Easy Park

Smart City Index 2018


En EasyPark, creemos en aprovechar la tecnología para crear ciudades eficientes e intuitivas. Sabemos que una red integrada de transporte y comunicación ahorra tiempo, energía y dinero. La digitalización no solo mejora las ciudades: Mejora la calidad de vida.

Los retos que enfrentan las ciudades cambian rápidamente. No solo son más complejos, sino que son específicos para cada lugar. Por eso, en EasyPark, creamos el Índice de ciudades inteligentes 2018. Con nuevos criterios e innovaciones, el índice proporciona datos específicos sobre la tendencia de las inversiones gubernamentales de ciudades de todo el mundo, desde la cantidad de puntos de recarga hasta la frecuencia de las transacciones de Bitcoin: estas son las conclusiones a las cuales EasyPark ha llegado hasta la fecha.

La definición de ciudad inteligente evoluciona constantemente en la medida que surgen descubrimientos que mejoran nuestra calidad de vida. Con esto en mente, en el índice de este año hemos incluido: Provisión de estacionamiento inteligente, tasa de reciclaje, inversión en infraestructuras, puntos de recarga de vehículos, ecosistemas de cadena de bloques (blockchain), seguridad cibernética e índice de sostenibilidad en la definición que proponemos sobre lo que constituye a una ciudad inteligente.

Para la segunda edición de este estudio, analizamos 500 ciudades en todo el mundo en un total de 24 factores, y clasificamos las 100 primeras para determinar las ciudades que administran sus activos y recursos de manera más eficiente.

"A medida que más y más personas emigran a las ciudades, 3 millones de personas por semana, esto plantea desafíos que solo la tecnología puede abordar. Una de las principales causas de la congestión del tráfico son las personas que conducen en círculos en busca de estacionamiento. En EasyPark, nuestras soluciones de estacionamiento inteligente hacen la vida urbana más fácil ", dice Johan Birgersson, CEO del Grupo EasyPark.

El índice de ciudades inteligentes 2018 es un análisis aún más sofisticado sobre las ciudades con la tecnología más avanzada del mundo. Ofrece un desglose claro de ciudad a ciudad de los indicadores clave que definen una ciudad inteligente, incluida la cantidad de puntos de acceso WiFi, edificios inteligentes y, por supuesto, estacionamiento inteligente. Mientras ciertos países continúan a la cola, está claro que muchos otros ya han tomado medidas importantes para crear lugares para vivir más saludables, más limpios y más eficientes

  •  Smart Parking
  •  Car Sharing Services
  •  Traffic
  •  Public Transport
  •  Clean Energy
  •  Smart Building
  •  Waste Disposal
  •  Environment Protection
  •  Citizen Participation
  •  Digitalization of Goverment
  •  Urban Planning
  •  Education
  •  Business Ecosystem
  •  4G LTE
  •  Internet Speed
  •  Wifi Hotspots
  •  Smartphone Penetration
  •  Living Standard
  •  How the City is Becoming Smarter
      Transport and mobility Sustainability Governance Innovation
Economy
Digitalization Cyber
Security
Living
Standard
Expert
Perception
 
