Author: Andrew Brown


Publication Date: Sep 30 2015


Pages: 97


Report Type: Forecast and Outlook



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The Future of Smart Cities - Opportunities, Solutions and Players




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Report Summary:

The United Nations predicted in 2008 that the end of the year would be a tipping point when more than 50% of the world’s population would live in urban areas. The urban tipping point coincided with the tipping points in ICT around the adoption of smartphones and a shift to cloud computing solutions. In recent years, the growth in IoT solutions, building on point M2M solutions of the past, offers an even greater opportunity to create smart cities by combining ICT services such as cloud computing and enterprise back-end systems with end points in an urban environment providing valuable data and information about multiple components of smart cities, from street lighting to parking, building automation and municipal information systems.

This foundational study looks into the ‘smart city’ approaches of ICT and IoT vendors and service providers and their solutions are described, together with recommendations for the future. Different approaches to “smart cities” are covered by this report. This paper looks at the positive and negative effect of new players, and safety concerns associated with a connected city. 



Table of Contents

1.       Executive Summary  6

2.       Introduction  8

2.1     Defining the Smart City  8

2.1.1       What is a City?  8

2.1.2       Smart Use of ICT can Help Cities Maximize on Scale  9

2.1.3       Smart Cities are more than Smart ICT  10

2.2     Challenges for the Smart City  11

2.2.1       Smart Energy and Smart Grids  13

2.2.2       Smart Water 14

2.2.3       Smart Transportation  15

2.2.4       Smart Buildings  17

2.2.5       Smart Government 18

2.3     Smart City Drivers  20

2.4     The ‘Scratch-Built’ Smart City  22

2.5     Smart City components  24

3.       The Market Opportunity for Smart Cities  26

3.1     Asia-Pacific  27

3.2     Central and Latin America  30

3.3     North America  31

3.4     Europe  31

3.5     Middle East and Africa  32

4.       Smart City Forecasts  34

4.1     Connections and Revenue per Application Area  37

4.1.1       Smart Health  37

4.1.2       Smart Infrastructure  37

4.1.3       Smart Security  38

4.1.4       Smart Building  38

4.1.5       Smart Energy  38

4.1.6       Smart Transport 38

4.1.7       Smart Government 38

4.2     Connections and Revenue per Region  39

4.2.1       Asia-Pacific  39

4.2.2       Central America/Latin America  40

4.2.3       North America  40

4.2.4       Western Europe  40

4.2.5       Central and Eastern Europe  40

4.2.6       Middle East and Africa  40

4.3     Smart City Business Models  41

4.3.1       A variety of Models are Needed  41

4.3.2       The Gap between Technology Demonstrators and Mass Deployment 43

5.       Smart City Challenges  44

5.1     New Services Disrupting Existing Infrastructure  44

5.1.1       Uber 45

5.1.2       AirBnB. 46

5.1.3       Other Potential ‘Sharing Economy’ Disruptors  46

5.1.4       Sharing Economy and Smart Cities  47

5.2     Safety and Security  47

6.       Smart City Ecosystems  49

6.1     C40Cities Climate Leadership Group  49

6.2     Connecting Europe  50

6.3     Selected Case Studies  51

6.3.1       Unified Fare System for Singapore Land Transport Authority (LTA) 51

6.3.2       22@Barcelona  52

6.3.3       Christchurch, New Zealand  53

7.       Key Technology Players  55

7.1     IBM   55

7.2     Cisco  58

7.3     Schneider Electric  60

7.4     Ericsson  61

7.5     Hitachi 62

7.6     Huawei 65

7.7     Autodesk  66

7.8     Microsoft 66

7.9     Accenture  69

7.10   Capgemini 69

7.11   Siemens  70

7.12   Honeywell 72

7.13   Oracle  74

7.14   GE  75

7.15   SAP  77

8.       Key Service Providers Targeting Smart Cities  79

8.1     AT&T  79

8.2     Vodafone  80

8.3     China Mobile  80

8.4     Telefonica  81

8.5     Orange  83

9.       Smart City Evolution  85

9.1     Standardization  85

9.1.1       Standardized Measurement 85

9.1.2       Standardized Platforms  86

9.1.3       FIWARE  86

9.2     Visualization  90

9.3     Smart Citizen Evolution  92

10.     Recommendations  95

10.1   ICT Vendors  95

10.2   Service Providers  95

11.     Conclusions  96

12.     Contact the author of this report: 97

Exhibits

Figure 1: Urban ICT Revenues by 2022. 7

Figure 2: City Parameters Increase 1.5X as City Doubles. 9

Figure 3: Screenshot of Microsoft Your Weather app. 12

Figure 4: Singapore Intelligent Energy System (IES) 14

Figure 5 Waze Smartphone Display. 16

Figure 6: Microsoft Building Efficiency with Recommissioning. 18

Figure 7: Smart City Triangle of Opportunity. 21

Figure 8: Scratch-Built Smart Cities. 22

Figure 9: Smart City Components. 24

Figure 10: CityOS Architecture. 25

Figure 11: Urbanization and the APAC Circle. 26

Figure 12: Singapore’s Push to Become a Smart Nation. 29

Figure 13: Smog Dispersing Building, Mexico City. 30

Figure 14: Smart City Forecasts Mapped to Components. 35

Figure 15: Urban ICT Revenues Totals. 36

Figure 16: Urban ICT Revenue per Application. 37

Figure 17: Urban ICT Revenue Per Region. 39

Figure 18 Four Dominant Smart City Models. 42

Figure 19: Decline of Average Trips per Taxi Car in San Francisco. 45

Figure 20: Connected Infrastructure Security Concerns. 48

Figure 21: C40Cities Overview. 49

Figure 22: C40Cities Profile, Copenhagen. 50

Figure 23: Cisco Sensor Demos, 22@Barcelona. 53

Figure 25: IBM Smart City Core Operation Areas. 56

Figure 26: Stockholm Road Toll Sensing. 57

Figure 27: Cisco Smart City Architecture. 59

Figure 28: Ericsson Smart Metering. 62

Figure 29: Hitachi Information Control Platform for Public Infrastructure. 64

Figure 30: Huawei Smart City Portfolio. 65

Figure 31: Autodesk Digital Cities 3D Model 66

Figure 32: Bismart City Dashboard for Microsoft Azure solution. 68

Figure 33: Siemens SItraffic Interface on Smartphone. 71

Figure 34: Scope of Siemens Electromobility. 72

Figure 35: Honeywell Enterprise Buildings Integrator (EBI) 73

Figure 36: Oracle Smart City Solution. 74

Figure 37: GE Streetlight Sensor Vision. 76

Figure 38: SAP Data Vizualization of Taxi Movements in City. 78

Figure 39: Telefonica City Platform integration for Valencia. 82

Figure 40: User Dashboard for Telefonica Thinking Things. 83

Figure 41: Orange Flux Vision data for People Flows. 84

Figure 42: ISO 37120 Standardization. 86

Figure 43: FIWARE Lab Operational Node Snapshot 88

Figure 44: FIWARE Smart City Activities. 89

Figure 45: Boston City Data Visualization. 91

Figure 46: California Department of Public Health’s Healthcare Associated Infections map. 92

Figure 47: Smart City Citizens as Service Providers. 93


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