How to Build a Smarter Planet

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1 Smarter Water Management

2 Building a smarter planet In 2001, there were 60 million transistors for every human on the planet... by 2010 there will be 1 billion transistors per human each costing 1/10 millionth of a cent IBM Corporation

3 Building a smarter planet In 2005 there were 1.3 billion RFID tags in circulation by 2010 there will be 33 billion IBM Corporation

4 Building a smarter planet Worldwide mobile telephone subscriptions reached 3.3 billion in 2007 and expected to reach 4 billion by the end of this year 2009 IBM Corporation

5 Building a smarter planet 1 billion camera phones were sold in G devices growing 30% annually IBM Corporation

6 Building a smarter planet 2011 an estimated 2 billion people will be on the Web and a trillion connected objects cars, appliances, cameras, roadways, pipelines creating the "Internet of Things." 2009 IBM Corporation

7 A Smarter Planet + + = Instrumented Interconnected Intelligent Water Challenge: Whether too much or not enough, the world needs a smarter way to think about water

8 One barrier to better management of water resources is simply lack of data Where the water is, where it's going, how much is being used and for what purposes, how much might be saved by doing things differently. In this way, the water problem is largely an information problem. The information we can assemble has a huge bearing on how we cope with a world at peak water. Source: Wired Magazine, Peak Water: Aquifers and Rivers Are Running Dry. How Three Regions Are Coping, Matthew Power, April 21 st, 2008

9 IBM Global Centres of Excellence (CoE) for Smarter Water Management CoE Netherlands: CoE Ireland: CoE Burlington US: CoE Montpellier : flood management marine environment and water quality industrial water using supercomputers for water flow modeling The aim is to integrate technology, knowledge and expertise to solve large scale water challenges

10 On the Hudson River IBM is building an observatory network from source to sea Project objective: Turning all 315 miles of the Hudson river into a distributed network of sensors that will collect and analyze biological, physical, and chemical information continuously and in real-time Link hydrological models to understand phenomena across a range of spatial and temporal scales REON (River and Estuary Observatory Network) Center for Advanced Environmental Technology (40,000 ft 2 )

11 1 2 3 The Hudson River Visualising the unseen river

12 Point solutions Current Sensor and Actuator Systems Network architecture Future Advanced Water Management Physical World Physical World Business Information System Business Information System Real-Time (Delay Sensitive Transactional Shift in technology in the Hudson River Networks of sensors, running publish and subscribe Real-time processing of information: Steam Computing Integrate understanding with business systems

13 13 Smarter Water: SmartBay Portal Sea conditions Tourism information Ecosystem education Government policy Renewable energy Coastal safety Fisheries Coastal technology Fine scale weather Pollution monitoring Bringing together the people an data to better manage a large scale marine environment

14 Integrated Ireland Bathing Water Information System Provides up to date information about bathing areas across the country. Anyone setting out for the beach will be able to log on and see the latest results of water quality at their favourite bathing spot Details about lifeguard availability Blue flag status, tides and weather forecast so that both Irish people and tourists will have information about safe bathing areas;

15 Drinking Water: Detection of Waterborne Pathogens First-line detection Real-time, on-line, continuous monitoring Proof of water quality over time Real-time data to manage operational risk Long-term data for trend analysis

16 Pulling together all aspects of drinking water production into one place

17 Managing Non Revenue Water (Sonoma, US) 1. Wireless telemetry to provide near real time readings Sensor Data Event monitoring Bulletin Board / Sametime Awareness 2. Data hub for the distribution network to enable optimization of operations: leakage detection, accurate billing, anomaly reporting, pressure management, power management, consumer demand management

18 Flood Management Analytics: Ijkdik large scale sensor test Saturday (approx. 2 days after start) at 16:01:30 A slight dip appears in the middle.