# CITY
COUNTRY
Smart Parking
 Car sharing services
 Traffic
Public Transport
Clean Energy
Smart Building
Waste Disposal
Environment Protection
Sustainability Index
Citizen Participation
Digitalization of Goverment
Urban Planning
Education
Business ecosystem
Blockchain Ecosystem
4G LTE
Internet Speed
Wifi Hotspots
Smartphone Penetration
Cyber security
Living Standard How The City Is Becoming Smarter
RANK/
SCORE
1 Odense Denmark 4.75 2.80 9.48 2.88 8.47 6.78 8.18 6.55 8.58 9.38 8.35 4.53 9.33 6.48 1.31 7.90 7.23 1.60 9.70 7.15 8.50 6.46 6.49
2 Aalborg Denmark 2.58 2.05 8.73 2.88 8.47 6.78 8.18 6.33 8.58 9.23 5.95 7.08 8.58 7.38 1.31 8.20 7.83 1.83 9.70 7.15 7.98 6.46 6.25
3 Oulu Finland 7.23 2.13 8.73 6.70 7.86 3.63 5.24 3.33 9.33 4.31 5.05 7.08 8.50 8.13 7.05 7.45 6.40 2.80 8.87 8.73 7.00 3.00 6.20
4 Koge Denmark 3.10 2.95 10.00 2.88 8.47 6.78 8.18 6.85 8.58 9.69 7.08 2.05 9.70 7.23 1.31 6.70 5.73 1.45 9.70 7.15 7.45 3.00 6.18
5 Strasbourg France 3.25 6.10 6.33 5.65 3.82 8.35 6.29 9.25 6.55 4.62 7.68 7.08 8.05 4.98 7.05 8.28 9.10 2.58 3.65 6.70 5.20 6.46 6.15
6 Bordeaux France 3.70 6.03 4.60 5.65 3.82 8.35 6.29 9.33 6.55 4.46 8.80 9.55 8.88 5.73 7.05 4.53 4.38 1.08 3.65 6.70 5.28 3.00 5.93
7 Turku Finland 3.33 2.20 9.48 6.70 7.86 3.63 5.24 3.40 9.33 5.15 4.15 4.53 8.80 7.68 7.05 8.35 7.68 2.65 8.87 8.73 6.78 7.15 5.90
8 Nice France 4.15 3.63 5.73 5.65 3.82 8.35 6.29 9.03 6.55 4.38 5.65 2.28 6.78 8.50 7.05 7.98 8.88 3.18 3.65 6.70 4.53 3.00 5.80
9 Vantaa Finland 4.00 5.88 9.85 6.70 7.86 3.63 5.24 3.25 9.33 3.85 8.88 4.53 7.75 5.58 7.05 6.03 4.30 2.13 8.87 8.73 5.88 3.00 5.79
10 Joensuu Finland 4.98 2.73 8.73 6.70 7.86 3.63 5.24 4.00 9.33 3.92 6.93 4.53 9.63 6.25 7.05 4.98 3.48 1.68 8.87 8.73 6.70 6.46 5.79
11 Nantes France 2.35 4.23 7.53 5.65 3.82 8.35 6.29 9.10 6.55 4.77 8.43 5.50 7.45 6.63 7.05 6.33 6.55 1.00 3.65 6.70 5.05 3.00 5.78
12 Jyväskylä Finland 1.68 2.43 7.98 6.70 7.86 3.63 5.24 3.55 9.33 4.15 8.20 4.53 9.10 5.95 7.05 8.05 7.15 1.30 8.87 8.73 6.63 3.00 5.71
13 Lahti Finland 7.08 2.58 4.23 6.70 7.86 3.63 5.24 3.63 9.33 6.46 5.80 4.53 9.03 6.10 7.05 4.30 2.58 1.75 8.87 8.73 6.93 3.00 5.70
14 Hämeenlinna Finland 2.13 2.88 10.00 6.70 7.86 3.63 5.24 4.08 9.33 4.77 9.40 2.05 9.48 6.48 7.05 4.68 2.88 1.15 8.87 8.73 7.60 6.46 5.62
15 Verona Italy 3.78 1.90 9.48 2.28 6.87 7.38 7.20 8.13 4.30 7.23 7.30 7.08 7.38 3.25 7.05 7.68 7.30 3.03 4.63 3.93 4.23 3.38 5.58
16 Perugia Italy 3.93 2.28 9.48 2.28 6.87 7.38 7.20 8.28 4.30 7.38 3.10 4.53 8.65 1.98 7.05 5.58 4.75 2.43 4.63 3.93 4.75 1.00 5.20
17 Florence Italy 2.43 6.40 7.23 2.28 6.87 7.38 7.20 7.83 4.30 6.62 8.28 4.98 6.63 3.40 7.05 4.00 3.03 4.08 4.63 3.93 3.63 6.46 5.12
18 Bari Italy 2.28 1.83 6.63 2.28 6.87 7.38 7.20 7.98 4.30 6.85 5.28 2.13 7.60 4.08 7.05 8.43 8.58 1.53 4.63 3.93 4.45 3.00 5.11
