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The Indian perspective of smart cities

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Smart City Symposium Prague 2017
The Indian Perspective of Smart Cities
Khushboo GUPTA and Ralph P. HALL
Abstract—Cities have been the engines of economic growth
since the industrial revolution. While effective at catalyzing pros-
perity, city development has not always been “smart” sacrificing
human health, for instance, for greater productivity. Smart cities
are now emerging. Leading smart cities such as Stockholm,
Barcelona, New York, Vienna, and Toronto have incorporated
efficiency into buildings, infrastructure, and social spaces using
technological advancements, increasing the livability, workability,
and sustainability of these places. Inspired by these smart city
developments, India is planning to build 100 smart cities in
various parts of the country. This research presents insight into
how smart cities are likely to evolve in India, by studying the
priority areas considered in planning smart cities. It presents
both the citizen and city official perspectives of smart cities. The
results indicate that citizens value living, followed by mobility,
environment, governance, and economy, whereas the city officials
prioritize living, followed by environment, economy, mobility, and
governance. This research further evaluated the titles of planned
smart city projects to determine how many of them can be
categorized as smart. The analysis also revealed how city size
influences the priorities of citizens and city officials, indicating
that the notion of a smart city in India may be context specific.
Index Terms—Smart City, Smart Cities Mission, People’s
Perspective, Smart City Characteristics
I. INTRODUCTION
INDIA is amongst the many developing countries witness-
ing a rapid rural to urban shift. This change is reflected
by the greater decadal growth of the urban versus rural pop-
ulation. The urban population in India increased from around
27.8% (286 million) in 2001 to 31.2% (377 million) in 2011
[1] and is estimated to grow to 40% by 2030 and more than
50% by 2050. The population growth in cities is accompanied
by infrastructure management and service delivery challenges.
The development of smart cities is one strategy being deployed
to efficiently and effectively cope with these challenges [2].
India’s Smart Cities Mission (SCM) is a national initiative
by the Ministry of Urban Development (MoUD) to build a
foundation for 100 smart cities in five years (FY 2015-16 to
FY 2019-20) [3]. However, the SCM does not specify the
specific characteristics that need to be included in a “ smart”
city. This research explores the concept of a smart city and
focuses on how Indian cities are defining smart cities as part
of the SCM.
The paper begins by providing an overview of the SCM
in India. The available information from the SCM is then
Manuscript received February 28, 2017.
K. Gupta is a Ph.D. student with the School of Public and International
Affairs, Virginia Tech, 112 Architecture Annex, 140 Otey St NW, Blacksburg,
VA 24060 USA (e-mail: khushboo@vt.edu).
Dr. R. P. Hall is an Associate Professor with the School of Public and
International Affairs, Virginia Tech, 201 Architecture Annex, 140 Otey St
NW, Blacksburg, VA 24060 USA (e-mail: rphall@vt.edu).
analyzed to identify how citizens and city leadership define a
smart city in India. Further, the titles of the planned city-level
projects are analyzed to assess how many can be considered
as smart. The paper concludes by summarizing the priority
areas specific to various city clusters, which are based on
the population and characteristics associated with envisioning
smart cities in India.
II. SM ART CITIES MISSION IN IND IA
The SCM is the first significant step towards the compre-
hensive implementation of the smart city concept in India.
The MoUD defines a smart city as “building and promoting
cities that provide core infrastructure and give a decent quality
of life to its citizens, a clean and sustainable environment,
and the application of “smart” solutions.” The SCM views
a smart city as doing more with less, building upon existing
infrastructural assets and resources, and proposing resource
efficient initiatives. The mission has further defined smartness
in terms of both physical and non-physical assets such as
water supply, waste management, energy sources and supply,
safety, citizen participation, economy and employment, and
education. The MoUD initiated the SCM through the India
Smart Cities Challenge. To take part in this challenge, Indian
cities competed for central government funding by submit-
ting a smart city proposal (SCP). On an average, each city
selected will receive USD 15.03 million per year from the
central government to spend on smart city development. An
equal amount of matching funds will be contributed by the
State/Urban Local Body (ULB); therefore, nearly USD 15,031
million of Government and ULB funds will be available for
smart city development.