19 Time 16:02:17 Here it goes

20 Time 16:02:29 Final situation (1 minute later) Millions of data points from a wide range of sensors enabling better prediction

21 Fine scale weather prediction + Storm Impact and Response Prediction The Problem: 1. Weather causes damage and outages 2. Outages require restoration 3. Restoration takes time, people, money We build model of the situation (over location and time) covering weather observations, storm damage and related infrastructure data Wind, rain, lightning, location and duration Real time environmental conditions Demographics of effected area Impact locations, timing and response options = better real time and predictive management & importantly a faster recovery Weather prediction Damage prediction Resource requirement prediction Restoration time prediction

22 Smart Storm Water Management System Innovative wireless technology Leveraging sensor and communications technology for informed real-time decision making Dynamically adjust collection system Large numbers of sensors and aggregate information City-wide Monitoring Innovative technology merges with existing infrastructure Predict outcomes with large scale models Fraction of the cost of traditional solutions Key decisions based on fact not assumptions Controls react real time for optimal performance

23 Strategic Water Asset Management Where are my things? What state are they in? Who needs to what? IBM Maximo Software with embedded ESRI GIS

24 Smarter City: Analytics Driven Asset Management In the industrial age it was Physically Driven inspect and if broken then fix it Seasonal Water Usage & their mapping to pressure zones Sudden jump in reading Decreasing reading? Average water consumption by customer Forecasting usage Detecting anomalies

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29 The Challenge of a Smarter Planet do you know enough, at the scale of the problem? can you make sense of it? can you act on it? do you have the collaborative relationships you need with others? (data sharing & agreeing on actions)

30 A Smarter Planet Instrumented Interconnected Intelligent + + = An opportunity to think and act in new ways: economically, socially and technically. Grazie Ian Abbott-Donnelly uk.ibm.com

31 Appendix on what Smarter is

32 How do we Bringing the people, the data and technology to create innovation Discuss Exploration 2-4 weeks Plan Exploration Joint Exploration Determine Outcome Path Support Outcome Path 6-8 weeks 1-3 days Varies (60-90 days) Varies Understand each other and gain commitment Identify topics and prepare for exploration Engage in working sessions Vet opportunities and gain further commitment Support and develop ideas

33 Building a smarter planet Smarter organizations will design products with the right ecosystem of partners and experts. SMART IS Managing a constantly changing set of requirements. SMART IS Targeting products for diverse markets. SMART IS Enabling dozens of partners to collaborate. BAE Systems Australia: Created a requirements-driven approach to development to streamline multiple, diverse requirements which had made it impossible for developers to trace requirements and collaborate efficiently, resulting in duplicated effort. The company experienced improved productivity and greater confidence that all customer-requested changes were included in the final product. 33 ABB: To reduce the time required to track, trace and prioritize product requirements for power and automation technologies for a wide range of utility and industry customers, ABB implemented software to help manage and prioritize requirements in order to create products that best meet the needs of their customers, improving product success through the selection of the right products for their marketplaces. NASA: To improve collaboration between separate space agencies from over a dozen different countries developing the software and systems that will operate the James Webb Space Telescope, NASA used real-time visual modeling development software that acts as a blueprint for the entire project, allowing developers of various telescope systems to easily implement software code directly into the blue print where it is then automatically made available across the entire project team, circumventing expensive and time consuming issues IBM Corporation

34 Building a smarter planet Smarter organizations will create the flexibility to undertake frequent updates without compromising integrity. SMART IS Responding to consumer demand more quickly. SMART IS Knowing where everything is in the supply chain. SMART IS Reusing existing capability to quickly deliver new products and services. BMW: Consolidated design environments and created a single reference model for the design of all future engines, enabling the company to quickly respond to consumer changes and production demand by having immediate access to global design plans and making those updates digitally so they are instantly shared across global manufacturing sites and with partners in the supply chain. METRO Group: Implemented an RFID tracking process to provide suppliers with a clear view of where their products through shipping, arrival at METRO Group distribution centers, and delivery to the shelves of individual retail stores. The supplier can determine whether an item that is part of a special promotion is on the shelves of the right store at the right time, and they can take corrective actions if items are not where they should be. Océ: Adopted IBM Rational solutions for modeldriven development and solutions for software change and configuration management to build its embedded systems. Océ can now reuse more than 50 percent of its software components from project to project, enabling the company to build a working prototype of a new printer in just two months a process that previously took eight months IBM Corporation