19 Catania Italy 2.20 4.68 5.73 2.28 6.87 7.38 7.20 8.05 4.30 6.92 4.83 1.23 7.00 2.80 7.05 7.15 6.78 2.50 4.63 3.93 4.83 6.46 4.97
20 Ancona Italy 1.45 2.65 8.73 2.28 6.87 7.38 7.20 8.80 4.30 6.46 5.50 4.53 9.18 2.13 7.05 2.95 2.05 1.38 4.63 3.93 4.60 3.00 4.86
21 Genova Italy 3.48 3.40 7.98 2.28 6.87 7.38 7.20 7.68 4.30 5.77 5.43 2.50 4.83 1.53 7.05 4.23 3.40 2.88 4.63 3.93 4.30 1.08 4.64
22 Copenhagen Denmark 6.03 7.23 8.73 2.88 8.47 6.78 8.18 5.88 8.58 9.46 9.25 8.80 6.40 9.18 3.48 5.58 4.53 5.43 9.70 7.15 6.10 9.23 6.75
23 Singapore Singapore 7.00 6.85 3.78 9.93 1.46 6.40 9.09 3.93 1.98 10.00 3.25 3.33 1.15 8.88 7.67 9.93 10.00 9.85 9.77 10.00 8.35 10.00 6.13
24 Stockholm Sweden 6.85 7.90 6.33 4.60 8.93 5.05 8.71 9.70 10.00 9.23 10.00 7.45 5.05 5.80 3.33 6.78 7.00 6.18 8.03 7.75 7.75 10.00 6.95
25 Zurich Switzerland 3.18 7.53 4.60 8.43 8.93 7.53 8.94 9.55 8.13 2.00 8.58 4.83 7.68 8.95 4.10 8.88 8.95 5.13 7.73 7.98 9.63 6.46 6.67
26 Boston United States 6.93 8.43 6.33 6.85 2.45 9.03 5.76 2.58 4.83 3.77 4.98 4.68 7.90 10.00 9.69 5.35 8.35 6.18 6.97 6.18 8.88 9.23 6.81
27 Tokyo Japan 9.78 8.80 2.35 9.25 3.97 8.50 3.42 3.18 6.55 2.46 6.40 6.25 2.28 6.78 1.47 1.83 3.33 9.55 1.76 9.33 3.93 10.00 5.40
28 San Francisco United States 6.10 9.03 2.58 7.53 2.45 9.03 5.76 2.35 4.83 2.85 5.73 1.68 6.93 9.78 10.00 3.18 5.35 8.58 6.97 6.18 8.43 6.46 6.30
29 Amsterdam Netherlands 8.35 8.88 8.88 3.93 1.92 6.85 8.94 3.48 4.90 9.08 9.48 8.43 5.43 9.55 9.22 8.13 6.70 8.13 6.45 7.23 7.38 10.00 6.92
30 Geneva Switzerland 2.80 5.05 3.25 8.58 8.93 7.53 8.94 9.40 8.13 1.69 6.03 5.88 6.70 9.33 3.72 6.55 5.88 4.38 7.73 7.98 9.48 6.46 6.09
31 Melbourne Australia 8.58 6.55 4.23 9.70 2.75 6.33 4.18 1.08 3.18 9.85 3.93 6.40 2.73 2.65 3.64 6.03 2.13 5.95 4.93 9.63 6.40 6.46 5.21
32 Vancouver Canada 5.88 10.00 2.58 7.30 9.24 4.38 3.80 2.20 5.43 4.92 7.90 6.70 7.15 8.80 7.59 9.55 9.18 6.78 7.28 9.93 5.35 7.15 6.65
33 Sydney Australia 7.53 7.83 2.58 9.70 2.75 6.33 4.18 1.00 3.18 9.92 3.70 7.30 2.35 7.08 7.28 9.18 5.80 7.90 4.93 9.63 6.03 6.46 5.77
34 Berlin Germany 9.63 9.63 5.73 3.70 5.73 10.00 9.92 3.70 7.53 8.15 2.65 8.20 3.03 3.48 9.61 3.55 5.28 8.95 6.45 5.65 7.53 7.23 6.71
35 Hamburg Germany 8.80 8.73 4.23 3.70 5.73 10.00 9.92 4.23 7.53 6.77 3.25 8.58 4.23 8.20 9.30 2.20 3.10 5.28 6.45 5.65 7.08 7.15 6.52
36 Gothenburg Sweden 7.90 7.60 8.73 4.60 8.93 5.05 8.71 9.85 10.00 8.77 9.85 5.58 6.10 7.45 2.55 8.58 9.25 4.15 8.03 7.75 8.13 9.23 7.24
37 Montreal Canada 10.00 9.55 5.73 7.30 9.24 4.38 3.80 1.75 5.43 3.31 6.70 9.85 4.53 8.28 7.52 9.33 8.80 6.93 7.28 9.93 5.80 9.23 6.84
38 London United Kingdom 9.85 9.70 2.35 6.70 4.74 9.25 7.50 5.73 5.73 4.08 1.08 8.95 1.98 5.05 9.77 3.85 6.25 9.78 5.54 4.53 4.00 9.23 5.99
39 Tel Aviv Israel 2.05 6.70 3.48 4.83 1.53 5.88 2.74 4.30 2.35 3.23 7.83 8.88 6.85 8.73 3.95 2.05 3.70 7.30 6.45 2.35 2.65 10.00 4.43
