State boundaries emerge in most of the cases ! Metropolitan areas (e.g. NYC, LA) define new regions ! Some states merge as level of interaction is higher than expected Applications ! Help regional and city provides to better plan or adjust their operations ! Adjust service catchment areas (e.g. hospital serviced neighbors) ! Plan new transit systems to help connecting areas with low interaction The Connected States of America. Can data help us think beyond state lines?, Time Magazine, 11 April 2011! © 2011 IBM Corporation
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IBM Research and
Development - Ireland How travel demand changes over space and time Origin Destination matrices are used for transport planning! ! ! Estimated from census data or travel surveys! • Very costly, so rarely done in developing countries, and quickly outdated ! • Only commuting! ! ! Developed a new method making use of mobile phone location data to estimate ODs! • All travels (not only commuting)! • Real time monitoring! !F. Calabrese, G. Di Lorenzo, L. Liu, C. Ratti, “Estimating Origin-Destination flows using opportunistically collected mobile phone location data from one million users in Boston Metropolitan Area”, IEEE Pervasive Computing, 2011.! ! ! © 2011 IBM Corporation
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IBM Research and
Development - Ireland How social events impact mobility in the city Modeling and predicting non-routine additive origin-destination flows in the city ! ! Estimated home location! Event duration! User stop! Overlap time > 70%! Time! Attendance Inference! !F. Calabrese, F. Pereira, G. Di Lorenzo, L. Liu, C. Ratti, “The geography of taste: analyzing cell-phone mobility and social events”, In International Conference on Pervasive Computing, 2010.! ! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Detecting and predicting travel demand Applications! • Improving event planning & management! • Predicting the effect of an event on the urban transportation! • Adapting public transit (schedules and routes) to accommodate additional demand! • Location based services! • Recommending social events! • Cold start problem! ! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Summary • In order to make city’s services more efficient we need to understand how people use the city infrastructure! • Pervasive technologies datasets allow to infer micro and macro behaviors of a population! • Inferred demand patterns can be used to make services more adaptive and efficient! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Outline Sensor data assimilation • Continuous assimilation of real-time traffic data Transportation Understanding/Modeling human demand • Characterizing urban dynamics from digital traces Operations & Planning Water • Leveraging mathematical programming for planning in an uncertain world Operations & Planning Multi-domain • Organising data and information to better engage citizens, empower universities and enable businesses to help drive overall growth © 2011 IBM Corporation
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IBM Research and
Development - Ireland Leveraging mathematical programming for planning in an uncertain world Susara van den Heever, PhD Research Staff Member, Analytics & Optimization Smarter Cities Technology Centre IBM Research and Development - Ireland © 2010 IBM Corporation © 2011 IBM Corporation
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IBM Research and
Development - Ireland Overview • Design and planning of urban infrastructures! – Transportation – Water distribution and treatment – Energy • “Standard” optimization approaches minimize costs while meeting demand! • Additional environmental objectives! – Minimize carbon footprint! – Meet pollution reduction targets! • Additional challenge – capturing uncertainty, such as:! – Population growth and urban dynamics! – Rainfall ! – Renewable energy sources! – Energy costs! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Planning Levels Design & long-term planning Tactical planning Decision aggregation Operations planning Operations scheduling Real-time control Real-time Hours Days Weeks Months Years Time horizon © 2011 IBM Corporation
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IBM Research and
Development - Ireland Examples of Decisions Plant & network design (e.g. valve placement), capacity expansion Reservoir Design & longterm targets planning Production, maintenance plans Tactical (e.g. leak detection) planning Decision aggregation Operations Pump planning scheduling Equipment Operations set points scheduling Real-time control Real-time Hours Days Weeks Months Years Time horizon © 2011 IBM Corporation
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IBM Research and
Development - Ireland Impact of Uncertainty Plant & network design (e.g. valve placement), capacity expansion Reservoir Design & longterm targets planning Production, maintenance plans Tactical (e.g. leak detection) planning Population growth Decision aggregation Operations Pump planning scheduling Long-term demand patterns Equipment Operations set points scheduling Energy costs, demand Real-time control Rainfall, renewable energy sources Real-time Hours Days Weeks Months Years Time horizon © 2011 IBM Corporation
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IBM Research and