The SCM’ s purpose is to drive economic growth and
improve the quality of life of people by enabling local area
development that has three components [3]: (a) Area-based
development (ABD) that will transform existing areas, in-
cluding slums, into better planned ones, by retrofitting and
redevelopment thereby improving livability of the whole city;
(b) Green-field projects that will develop new areas in the city
in order to accommodate the expanding population in urban
areas; and (c) Pan-city development (PAN) that envisages the
application of selected smart solutions to existing city-wide
infrastructure.
As of now, 60 cities (from the list of 100 proposed smart
cities) have been shortlisted in the SCM and provided with
initial funding for SCP implementation. More than half of the
shortlisted cities are located in the states of Uttar Pradesh (13),
Tamil Nadu (12), and Maharashtra (10). A special purpose
vehicle has been established in these 60 cities to monitor the
progress of the mission at the city level [3].
The next section provides the methodology used to under-
stand the Indian perspective of smart cities.
Smart City Symposium Prague 2017
TABLE I: DESCRIPTION OF SMART CHARACTERISTICS (BLUE ROWS) AND PHRASES/KEYWORDS FROM THE
VISION STATEMENTS DEFINING THOSE CHARACTERISTICS (WHITE ROWS)
Characteristics Phrases/Keywords
Living Cultural Facilities, Health Conditions, Individual Safety, Housing Quality, Education Facilities, Touristic Attractivity, and Social
Cohesion
Quality of Life, Improving/Enhancing Physical Infrastructure, Livable, World Class Infrastructure, Solving Core Infrastructure, Heritage,
and Tourism Development
Mobility Local Accessibility, (Inter-)national Accessibility, Availability of ICT-Infrastructure, and Sustainable, Innovative, and Safe Transport
Systems
Mobility, Improving/Enhancing Physical Infrastructure, Livable, world Class Infrastructure, Connectivity, Transit oriented, Solving Core
Infrastructure, and Internet Connectivity
Environment Attractivity of Natural Conditions, Pollution, Environmental Protection, and Sustainable Resource Management
Sustainable, Eco-friendly, Environment friendly, Protecting Ecology, Green, Clean, Healthy Environment, Ecological Integration, and
Pollution Reduction Measures
Economy Innovative Spirit, Entrepreneurship, Economic Image and Trademarks, Productivity, Flexibility of Labor Market, International
Embeddedness, and Ability to Transform
Economic Development, Economic and/or Regional Center, Economic Vibrancy, Promoting Tourism and/or Leveraging Heritage and/or
Culture for Economic Enhancement, Financially Vibrant or Efficient, Investment in Opportunities for Youth, Entrepreneurship, and
Economic Prosperity
Governance Participation in Decision-making, Public and Social Services, Transparent Governance, and Political Strategies and Perspectives
Citizen Partnership, Participatory Decision Making, E-governance, Community Involvement, and ICT Enabled Government Services
Source:Blue Rows [4] and White Rows by Authors
III. METHODOLOGY
A city’ s vision and citizens’ priorities form an important
part in planning smart cities. Since each city has different
strengths and weakness, their respective routes to developing
a smart city are likely to vary. This research seeks to explore
these potential differences. The Indian perspective of a smart
city was obtained by analyzing three different data sources:
(1) a citizen survey, (2) smart city vision statements, and
(3) a list of planned smart city projects. The citizen survey
provides insight into the critical issues facing society, whereas
the vision statements provide insight into how city government
officials view smart cities in India. The cities considered
in this study were grouped into various clusters based on
their population (see Table IV in the Appendix) to study the
impact of population size on citizen’s priority and focus areas
expressed in the vision statements. As described in section II,
the objective of the SCM is to provide core infrastructure that
leverages smart solutions. To evaluate the extent of projects
that are likely to implement smart solutions, the titles of the
SCM projects were categorized. In summary, these three data
sets provide an understanding of citizen priorities, city officials
perspectives, and the smartness of planned projects.