40 Paris France 7.15 9.93 2.88 5.65 3.82 8.35 6.29 7.53 6.55 5.31 9.33 9.48 3.55 8.58 9.61 7.90 8.43 8.73 3.65 6.70 3.70 6.46 6.61
41 Toronto Canada 9.25 9.25 4.98 7.30 9.24 4.38 3.80 1.45 5.43 5.77 2.95 9.93 3.40 7.90 8.22 7.53 5.50 8.05 7.28 9.93 5.43 9.23 6.42
42 Seoul South Korea 6.33 9.78 2.35 9.25 1.38 5.28 8.71 2.43 6.78 6.23 3.85 5.28 1.60 6.33 1.00 7.60 7.45 9.03 7.58 4.68 3.25 9.23 5.30
43 Luxembourg Luxembourg 1.83 5.13 4.23 8.43 5.81 5.13 8.26 2.73 7.68 9.85 7.23 7.98 9.78 7.75 7.05 4.53 2.43 3.48 9.92 6.78 9.78 6.46 5.98
44 Helsinki Finland 6.48 5.50 7.23 6.70 7.86 3.63 5.24 3.85 9.33 5.38 9.55 2.80 5.20 7.15 8.14 8.65 7.90 5.73 8.87 8.73 5.65 9.23 6.21
45 New York United States 9.70 7.45 3.48 7.53 2.45 9.03 5.76 1.60 4.83 2.54 8.13 9.40 3.10 9.03 9.92 3.70 6.33 10.00 6.97 6.18 8.65 7.15 6.71
46 München (Munich) Germany 6.63 9.33 4.98 3.70 5.73 10.00 9.92 4.38 7.53 7.69 2.13 8.50 4.90 3.03 8.91 4.08 5.95 4.68 6.45 5.65 6.33 9.23 6.36
47 Düsseldorf Germany 5.35 7.75 7.98 3.70 5.73 10.00 9.92 5.05 7.53 8.00 1.75 1.38 7.30 7.00 7.05 7.00 9.33 4.30 6.45 5.65 7.83 6.46 6.63
48 Västerås Sweden 1.23 3.18 7.98 4.60 8.93 5.05 8.71 9.93 10.00 9.00 9.03 4.53 9.93 7.98 2.55 9.25 9.70 1.98 8.03 7.75 9.18 6.46 6.78
49 Washington, DC United States 6.25 8.58 5.73 1.00 2.45 9.03 5.76 2.58 4.83 3.62 9.70 9.78 8.28 9.85 9.38 3.55 6.03 9.10 6.97 6.18 8.80 6.46 6.86
50 Bayreuth Germany 1.08 1.68 7.23 3.70 5.73 10.00 9.92 4.83 7.53 7.69 7.75 2.58 5.95 7.30 7.05 2.13 2.65 1.23 6.45 5.65 9.25 3.38 5.67
51 Hannover Germany 2.95 7.15 5.73 3.70 5.73 10.00 9.92 5.20 7.53 7.15 7.53 6.10 8.35 4.83 7.05 4.53 6.85 2.95 6.45 5.65 8.20 3.00 6.48
52 Köln (Cologne) Germany 6.78 8.65 3.78 3.70 5.73 10.00 9.92 4.60 7.53 8.00 1.98 1.60 5.65 9.10 8.14 6.48 9.03 4.53 6.45 5.65 7.90 3.00 6.60
53 Vienna Austria 8.50 8.50 4.60 7.30 9.54 5.95 10.00 5.65 7.98 8.54 1.98 7.83 3.85 5.50 7.05 8.95 8.13 7.08 10.00 7.45 8.58 9.23 6.69
54 Frankfurt am Main Germany 5.20 8.05 6.33 3.70 5.73 10.00 9.92 4.75 7.53 8.38 1.60 5.35 6.55 8.43 8.99 3.18 4.60 5.50 6.45 5.65 6.85 9.23 6.46
55 Oslo Norway 9.10 7.08 4.98 7.90 9.92 1.75 8.18 5.80 9.70 8.15 7.38 7.38 5.58 2.43 3.87 9.85 9.48 5.05 9.17 9.10 9.55 9.23 6.84
56 Philadelphia United States 4.60 5.65 8.73 8.13 2.45 9.03 5.76 2.13 4.83 2.92 6.25 9.33 5.28 9.70 8.45 5.43 8.50 6.25 6.97 6.18 9.40 3.00 6.61
57 Chicago United States 9.48 4.98 7.23 9.03 2.45 9.03 5.76 1.90 4.83 3.46 5.20 10.00 4.15 9.40 9.46 4.83 7.60 9.63 6.97 6.18 9.33 3.00 6.95
58 Dubai United Arab Emirates 9.18 5.73 5.73 8.05 1.15 2.35 2.59 1.15 1.38 1.38 4.30 3.25 1.53 1.38 3.09 7.08 2.50 8.65 9.32 2.13 6.25 9.54 4.32
59 Trondheim Norway 6.18 4.30 9.48 7.90 9.92 1.75 8.18 6.25 9.70 7.54 8.73 4.53 9.25 3.78 1.78 9.40 8.05 2.35 9.17 9.10 9.70 3.00 6.70