Development - Ireland Example: Water treatment infrastructure*! Network of pumps, treatment plant, pipelines, and reservoirs! Reservoir! Pumphouse! Reservoir! Treatment plant! Pumphouse! Reservoir! Water Reservoir! Reservoir! source! *Based on Inniscarra network! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Example: Water treatment infrastructure*! Network of pumps, treatment plant, pipelines, and reservoirs! Carrshill Long-term:! reservoir! the best investment “What are Inniscarra pumphouse! Strawhall choices over the next two decades to reservoir! optimize the network design?”! plant! Inniscarra ! Mid-term:! Carrshill Inniscarra “What should the reservoir level pumphouse! reservoir! targets be to best hedge against uncertain demand?”! ! Short-term:! Inniscarra Chetwynd Curraleigh dam! “How can we optimize our low-tariff reservoir! reservoir! pumping?”! Current focus *Based on Inniscarra network! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Summary • Design and planning of urban infrastructures under uncertainty ! • Ignoring uncertainty could lead to costly decisions! • Traditional approaches to dealing with uncertainty! • Often require an expert to implement! • Scenario creation and analysis not obvious! • Research towards generalized approach to aid! • Scenario creation! • Uncertainty and sensitivity analysis! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Outline Sensor data assimilation • Continuous assimilation of real-time traffic data Transportation Understanding/Modeling human demand • Characterizing urban dynamics from digital traces Operations & Planning Water • Leveraging mathematical programming for planning in an uncertain world Operations & Planning • Organising data and information to better engage citizens, empower universities and enable businesses to help drive overall growth © 2011 IBM Corporation
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IBM Research and
Development - Ireland Dublinked and Open City Data Pol Mac Aonghusa Smarter Cities Technology Centre IBM Research and Development - Ireland © 2010 IBM Corporation © 2011 IBM Corporation
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IBM Research and
Development - Ireland Opening the Data locked in our Cities is no longer an option Open access to data and services coupled with ad hoc social innovation are only the beginning Activity Ecosystem Innovation increasingly based on focused on Aggregation Collaboration long-term & Efforts to & Social sustainability Content Content create linkage Innovation Factual & based on Static Semantic Web Publicdata.eu – 35 Cities in LOD2 for Structure Open Data Citizen study >25 Billion Hackday, due 2014 Triples on 12/2010 >350 ‘Open Linked Data City Data Cloud Catalogs’ (data Innovation .gov) 2009, 2011+, Gov 3.0 Time 1993, SEC 2004, USG 2010, .... announces e- Data.gov.uk City as an Enterprise Online Amazon, Gov 2.0 Data.gov (US) Google & MSoft © 2011 IBM Corporation
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IBM Research and
Development - Ireland Open Innovation Portal (OIP) ! publish, organise, discover & consume the information resources of a City Research Challenges include .. Open Innovation Portal Scalable privacy and security of resources Automated assimilation and sharing of Administration Monitor & Events Contents & Catalog resources Knowledge Semantic Query & Robust models to organize and Representation & Privacy & Security represent resources and their context Analytics Reasoning Open REST Web Services API Efficient knowledge representation for continuous machine reasoning and diagnosis Composable resources for Enterprise Applications development, mash-up & visualization IBM Intelligent Operations Center (IOC) IBM Connections Integrated data visualization, real-time Content Sharing & collaboration, deep analytics. Collaboration Services IBM Enterprise Cloud Scalable compute, storage & network infrastructure Key IBM Research Dublin IBM Products & Services City Enterprise Citizen City 2 ..N Partners & People © 2011 IBM Corporation
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IBM Research and
Development - Ireland Dublinked Excellent download statistics The highest demand data sets are for water telemetry reading (Water, Traffic, Planning) Creating meaningful and accurate meta- data is still a tedious and error prone task. Enhanced support a priority for version 2. Have provided a review of site usability & function by student as input. Will also provide analysis of data sets from researchers. http://www-958.ibm.com/software/data/cognos/manyeyes/visualizations/word-tree-of-dublinked-launch-open © 2011 IBM Corporation
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IBM Research and
Development - Ireland How can we help cities achieve their aspirations? " Sensor data assimilation! From noisy data! ! to uncertain information! ! ! " Modeling human demand! ! !Capturing uncertainty! ! ! " Operations & Planning! ! !Factoring in uncertainty! © 2011 IBM Corporation
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IBM Research and
Development - Ireland Working harder is not sustainable Cities require innovative approaches © 2011 IBM Corporation
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IBM Research and
Development - Ireland Publications • The Connected States of America. Can data help us think beyond state lines?, Time Magazine, 11 April 2011! • F Calabrese, D Dahlem, A Gerber, D Paul, X Chen, J Rowland, C Rath, C Ratti, The Connected States of America: Quantifying Social Radii of Influence, International Conference on Social Computing, 2011.! • F. Calabrese, G. Di Lorenzo, L. Liu, C. Ratti, “Estimating Origin-Destination flows using opportunistically collected mobile phone location data from one million users in Boston Metropolitan Area”, IEEE Pervasive Computing, 2011.! • G. Di Lorenzo, F. Calabrese, "Identifying Human Spatio-Temporal Activity Patterns from Mobile-Phone Traces”, IEEE ITSC, 2011! • F. Calabrese, Z. Smoreda, V. Blondel, C. Ratti, “The Interplay Between Telecommunications and Face-to-Face Interactions-An Initial Study Using Mobile Phone Data”, PLoS ONE, 2011.! • D. Quercia, G. Di Lorenzo, F. Calabrese, C. Ratti, “Mobile Phones and Outdoor Advertising: Measurable Advertising”, IEEE Pervasive Computing, 2011.! • F. Calabrese, M. Colonna, P. Lovisolo, D. Parata, C. Ratti, “Real-Time Urban Monitoring Using Cell Phones: a Case Study in Rome”, IEEE Transactions on Intelligent Transportation Systems, 2011.! • L. Gasparini, E. Bouillet, F. Calabrese, O. Verscheure, Brendan O’Brien, Maggie O’Donnell, "System and Analytics for Continuously Assessing Transport Systems from Sparse and Noisy Observations: Case Study in Dublin”, IEEE ITSC, 2011! • A. Baptista, E. Bouillet, F. Calabrese, O. Verscheure, "Towards Building an Uncertainty-aware Multi-Modal Journey Planner”, IEEE ITSC, 2011! • T. Tchrakian, O. Verscheure, "A Lagrangian State-Space Representation of a Macroscopic Traffic Flow Model”, IEEE ITSC, 2011! © 2011 IBM Corporation
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