Intelligent Operations Center

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© 2011 IBM Corporation IBM Industry Solutions Intelligent Operations Center for Smarter Cities Programming Guide Guidance for Integration with the IBM Smarter Cities Software Solutions Ron Baker Senior Technical Staff Member Software Group Industry Solutions Architecture June 9, 2011 Edition Suitable for External Use

Transcript of Intelligent Operations Center

Page 1: Intelligent Operations Center

© 2011 IBM Corporation

IBM Industry Solutions

Intelligent Operations Center for Smarter CitiesProgramming GuideGuidance for Integration with the IBM Smarter Cities Software Solutions

Ron BakerSenior Technical Staff Member

Software Group Industry Solutions ArchitectureJune 9, 2011 Edition

Suitable for External Use

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IBM Industry Solutions

IBM Smarter Cities Initiative © 2011 IBM Corporation2

The Intelligent Operations Center Content

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IBM Smarter Cities Initiative © 2011 IBM Corporation3

The Entertainment Venue Attendance Management Use Case

Betty, the Cross-Organization Operations Manager is watching the large monitors in the Operations Center, and sees an event that the Stadium Gates have now opened. She begins to watch attendance arrival rates and be ready for potential adjustments. As the crowd flows through the gates and into the turnstiles, information is sent to her monitors, and she focuses on the Dashboard display where the Attendance Management entry has a “green” status. After a few minutes, she opens a report to see the average arrival rate per minute through the turnstiles.

Based on working many events, she knows the normal patterns for turnstile counts in the first few minutes after opening, and everything is working well. After a few minutes, Betty sees on the dashboard as the Attendance Management entry has now turned red. One of the turnstiles has a zero count while other turnstiles at that gate are still busy, indicating a potential problem. She looks at the updated report and notices that the average count has dropped out of normal range. Based on defined policy, the Intelligent Operations Center has started a operating procedure that automatically notified Tom, the Maintenance Director, to check on the situation.

Tom checks out the turnstile and determines that it needs repair. Leveraging the next step in the operating procedure, he opens a Maintenance Work Order, which immediately notifies the assigned maintenance expert. Tom waits for the expert to arrive and then monitors the situation through the operating procedure updates.

Betty can also monitor the operating procedure for the latest information, and notices that Tom has determined that Turnstile 1 is not operating correctly she can see the work order progress. Betty checks the report again to see how this is affecting crowd flow, and can call the security staff to help direct crowd flow appropriately.

Once repaired, Betty can see the work order completed, and watches the dashboard for the turnstile counts to returnto their normal range, and turn to “green” status. Now the staff can focus on other areas.

After the event is complete, Betty receives an event on the monitor that the gates have been closed.

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The Entertainment Venue Operations Center Examples

Stadium

Cruise Ship

Theatre

Attendance Analysis•Ticket sales, event dates•Entry/Exit flow patterns

Public Safety & Security•Individual medical•Restricted access areas•Weather delays•Mass threats, evacuation

Transportation•Highway traffic outside venue•Parking•Crowd flow

Water•Overall Usage and Optimization•Consumption versus Sanitation usage

Energy Usage•Overall Usage and Optimization

and so on…•similar to a city infrastructure

Physical Meets Digital: Turnstile Sensor Data

The Potential Uses Cases Include:

The Potential Venues Include:

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Kay Values

• Provides better proactive management of traffic

• Uses a combination of historical and real time traffic data to predict the rates of traffic flow in the near future (10-60 minutes)

• Predictions for areas for which current traffic flow information is not available – Data Expansion Capability

• Has proven to be more accurate than existing traffic prediction methods.

• Is highly efficient and can be run on a medium- to large-size network in real-time.

• Provides valuable input to traffic operators

• Can augment future predictive to real-time data as input for traveler information systems in route planning

Customer Pain Addressed:• Increasing Congestion – Everywhere

• Wasted time, wasted fuel, wasted productivity

• Negative impact on a region’s economic vitality, growth and competitiveness

• Deteriorating Infrastructure• Roads and bridges need significant rehabilitation

• Risk of serious infrastructure failures impacting public safety

• Funding Gap is Growing• Many important needs with limited financial resources

• Gas tax no longer a reliable source of sustained funds

• Environmental Impact• Traffic is the single largest contributor to poor air quality

• Negative impact on health and quality of life

• Safety• Traffic crash statistics improved; yet, always more to do

Lane control employed to open additional outbound lane

Traffic signal timing patterns adjusted along parallel arterials

Variable message signs display alternate route information

Warning of potential commute troubles -Reroute Advice

Traveller Portal

Traffic News Ticker

Solution Software Key Components:

2. Predictive Analytics Engine

3. Data Expansion Algorithm

4. Data Integration, Query & Visualization Module

5. Cloud Enabled

6. Operation Center Function & Container

Transportation Domain Accelerator: The Traffic Prediction Tool

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The Intelligent Operations Center Contacts and ReferencesIBM Intelligent City Operations Center 1.0 Architecture PreviewSWG Architecture Board, May 19, 2011https://w3.blueprint-secured.sby.ibm.com/b_dir/blueprint.nsf/url2/AB089797?OpenDocument

IBM Intelligent Operations Center for Smarter Citieshttp://www-01.ibm.com/software/industry/intelligent-oper-center/

IBM Intelligent Operations Center for Smarter Cities Press Releasehttp://www-03.ibm.com/press/us/en/pressrelease/34665.wss

Sales: Vinod Chavan/Tampa/IBM@IBMUSPresales Architecture:Europe: Marc Fiammante/France/IBM@IBMFR Rick Robinson/UK/IBM@IBMGBNorth America: Mike Beranek/Chicago/IBM@IBMUSGMU: David Waxman/Watson/IBM@IBMUSSWG Services: Tom Luzzi/Raleigh/IBM@IBMUSProduct Management: Michael Kehoe/Ireland/IBM@IBMIE (Mike)

Portfolio Architecture:Steven De Gennaro/Watson/IBM@IBMUS (Steve)

Pam Nesbitt/Tampa/IBM@IBMUSMike Kloke/Markham/IBM@IBMCA

Product Architecture: Anthony L Carrato/Somers/IBM@IBMUS (Tony)User Experience: Carolyn Hyink/Austin/IBM@IBMUSProgramming Model: Ron B Baker/Durham/IBM@IBMUS