60 Helsingborg Sweden 1.38 3.48 7.98 4.60 8.93 5.05 8.71 10.00 10.00 8.85 9.10 2.05 10.00 9.93 2.55 4.75 4.45 2.05 8.03 7.75 8.73 7.15 6.39
61 Ottawa Canada 9.55 5.20 6.33 7.30 9.24 4.38 3.80 1.98 5.43 7.00 6.18 9.70 5.13 6.55 3.17 7.00 4.90 4.98 7.28 9.93 5.58 9.54 6.25
62 Perth Australia 7.38 1.23 6.63 9.70 2.75 6.33 4.18 1.30 3.18 9.31 3.33 3.25 3.48 6.93 2.71 4.98 1.53 5.58 4.93 9.63 7.15 6.46 4.98
63 Dublin Ireland 5.50 5.95 1.60 5.05 4.81 6.03 7.20 3.85 8.20 5.23 1.15 4.60 6.48 8.65 8.14 2.80 4.68 6.33 9.92 7.38 8.28 6.69 5.45
64 Stavanger Norway 1.53 4.45 7.98 7.90 9.92 1.75 8.18 6.63 9.70 7.31 7.98 4.53 9.85 4.45 1.78 10.00 9.78 2.20 9.17 9.10 10.00 3.00 6.42
65 Manama Bahrain 1.00 2.35 9.48 2.28 1.00 1.00 2.13 2.05 1.08 6.31 7.60 4.53 8.73 1.75 1.00 1.30 1.38 3.85 7.58 1.00 6.55 0.00 3.47
66 Aarhus Denmark 2.65 3.33 8.73 2.88 8.47 6.78 8.18 6.10 8.58 9.62 6.70 2.28 7.83 7.60 1.31 6.10 5.05 3.25 9.70 7.15 7.23 6.46 5.93
67 Los Angeles United States 9.93 7.38 1.38 9.40 2.45 9.03 5.76 1.83 4.83 2.85 4.53 3.48 4.08 9.48 9.84 5.28 7.98 9.93 6.97 6.18 8.95 9.23 6.59
68 Stuttgart Germany 7.45 8.28 3.78 3.70 5.73 10.00 9.92 5.13 7.53 8.31 1.75 4.90 7.23 5.65 8.91 3.78 5.65 4.00 6.45 5.65 7.68 6.46 6.53
69 Auckland New Zealand 7.68 4.15 2.88 9.85 9.62 2.88 3.87 2.80 7.68 5.46 5.35 9.33 2.95 4.23 2.01 9.03 8.20 8.35 5.31 9.18 3.33 6.46 5.52
70 Bergen Norway 8.13 6.18 9.63 7.90 9.92 1.75 8.18 6.10 9.70 7.54 8.65 5.50 7.98 6.85 1.78 9.70 8.73 3.10 9.17 9.10 9.93 6.46 7.06
71 Espoo Finland 2.88 5.80 9.63 6.70 7.86 3.63 5.24 4.53 9.33 5.00 8.95 2.05 8.13 8.05 7.05 7.38 6.18 2.28 8.87 8.73 5.95 6.46 5.96
72 Madrid Spain 7.98 8.20 7.53 5.05 6.03 5.73 5.24 7.23 2.88 7.08 5.13 6.48 1.90 5.43 7.05 7.90 9.63 8.95 5.08 2.73 2.50 6.46 5.74
73 Osaka Japan 8.28 8.95 7.23 9.03 3.97 8.50 3.42 4.15 6.55 2.46 7.00 6.18 3.78 2.05 1.47 1.90 3.63 7.45 1.76 9.33 4.98 9.23 5.44
74 Barcelona Spain 5.65 6.93 4.60 5.05 6.03 5.73 5.24 7.30 2.88 6.62 4.53 1.15 2.13 5.35 8.91 2.35 3.18 6.03 5.08 2.73 2.05 10.00 4.60
75 Abu Dhabi United Arab Emirates 6.40 4.90 9.03 8.58 1.15 2.35 2.59 1.53 1.38 1.08 7.15 7.68 3.63 4.90 2.16 5.65 1.98 4.60 9.32 2.13 6.18 9.54 4.55
76 Birmingham United Kingdom 3.03 6.33 7.23 6.70 4.74 9.25 7.50 6.18 5.73 2.62 1.53 5.80 5.73 9.63 8.29 3.25 5.20 3.55 5.54 4.53 4.08 3.00 5.49
77 Bochum Germany 1.75 1.75 8.95 3.70 5.73 10.00 9.92 5.43 7.53 8.00 5.58 1.00 9.55 8.35 7.05 5.20 7.38 1.90 6.45 5.65 9.10 6.46 6.34
78 Taipei Taiwan 8.05 1.60 2.35 10.00 1.61 4.08 9.17 2.95 6.55 5.92 7.45 9.63 2.50 5.13 3.56 9.18 8.28 6.70 7.35 7.30 9.03 9.23 5.78
79 Doha Qatar 1.15 1.53 6.33 4.60 1.00 2.58 1.53 1.23 1.45 1.00 2.20 6.55 3.70 1.15 1.00 5.73 1.90 4.75 8.11 2.95 9.85 0.00 3.32
80 Lyon France 8.95 6.48 5.73 5.65 3.82 8.35 6.29 8.50 6.55 5.08 6.33 9.03 8.43 6.70 8.14 8.80 9.40 4.23 3.65 6.70 4.38 3.00 6.81
