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SIS Scientific Meeting 2014
Cagliari Jun 11,13
Staying On The Smart Side.
Measuring The Smart Communities
Mariagrazia Dotoli, Vincenzo Patruno, Luigi Ranieri, Aldo Scarnera
A Smart City enable us to monitor,
understand, analyze, and plan the
city improving efficiency, reducing
costs, generate savings, improving
equity and quality of life for its
citizens
City Indicators
Decision support tool for policy makers (to
define city policies)
Better communicate city performance to city
users (citizens, visitors) and potential
investors
Measuring the smartness
of a city
is a complex issue. There does not exist
a set of indicators for measuring the
performance of a city that is valid in each
context and for each purpose
A harmonized approach is preferable and
encouraged so that an effective comparison
is allowed on a national or international
basis
today no universal rule exists in the choice
of an appropriate set of indicators, neither a
methodological taxonomy and classification
has occurred so far
but
http://www.smart-cities.eu/download/smart_cities_final_report.pdf
Es: Green spaces per person (m²)
http://www.icitylab.it/
Cc-by 2014 Vincenzo Patruno
Cc-by 2014 Vincenzo Patruno
Poetto, CA - Cc-by 2014 Vincenzo Patruno
The idea is to propose a novel conceptual
framework for smart city indicators
classification, which puts both the human
perspective and the technological content at
the heart of the classification and selection
process
Objective
refers to indicators which look at the city
physical infrastructure
(e.g. public transport network capillarity), urban assets (e.g.
green space share) and conditions of the general context (e.g.
air quality).
includes indicators which tend to measure
the citizens satisfaction and well-being.
The subjective indicators represent a useful
addition and complement to the objective
ones.
(Es: satisfaction with quality of schools, satisfaction with
transparency of bureaucracy. )
Subjective
The importance of the subjective indicators
is to allow to achieve a more complete and
articulated vision of the measured system
than by the single use of objective
indicators
http://www.smart-cities.eu/download/smart_cities_final_report.pdf
Cinema attendance
per inhabitant;
Museums visits per
inhabitant;
Theatre attendance
per inhabitant.
Smart Living:
Satisfaction with quality
of health system;
Satisfaction with
personal housing
situation;
Satisfaction with access
to educational system;
Satisfaction with quality
of educational system.
The framework is being tested as a tool for
developing indicators to monitor the smart city
initiatives in the municipality of Bari (Italy).
@vincpatruno
vincenzo.patruno@istat.it
Aggràssias!
1. traditional tools: indicators are computed by analysis and
manipulation of the observed variables and data in a
traditional repository;
2. innovative tools based on data sensing and mining of
physical infrastructure: indicators computation is based on
the collection and analytics of machine-sensed data (e.g.
smart grid energy consumption through power meter);
3. innovative tools based on data sensing and mining of
social infrastructure: indicators are computed collecting
the digital footprints and applying to them complex
analytics as knowledge discovery and data mining (e.g.,
service satisfaction level deduced from social networks).

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Staying on the Smart Side. Measuring the Smart Communities

  • 1. SIS Scientific Meeting 2014 Cagliari Jun 11,13 Staying On The Smart Side. Measuring The Smart Communities Mariagrazia Dotoli, Vincenzo Patruno, Luigi Ranieri, Aldo Scarnera
  • 2. A Smart City enable us to monitor, understand, analyze, and plan the city improving efficiency, reducing costs, generate savings, improving equity and quality of life for its citizens
  • 3. City Indicators Decision support tool for policy makers (to define city policies) Better communicate city performance to city users (citizens, visitors) and potential investors
  • 4. Measuring the smartness of a city is a complex issue. There does not exist a set of indicators for measuring the performance of a city that is valid in each context and for each purpose
  • 5. A harmonized approach is preferable and encouraged so that an effective comparison is allowed on a national or international basis today no universal rule exists in the choice of an appropriate set of indicators, neither a methodological taxonomy and classification has occurred so far but http://www.smart-cities.eu/download/smart_cities_final_report.pdf
  • 6. Es: Green spaces per person (m²) http://www.icitylab.it/
  • 9. Poetto, CA - Cc-by 2014 Vincenzo Patruno
  • 10. The idea is to propose a novel conceptual framework for smart city indicators classification, which puts both the human perspective and the technological content at the heart of the classification and selection process
  • 11. Objective refers to indicators which look at the city physical infrastructure (e.g. public transport network capillarity), urban assets (e.g. green space share) and conditions of the general context (e.g. air quality).
  • 12. includes indicators which tend to measure the citizens satisfaction and well-being. The subjective indicators represent a useful addition and complement to the objective ones. (Es: satisfaction with quality of schools, satisfaction with transparency of bureaucracy. ) Subjective
  • 13. The importance of the subjective indicators is to allow to achieve a more complete and articulated vision of the measured system than by the single use of objective indicators
  • 15. Cinema attendance per inhabitant; Museums visits per inhabitant; Theatre attendance per inhabitant. Smart Living: Satisfaction with quality of health system; Satisfaction with personal housing situation; Satisfaction with access to educational system; Satisfaction with quality of educational system.
  • 16. The framework is being tested as a tool for developing indicators to monitor the smart city initiatives in the municipality of Bari (Italy).
  • 18. 1. traditional tools: indicators are computed by analysis and manipulation of the observed variables and data in a traditional repository; 2. innovative tools based on data sensing and mining of physical infrastructure: indicators computation is based on the collection and analytics of machine-sensed data (e.g. smart grid energy consumption through power meter); 3. innovative tools based on data sensing and mining of social infrastructure: indicators are computed collecting the digital footprints and applying to them complex analytics as knowledge discovery and data mining (e.g., service satisfaction level deduced from social networks).