A. Citizen surveys
The citizen survey data was obtained from the online smart
city forum [5], which was launched as a part of the SCM by the
Government of India to capture peoples’ views on smart city
development. Fifty-nine cities hosted a poll (prior to October
1, 2016) to obtain information on their citizens’ perspective of
priority areas for smart city development. The poll reflected the
city’s priority areas in terms of a percentage, so priority areas
with a higher percentage meant citizens were more concerned
with that area. The citizen responses were classified under five
out of six smart characteristics defined by Giffinger et al. [4],
namely Living, Mobility, Environment, Governance, People,
and Economy. This classification comprehensively presents
most of the elements that form a smart city. Giffinger et al.
[4] further assigned factors to these six smart characteristics
described in Table I (the Smart People category had to be
excluded due to a lack of information on this dimension).
The priority areas varied slightly as the on-line polls used by
the cities defined similar features using different terminology.
For example, some on-line polls used “ transportation” as
their priority area, while other cities captured transportation as
mobility” or “ connectivity. In this research, these priority
areas were grouped based on similar asset characteristics. For
example, phrases or keywords such as transportation, mobility,
or traffic management were all classified under the same
cluster entitled smart mobility.
Post categorization, the priority for all five smart charac-
teristics for each city cluster was calculated as the average
priority percentage of all cities grouped in each city cluster.
The classification of the priority areas under the five smart
characteristics was carried out manually and involved the
author’s judgment, which many be subject to personal bias.
Additionally, while the poll data does not represent the whole
population of a city, it does provide an indicator of the
preferred smart characteristics that connected citizens of the
city believe should be included in the vision of their smart
city.
B. City vision statements
The smart city vision statements were obtained from 60
smart city proposals available on the SCM’ s website (two
examples of city vision statements are provided in the Ap-
pendix). Semantic and Keyword analysis were used to analyze
the contents of the statements. Semantic content analysis is the
process of creating themes (categories) that identify the main
subjects and dimensions in the material under study, and the
Smart City Symposium Prague 2017
TABLE II: EFFECT OF POPULATION SIZE ON CITIZEN PRIORITIES (%)
No. of cities City cluster with population Living Mobility Environment Governance Economy
3Less than 100,000 42% 30% 12% 5% 11%
24 100,000-500,000 59% 24% 8% 5% 5%
14 500,000-1,000,000 50% 36% 6% 7% 1%
13 1,000,000-2,000,000 44% 33% 12% 8% 4%
5 2,000,000 and above 40% 40% 9% 4% 6%
59 Overall 51% 30% 9% 6% 4%
Source:Authors
specific sub-fields under these subjects and dimensions [6],
[7]. The smart city proposals were accessed over the Internet
and the vision statements were extracted for analysis. Semantic
analysis was used to identify the focus areas expressed in the
vision statements with respect to the five smart characteristics
described in Table I namely, Living, Mobility, Environment,
Economy, and Governance. The key phrases in each vision
statement were identified and then grouped under one of the
smart characteristics. The high occurrence of a characteristic
signals that city officials consider this characteristic to be a
high priority.
The extracted phrases from the vision statements were
manually assigned to the categories. The manual catego-
rization was necessary as certain vision statements used the
same keywords with reference to different aspects of a smart
city. For example, Belagavi city’s vision statement described
their smart city as culturally “ vibrant” while Kakinada used
vibrant” to describe the economy in their futuristic smart
city.
To validate the characteristics identified in the vision state-
ments using semantic analysis and to increase the reliability
of the study, another expert assisted in the process. A random
sample of 10 cities was selected to conduct the reliability
test. To increase coding reliability, the expert independently
coded the vision statements using the framework in Table 1.