81 Milan Italy 6.55 8.13 4.98 2.28 6.87 7.83 7.20 7.15 4.30 5.62 1.83 6.63 4.68 2.35 7.05 7.30 6.93 7.53 4.63 3.93 3.48 9.23 5.41
82 Adelaide Australia 5.73 3.25 6.63 9.70 2.75 6.33 4.18 1.38 3.18 9.54 3.48 2.43 4.60 4.00 2.71 6.40 2.35 2.73 4.93 9.63 7.30 9.23 4.87
83 Brussels Belgium 4.68 7.00 2.88 4.68 4.20 5.88 9.02 4.90 5.05 8.92 1.00 9.18 4.30 4.75 7.05 8.58 7.08 7.68 5.16 4.23 5.50 6.69 5.34
84 Daejeon South Korea 4.30 7.98 8.73 9.85 1.38 5.28 8.71 2.88 6.78 6.08 3.03 1.08 4.38 2.50 1.00 9.48 9.85 7.75 7.58 4.68 3.85 6.46 5.38
85 Lisbon Portugal 5.80 5.58 3.25 4.00 7.94 1.45 2.97 9.78 3.48 2.31 6.55 3.40 7.53 6.18 7.05 3.18 4.15 4.90 3.72 4.83 2.43 6.46 4.76
86 Leeds United Kingdom 4.90 4.00 7.23 6.70 4.74 9.25 7.50 6.40 5.73 3.08 6.85 2.35 6.03 7.83 7.13 6.03 8.65 3.78 5.54 4.53 5.13 3.00 5.85
87 Ljubljana Slovenia 3.40 4.83 9.85 2.35 4.97 1.83 4.25 6.70 7.83 3.46 1.30 7.75 8.20 4.60 7.05 7.23 7.75 5.80 2.36 4.15 3.40 6.46 4.92
88 Tampere Finland 4.83 1.98 9.85 6.70 7.86 3.63 5.24 4.68 9.33 4.54 9.78 7.08 8.95 9.25 7.05 4.60 2.80 3.33 8.87 8.73 6.48 3.00 6.13
89 Hong Kong China 9.40 1.00 3.25 7.38 4.51 1.23 7.28 5.50 3.48 1.15 4.23 7.90 2.43 4.30 7.75 2.58 3.33 8.80 2.21 1.98 3.78 9.23 4.69
90 Turin Italy 1.90 5.35 7.53 2.28 6.87 7.83 7.20 7.45 4.30 6.08 2.05 7.53 5.50 4.68 7.05 5.13 4.00 4.45 4.63 3.93 4.68 7.15 4.99
91 Reykjavik Iceland 3.85 2.50 4.23 8.43 10.00 1.08 3.50 7.00 9.40 8.00 6.78 4.53 9.40 7.53 8.91 9.78 9.93 3.40 5.31 4.75 8.05 9.23 6.06
92 Rome Italy 8.73 8.35 2.35 2.28 6.87 7.83 7.20 6.93 4.30 5.92 1.38 9.10 2.65 5.20 7.05 2.58 1.68 7.60 4.63 3.93 3.55 1.00 5.13
93 Prague Czech Republic 7.83 6.78 6.33 5.65 1.84 2.80 2.82 3.10 5.80 1.85 3.85 7.68 4.45 5.28 3.25 6.18 3.85 8.50 3.12 4.90 2.80 6.46 4.56
94 Vilnius Lithuania 4.38 7.68 6.33 2.95 6.95 2.65 1.91 9.03 5.50 2.15 6.48 2.65 5.88 3.18 7.05 6.85 5.58 4.83 2.36 2.20 3.18 3.00 4.52
95 Marseille France 7.60 4.60 2.35 5.65 3.82 8.35 6.29 7.90 6.55 4.31 2.73 1.45 6.18 3.63 8.91 5.05 4.83 3.93 3.65 6.70 4.90 6.46 5.39
96 Riga Latvia 4.08 3.10 8.73 6.78 8.02 1.98 2.29 9.18 7.90 3.08 8.50 2.80 4.75 4.38 9.22 2.88 2.95 6.55 2.44 4.30 2.88 3.00 4.72
97 Tallinn Estonia 2.50 3.85 4.30 8.43 2.91 1.38 3.12 3.03 7.83 4.08 9.93 8.13 6.25 6.03 8.14 6.25 6.48 5.65 2.66 7.83 3.03 9.54 4.92
98 Moscow Russia 9.03 9.48 1.45 1.15 4.13 4.00 2.06 2.28 2.50 1.54 9.25 6.33 1.08 1.23 9.07 1.68 2.28 9.70 2.59 4.08 1.68 6.54 4.16
99 Panama City Panama 1.98 1.30 5.73 7.30 8.09 4.45 5.24 9.63 1.60 8.23 2.50 8.73 3.33 1.08 1.00 2.28 3.93 5.20 1.08 1.60 1.60 6.46 3.78
100 Budapest Hungary 8.20 7.30 8.88 3.93 1.76 2.13 3.42 8.43 2.73 3.77 4.08 8.35 2.80 2.88 1.54 9.63 9.55 7.98 1.98 3.10 2.58 9.23 4.82
