Easy Park

Smart City Index 2018


In EasyPark, crediamo nell'utilizzo che la tecnologia per possa creare città efficienti e intuitive. Sappiamo che una rete integrata di trasporto e comunicazione consente di risparmiare tempo, energia e denaro. La digitalizzazione non si limita ad aggiornare le città: migliora la qualità della vita.

Le sfide affrontate dalle città stanno cambiando rapidamente. Non sono solo più complessi, ma specifici per ogni luogo. Ecco perché in EasyPark abbiamo creato Smart Cities Index 2018. Con nuovi criteri e risultati aggiornati, l'indice fornisce dati dettagliati su abitudini comportamentali e investimenti governativi da città di tutto il mondo. Dal numero di stazioni di ricarica elettriche, alla frequenza delle transazioni di Bitcoin: questi sono i risultati più complessi e precisi di EasyPark fino ad oggi.

La definizione di una città intelligente è in continua evoluzione mentre emergono scoperte che migliorano il nostro tenore di vita. Con questo in mente, nell'indice di quest'anno abbiamo incluso: Fornitura di Smart Parking, tasso di riciclaggio, investimenti infrastrutturali, stazioni di ricarica elettriche, addebito elettronico, ecosistema Business e Blockchain, sicurezza informatica e indice di sostenibilità nella nostra definizione di ciò che costituisce una città intelligente .

Per la seconda edizione di questo studio, abbiamo analizzato 500 città in tutto il mondo per un totale di 24 fattori e stilato la classifica delle prime 100 per determinare le città che gestiscono le loro risorse e investimenti in modo più efficiente.

"Sempre più persone migrano verso le città - 3 milioni di persone a settimana - questo pone sfide che solo la tecnologia può affrontare. Una delle più grandi cause di congestione del traffico è la gente che guida alla ricerca di spazi di parcheggio. In EasyPark, le nostre soluzioni di parcheggio intelligenti semplificano la vita in città", afferma Johan Birgersson, CEO di EasyPark Group.

Lo Smart Cities Index 2018 è un'analisi ancora più sofisticata degli spazi più tecnologici al mondo. Offre una chiara ripartizione da città a città degli indicatori chiave che definiscono una città intelligente, tra cui il numero di hotspot WiFi, edifici intelligenti e, ovviamente, parcheggio intelligente. E mentre alcuni paesi continuano a avere perfomance sopra la media, è chiaro che molti altri hanno fatto passi significativi per creare luoghi di vita più sani, più puliti e più efficienti.

  •  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.