Reliability (R) was calculated using the following formula [8]:
R=Agreement
Agreement +Disagreement ×100.(1)
To ensure the robustness of the method, reliability for
all five characteristics was conducted. The reliability for the
characteristics Mobility, Environment, and Governance was
100%, and 86% for Living and Economy. These results imply
that the data were coded reliably.
C. Assessment of ABD and PAN projects
An investigation was carried out to identify if there was an
alignment between the projects that will be implemented under
the SCM, the citizen’ s priorities, and vision statements. The
objective of this exercise was to categorize the SCM projects
based on smart characteristics (as explained in Section III-B).
A list of 329 projects to be undertaken by the 60 shortlisted
cities was obtained from the Smart Cities Missions website.
These 329 projects are each worth USD 15.03 million or more
and are categorized as ABD and PAN (described in Section II)
by MoUD. For this study, the project titles were also classified
as being smart or traditional based on the definition of smart
solutions given by the SCM. Project titles were searched
for keywords like “ smart, “ integrated,” “ intelligent, “ ICT-
enabled,” “ Environment/eco-friendly, and “ cost effective.
If a project’ s title reflected the use of a renewable energy
source or use of a new technology to reduce environmental
impacts, enhance productivity, save time, etc., the project was
categorized as smart.
IV. FINDINGS
A. Citizen perception of smart cities in India
The SCM tried to capture citizens’ aspirations in terms of
priority areas for smart city development.
The analysis of the citizen poll data revealed the citizens’
priority areas and how these varied by the size of a city.
Out of the five smart city characteristics shown previously
in Table I, 51% of the total sample voted for Smart Living.
Smart Mobility was the second priority domain selected by
30% of the total sample. The third priority domain was Smart
Environment (9%) that was followed by Smart Governance
(6%). The domain given the least priority was Smart Economy
(4%).
The citizen’ s perspective shows that the major focus is
on smart living and mobility. Decades of underinvestment
have left cities in India with dire deficits in these two crit-
ical domains, which include railways, roads, ports, airports,
telecommunications, and electricity generation. In the World
Economic Forum’ s Global Competitiveness Report for 2011-
2012, India ranked 89th out of 142 countries for its infras-
tructure. The report criticized its transport, ICT, and energy
infrastructure as “ largely insufficient and ill-adapted to the
needs of the growing population” [9]. Additionally, education
and health services suffer from poor service delivery, a lack of
quality choices, and a lack of access especially for the poor
due to a high dependence on relatively expensive privately
provided services [10]. The third priority domain based on
the citizen survey was Environment, though the gap between
Mobility and Environment is large. The growing population
fuels the exploitation of natural resources and creates high
levels of pollution, making the Environment a priority for
a smart city. The Economy and Governance domains are
typically given the lowest priority by citizens. The main reason
for this is likely to be a lack of awareness amongst citizens
about the importance of citizen participation and the emphasis
Smart City Symposium Prague 2017
TABLE III: EFFECT OF POPULATION SIZE ON FREQUENCY OF SMART CHARACTERISTICS EXPRESSED IN THE
VISION STATEMNTS BY CITY OFFICIALS
No. of cities City Cluster with population Living Environment Economy Mobility Governance
4Less than 100,000 4 4 2 2 2
17 100,000 500,000 16 12 11 5 3
11 500,000 1,000,000 11 8 7 3 3
20 1,000,000 2,000,000 19 17 16 8 6
8 2,000,000 and above 75342
60 Overall 57 46 39 22 16
Source:Authors
citizens have given to strengthening the other aspects of a
smart city.
On further analysis, the city clusters (Table IV in the
Appendix) create a slightly different ordering of the priority
areas (Table II). This variation in the ordering can be explained
by the different issues/challenges that cities face in each
group. The difference can be seen in the cities with more
than 2,000,000 people when compared with the other groups.