101 Sao Paulo Brazil 8.43 5.43 4.98 1.15 9.39 5.58 1.53 8.20 2.65 8.62 3.63 6.03 1.23 2.20 7.36 1.38 1.30 8.43 1.38 1.53 1.38 3.38 4.47
102 Beijing China 8.65 9.40 1.30 9.03 4.51 5.43 1.83 5.35 3.48 1.00 2.80 5.28 1.75 3.93 8.37 3.63 4.98 9.25 2.21 1.98 1.00 3.00 4.69
103 Bratislava Slovakia 4.23 3.03 7.53 2.43 4.28 1.90 2.29 7.08 6.63 2.85 5.88 7.23 7.08 2.73 7.05 6.70 7.53 5.35 1.91 2.43 2.73 9.23 4.55
104 Naples Italy 1.30 1.45 4.23 2.28 6.87 7.83 7.20 7.38 4.30 5.54 4.75 1.30 5.35 1.90 7.05 5.80 5.13 3.70 4.63 3.93 4.15 3.38 4.38
105 Kuala Lumpur Malaysia 5.43 4.53 3.78 7.60 1.69 2.20 1.00 4.45 2.13 8.77 3.55 7.15 3.18 3.55 2.24 1.45 1.60 8.28 3.04 8.80 2.95 6.46 4.03
106 Shanghai China 8.88 9.85 1.90 9.10 4.51 5.43 1.61 5.28 3.48 1.00 2.43 5.28 1.38 5.88 7.21 2.65 3.55 8.20 2.21 1.98 1.08 9.23 4.60
107 Rio de Janeiro Brazil 5.28 4.38 1.15 2.28 9.39 5.58 1.53 8.58 2.65 6.69 4.90 5.95 1.68 1.30 3.41 1.53 1.75 9.18 1.38 1.53 1.30 6.46 3.94
108 Bucharest Romania 4.45 3.78 1.08 4.60 7.10 2.50 1.53 8.35 4.98 1.23 4.08 8.28 2.88 2.28 1.85 2.43 3.78 7.23 2.82 2.88 2.13 3.00 3.71
109 St Petersburg Russia 5.58 6.25 1.90 4.60 4.13 4.00 2.06 2.65 2.50 1.46 4.60 2.88 2.20 1.83 7.44 4.15 6.63 9.33 2.59 4.08 2.35 6.46 3.94
110 Warsaw Poland 7.30 6.63 3.03 3.78 2.83 3.85 3.42 4.98 5.13 2.31 1.53 8.65 3.93 3.85 3.79 3.93 6.10 6.85 3.04 3.03 2.20 3.38 4.26
111 New Delhi India 4.53 9.10 1.90 9.40 3.21 4.60 1.53 8.73 1.23 3.54 3.40 1.53 1.00 3.10 2.94 2.73 4.08 6.48 1.00 2.58 1.45 9.23 3.76
112 Athens Greece 6.70 4.75 3.03 2.88 4.89 2.50 2.89 6.78 2.20 4.92 1.23 2.95 5.80 1.60 7.05 3.40 1.23 9.48 2.89 1.30 3.10 6.46 3.95
113 Cape Town South Africa 5.95 5.28 3.48 4.83 1.38 1.30 2.44 5.58 1.00 6.23 4.38 3.10 6.33 3.33 2.32 1.00 1.08 6.40 1.23 1.08 1.15 9.23 3.46
114 Mumbai India 3.55 9.18 1.30 9.03 3.21 4.60 1.53 8.88 1.23 3.23 2.28 3.03 1.45 3.70 2.94 1.23 1.45 5.95 1.00 2.58 1.23 9.23 3.52
115 Sofia Bulgaria 5.05 3.70 5.73 2.28 3.29 1.15 1.00 6.48 2.35 2.08 8.13 8.05 4.00 4.53 8.91 8.80 5.43 7.00 1.45 2.80 1.75 3.00 4.24
116 Santiago Chile 3.63 3.93 1.60 4.60 7.03 2.05 1.08 7.75 1.83 1.62 2.35 5.65 1.83 4.15 4.03 1.83 2.73 6.63 2.74 2.28 1.98 6.46 3.27
117 Buenos Aires Argentina 1.60 3.55 1.68 8.05 5.88 3.78 2.44 5.95 1.90 8.46 9.63 5.05 2.58 2.58 3.02 1.15 1.15 7.15 1.83 1.38 2.28 6.46 3.60
118 Medellin Colombia 2.73 1.15 7.23 8.73 9.47 3.70 3.12 9.55 2.05 1.77 4.68 3.55 3.25 1.45 2.78 1.08 1.00 3.63 1.15 1.15 1.53 6.46 3.45
119 Monterrey Mexico 7.75 1.38 2.88 8.65 3.06 4.75 1.76 8.65 1.75 1.31 2.88 4.75 4.98 1.68 2.09 1.98 2.20 7.83 1.61 1.75 1.83 6.46 3.77
120 Riyadh Saudi Arabia 5.13 1.08 6.63 2.28 1.00 2.73 2.66 1.68 1.53 1.00 2.58 1.75 1.30 1.00 1.93 1.60 1.83 7.38 3.80 1.23 5.73 9.23 2.76
121 Mexico City Mexico 9.33 4.08 1.00 6.70 3.06 4.75 1.76 7.60 1.75 2.00 6.10 5.73 2.05 2.95 4.18 3.40 4.23 9.40 1.61 1.75 1.90 6.46 4.11