35 Building a smarter planet Smarter organizations will seamlessly integrate software, electronics and mechanical technologies. SMART IS Enabling systems to talk to each other. SMART IS Putting images and data in the palm of frontline people. SMART IS Identifying and fixing flaws sooner. Curtiss-Wright: In order to ruggedize computer systems for unmanned aerial vehicles and enable interconnectivity with on-board and ground systems, Curtiss-Wright implemented software tools to manage requirements and change across multiple product variants and reuse software components to increase reliability and reduce costs, resulting in greater speed, reliability and accuracy of onboard systems, which allow unmanned aircraft to fly for up to 30 hours at altitudes greater than 50,000 feet. 35 Merge Healthcare: Provides doctors, radiologists and other medical professionals easier access to medical images including x-rays, MRIs and CT scans using a mobile device or desktop computer without waiting for medical imaging films, accessing a specialized system or downloading cumbersome files. Simplifying the process of managing changes throughout the life of this software ensures that all processes for the development and delivery of software can be defined, implemented, automated, visualized and managed collaboratively. Easun Reyrolle Limited: To accelerate development and manage research and development projects among its teams, Easun uses the Logiscope tool to identify software flaws early in the lifecycle, minimize the company s debugging time, increase productivity through user-friendly, task-based configuration management, and improve communication among distributed teams IBM Corporation

36 Building a smarter planet Smarter organizations will shift to more dynamic processes for building and testing products. SMART IS Shortening the design cycle with product modeling. SMART IS Not reinventing the wheel. SMART IS Streamlining the development process. Eaton Corporation: Is using modeling software that helps improve quality and save time in the development of a hydraulic hybrid system that promises dramatic fuel savings and environmental benefits in UPS fleet trucks. Project teams model the software that makes the SHH system work, allowing development teams to be more efficient and shorten design cycles. Valtech: To create a new object-oriented process for global development in response to an avionics customer s request, Valtech enabled developers to reuse objects and requirements in a concurrent engineering environment, achieving a 40 percent increase in productivity and reducing defects by 75 percent while lowering development costs for the customer. Jeppesen: To ensure the accuracy, dependability and usability of the software it develops for managing and publishing highquality aviation and marine data, the company used IBM Rational Method Composer software to create a customized methodology that incorporates proven project management best practices, increasing the repeatability of its development processes, improving software quality, cutting build times by 90 percent and increasing productivity IBM Corporation

37 Update on Hudson River Project June 2010 The current status of the Beacon REON (River and Estuary Observatory Network) project is that we are just completing the first phase of the project on which collaborated on the design of the cyberinfrastructure and information infrastructure. Within this phase we have also completed several pilot/demonstration projects involving a number of key components including an embedded intelligent platform for complex sensors using middleware components such as Harmony and the software framework ics (Internet Scale Control Systems). The pilot also involves high bandwidth streaming data which is then analyzed in real-time using System S/InfoSphere Streams. We expect to announce and publish (in a peer reviewed scientific paper) this within the next few months. Beacon is continuing to deploy sensors as described in our paper (the robotic platform with a number of sensors, including complex sensors such as LISST...please see below): Salinity Turbidity Temperature Conductivity Dissolved oxygen Chlorophyll a Particle size (using laser in situ scattering and transmissometry, or LISST) Coloured dissolved organic matter (CDOM) Total petroleum hydrocarbons (TPH) The platform also hosts an acoustic Doppler current profiler (ADCP) to measure water current structure and a meteorological sensor package to monitor meteorological conditions such as wind speed and direction and atmospheric pressure. Most of these sensors are part of a robotic mechanism that moves the payload through the water column to take measurements at five different positions in the water column (this of course may be varied). They expect to deploy several of these over the next year in addition to other sensors. IBM J of R&D paper for a good overview of the project. ups%2fn%2fna%2fnano-tera%2fwww%2fibm_wsn_complex_realtime.pdf&ei=g1uhtpkjhqh80wt8ulxo&usg=afqjcnexm2h0rb2flodi2vfeue0qejqwfa

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