The top priority for cities with less than 2,000,000 people is
Smart Living, while the top priority for the cities with more
than 2,000,000 people is shared between Smart Living and
Smart Mobility. Traffic issues tend to be worse in the largest
cities and require immediate action, elevating both Living
and Mobility as top priorities. The most important concern
in the other groups relates to having physical infrastructure
that provides affordable housing, proper road connectivity,
24-hour power supply, and running water. The citizens in
the cities with a population less than 100,000 gave almost
equal importance to Smart Environment (12%) and Smart
Economy (11%). An interesting observation about this smaller
city cluster is that the priority for economy is the highest
when compared to other city clusters, even though the cities
clustered under this category are less urbanized than other
clusters. Smart Economy (5%) and Smart Governance (5%)
were given equal importance by the cities with a population
between 500,000 1,000,000. Smart Economy moves up in
the ranking for cities in the smallest group (with population
less than 100,000) and the largest group (with population more
than 2,000,000), while Smart Governance takes the fifth place
in priority order for these clusters.
B. Vision statements used to describe an Indian Smart City
Burke characterized a good vision statement as a succinct,
future oriented, and descriptive statement that should include a
time-frame [11]. This means a vision statement should include
a destination, purpose, and an organization’ s core values.
According to the MoUD, a strategic vision shapes a preferred
future for a city. A successful vision is considered to have an
economic, spatial, social, and/or environmental dimension that
reflects a city’ s unique physical and cultural trait. It provides
a direction for the activities of the municipality, citizens, and
stakeholders and ensures that they are working towards those
shared goals. The city vision captures what a city can be in
the future, with the transformation being generally achieved
within a ten to twenty-year time frame [3].
Out of the 60 cities, 57 included Living, 46 included
Environment, 39 included Economy, 22 included Mobility,
while just 16 included Governance (Table III). From these
observations, the top priority area is Living while Governance
has the lowest importance.
The semantic analysis of the city vision statements high-
lights a different ordering of priorities when compared against
the citizen survey. This difference can be seen by comparing
the order of columns in Table I and Table II. While Living is
identified as a top priority by both citizens and city officials,
city officials place much more emphasis on the Economy
than citizens, and citizens appear to be more concerned about
Mobility than city officials.
The 10 most frequent characteristics included in the vision
statements were Eco-friendly (30), Sustainable (28), Inclusive
(21), Vibrant (19), Economy (17), Tourism (16), Livable (15),
Heritage (14), Quality of Life (11), and Safe (11). These
keywords describe city officials’ visions for developing their
smart cities and reflect the goals to be achieved in the next
5-10 years. Heritage and Tourism were seen as supporting the
economy by many of the city officials envisioning smart cities.
C. Analysis of ABD and PAN projects
The project title analysis of 329 projects to be implemented
under the SCM showed that the majority of the projects
focused on Living, Mobility, and Environment, with only
a small number focused on the Economy and Governance.
Further, the SCM funding is heavily targeted on ABD projects
(80%) rather than PAN projects (20%), which means that a
larger amount of funds are spent on projects that are likely
to benefit only a portion of the city. The analysis of the PAN
projects showed that 60% are smart and the other 40% are
traditional. On further investigation of both PAN and ABD
projects for the top 21 cities (ranked by MoUD), it was found
that 54% of the ABD projects and 89% of the PAN projects
can be categorized as smart. Some of the smart projects
included Smart Metering for Energy, Water, and Waste, Traffic
Analytics, Simulation and Modeling, and a Citizen’s Connect
Initiative whereas the traditional projects included 24*7 Water
and Energy Supply, Bus Depot Management, and Building
Affordable Housing. The share of smart ABD projects by cost
account for 39% of the total cost of ABD projects, whereas the
Smart City Symposium Prague 2017
share of smart PAN projects by cost account for 87% of the
total cost of PAN projects. The share of smart ABD projects is
low when considered in the context of the purpose of the SCM.