METHODOLOGY

We researched 500 cities worldwide with medium to high positions in the UN Human Development Index. The cities also rank on the UN prosperity list and the European Commission’s Digital City Index. We aimed to cover a wide range of regions, and prioritised capitals and financial centres.

We analysed the cities for 24 factors that determine a smart city, and then ranked the top 100. While the cities at the top of the index deserve praise, those at the bottom should also be given credit as emerging urban spaces making impressive strides towards integrated information networks.

We collected granular level data across a range of criteria: Transport and Mobility, Sustainability, Governance, Innovation Economy, Digitalisation, Cyber Security, Living Standard and Expert Perception.

Each factor is scored from 1 – 10, the higher the score, the better. Below you can find a description of how each factor was researched.

Smart Parking

  • Percentage of people owning cars (city). Source: local census reports, Eurostat NUTS 2 statistical level data
  • Number of parking spaces in city center per klm2
  • Smartphone penetration. Sources: local reports, online databases
  • Availability of parking apps and usage penetration


Car Sharing Services

  • Estimation of the car sharing industry fleet (number of cars) in the city with respect to the city’s population. Sources: local reports, official sites of car2Go, GoGet, Zipcar, DriveNow, Communauto, Car4away, Autonapůl, LetsGo, GreenMobility, Autolib’, GoCar, Enjoy, XXImo, Bluemove, Sunfleet, Mobility Carsharing and Flinkster.
  • Population data from Google


Traffic

  • Levels of congestion. Sources:TomTom Traffic index, INRIX traffic scorecard (adjusted to TomTom), Google traffic (adjusted to TomTom).


Public Transport

  • Public transport satisfaction percentage. Sources: local reports, European Commission report


Clean Energy

  • Percentage of electricity production from renewable sources. Source: International Energy Statistics report


Smart Building

  • Research centers: Investment to research and development (percentage of GDP). Source: Global Innovation Index 2017 (report)
  • Efficiency of buildings: GDP per unit of energy use. Source: Global Innovation Index 2017 (report)


Waste Disposal

  • Percentage of waste landfilled. Sources: local reports, United Nations


Environment Protection

  • Green House Gases emission per capita. Source: United Nations
  • CO2 Emissions per capita. Source: United Nations.
  • Adjusted to population. Source: Population data from Google.


Citizen Participation

  • Election turnout for parliament (for Hong Kong latest local elections), percentage. Source: International Institute for Democracy and Electoral Assistance. Where no parliament exists, local elections participation rate was used.


Digitalization of Government

  • Digital Infrastructure Rank. Source: Digital City Index (supported by the European Commision)
  • Traffic of local government sites as a percentage of the population.


Urban Planning

  • Rank according to percentage of green public areas in the city. Source: Data from city records and satellite data (Google)


Education

  • PCs per 1000 population. Source: Online databases and local reports.
  • Information technologies development index (Measuring the Information Society Report). Source: International Telecommunications Union
  • Number of universities the country has in the top university list, country level. Source: World University Rankings 2016
  • Number of universities in the top 10 list, city level. Source: World University Rankings 2016 
  • Number of students in top 3 universities from the list, city level. Source: World University Rankings 2016
  • Adjusted to city population, country population (data from Google)


Business Ecosystem

  • Source: Global Innovation Index
  • Number of startups as registered on Angel.co
  • Adjusted to population (Google)


4G LTE

  • Mbs, Speed Test Global Index (mobile). Source: Online Speed Test


Internet Speed

  • Download Mbs, Speed Test Global Index (fixed broadband). Source: Online Speed Test Global Index
  • Download Mbs, Source: Ookla
  • Download Mbs, Source: Publicly available data from the Digital City Index


Wi-Fi Hotspots

  • Free Wi-Fi hotspots (estimate) Sources: Online Wi-Fi databases
  • Adjusted to the city area (from Google).


Smartphone Penetration

  • Smartphone penetration (country). Source: local reports, online databases


Living Standard

  • Average sum spent on (Fast food, Restaurant, Clothes, Rent, Transportation). Source: Expanistan
  • Average Net Salary. Source: Average salary survey data
  • Adjusted to the GDP per capita levels. Source: World Bank Data


Expert Perception

  • 20,000 technology and urban planning journalists were asked to rate how smart each city was. Source: poll, only on top 100 cities.