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Smarter cities: Important Lessons Learned

Jean-François Barsoum jbarsoum@ca.ibm.com Senior Managing Consultant. Smarter cities: Important Lessons Learned. Lesson # 1. Water. GHG. Energy. May 23rd, 2007. 4. 4. Lesson # 1: Cities are the place where environmental problems have to be solved. Lesson # 2. Congestion is expensive.

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Smarter cities: Important Lessons Learned

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  1. Jean-François Barsoum jbarsoum@ca.ibm.com Senior Managing Consultant Smarter cities: Important Lessons Learned

  2. Lesson # 1

  3. Water GHG Energy

  4. May 23rd, 2007 4 4

  5. Lesson # 1: Cities are the place where environmental problems have to be solved

  6. Lesson # 2

  7. Congestion is expensive • 1-3% of GDP • $3B a year for Montreal • Reduce congestion by 10% = 3% more employment growth 50% reduction = 15% more growth Infrastructure too! • China: 221 cities over 1M by 2030 • 35 000 billion $ in infrastructure • India: 68 cities over 1M by 2030 • 2 200 billion $ • 5h commutes!!! Source: Kent Hymel, “Does traffic congestion reduce employment growth?” Journal of Urban Economics 2009.

  8. Lesson # 2: The solution to traffic is not to build more physical infrastructure

  9. Lesson # 3

  10. Realtime Origin destination to redefine public transit lines

  11. London

  12. Financing infrastructure in Stockholm Stockholm

  13. Trial period 2005 2006 Fin du projet pilote

  14. Trafic intelligent : Projet novateur Stockholm

  15. Public opinion 2005, 2006, 2007, 2010

  16. For all roads Based on GPS location OBU GPS Vignette GSM 20 12 10 5 5 3 2 2 Road user charging based onDistance, time, place & pollution

  17. Lesson # 3: Changing habits is not necessarily expensive

  18. Lesson # 4

  19. Lesson # 4: Technology is not the biggest obstacle. Lack of planning is!

  20. Lesson # 5

  21. Singapore: EZ-Link

  22. Londres: TfL

  23. Lesson # 5: Governance is KEY!

  24. Lesson # 6

  25. Lesson # 6: You are going to have to deal with lots, and lots, of data – so once again: PLAN AHEAD!

  26. Lesson # 7

  27. Flooding in NYC Estimations Prévisions et mesures météo Analyse des précipitations Prévisions des inondations Recalibration des senseurs Inondations Calibration des modèles Prévision de l’impact

  28. Lesson # 7: Realtime is NOT good enough!

  29. Lesson # 8

  30. 2006 2008 2010 Rio de Janeiro planning centre Emergency planning

  31. « Walkscore » (Peterborough, UK)

  32. Lesson # 8: There is a real need for inter-departmental collaboration

  33. Lesson # 9

  34. Citizens become active data collectors and sharers – use them!

  35. Lesson # 9: Help citizens help you

  36. Lesson # 10

  37. NASA/ Star Trek Livable Connected Masdar

  38. Lesson # 10: There is no single correct definition of a Smarter City

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