However, the vision of SCM does include the “ provision of
core infrastructure,” decent quality of life for the citizens,”
clean environment, and “ application of smart solutions.”
Thus, there is clearly scope within the SCM to advance more
traditional infrastructure projects.
V. DISCUSSION
The United Nations estimates that by 2030, over 60% of
the global population will be living in cities or peri-urban
communities that are increasingly concentrated in Asia, Africa,
and Latin America [2]. It is therefore important to plan
smart cities in these regions to address the current and future
urbanization challenges. These challenges across developing
and underdeveloped countries are, to an extent, similar, but
their priority may vary with the population size as seen in this
case study of the SCM in India.
The prospective smart cities in India envision smartness dif-
ferently. Using the smart city framework proposed by Giffinger
et al. [4], it was possible to categorize the priorities of city
officials and Indian citizens. While the priority areas included
in the vision statements varied from those identified by the
citizens, the following two observations can be made: (a) from
a citizen perspective, Living is the top priority area followed
by Mobility; and (b) from the category analysis of vision state-
ments, Living was the top priority followed by Environment.
The priority areas mentioned by the citizens focused more on
physical assets, including Mobility and Living, while Economy
was given the lowest priority. In contrast, the vision statements
consistently emphasized Living followed by Environment and
Economy. In both analyses, Governance was given a much
lower priority. These results confirm the trends highlighted
in recent studies [12]–[15] on the patterns of urbanization of
large Asian cities. It is observed that Asian cities have paid
more attention to the Transport and Mobility domains than
they have to Government, Economy, and People [16].
The analysis of PAN and ABD projects showed that the
majority of projects which focused on Living, Mobility, and
Environment aspects could be better categorized under Ba-
sic Infrastructure. Basic Infrastructure can be considered as
providing a foundation for smartness, and include projects
such as WiFi connectivity, Optical Fibre Cable, Underground
Drainage, Wiring and Data Management, Fire Safety, and
Sanitation. Several cities focused on improving governance,
which was reflected in projects involving Citizen Connectivity,
Digitization of Assets, and Integration of Services. Very few
projects focused on creating a Smart Economy.
In contrast to these findings, most of the smart city inter-
ventions in the European Union focus on the soft aspects
of the smart city concept such as smart governance and
smart people, whereas the emphasis in North America is
on creating a smart environment. The leading smart cities -
e.g., Vienna, Barcelona, New York, London, etc. - use city
development strategies to advance their objectives, relying
on key technologies such as modern transport technologies;
green, efficient, and sustainable energy [17]–[19]; and policy
frameworks or smart governance [20]–[22].
This research highlights that the concept of a smart city in
India –as defined by vision statements and citizen preferences,
and the analysis of PAN and ABD projects –may be different
to the notion of a smart city outside of the Indian sub-
continent. This difference can perhaps be explained by the
state of infrastructure development in India when compared
to cities in a more developed context. India has encountered a
mix of conditions over the last few decades such as rapid
migration, shortage of urban services, and high levels of
pollution. Therefore, Indian cities need to develop and expand
their basic services, in addition to embedding “smartness” into
these services. In contrast, in the European and North America
context, the focus has been on embedding smartness into
existing infrastructure systems. Thus, countries facing a similar
set of infrastructure development challenges as India, may
be advancing a unique approach to smart city development
that blends smartness with traditional infrastructure projects.
Given the need to build new infrastructure, cities in India have
an opportunity to embed smartness into their infrastructure
systems. However, our analysis reveals that this opportunity
does not appear to be leveraged by the majority of projects
funded under the SCM.
VI. CONCLUSION
This preliminary research presents the first step in under-
standing how India is defining “ smartness” in the context
of city development. The research used three approaches: (a)
an analysis of citizens priorities in smart city development;
(b) an analysis of smart city vision statements framed by
city officials; and (c) an analysis of the titles of smart city
projects to be implemented under the SCM. The results
indicate that citizens value smart living and mobility, whereas
city officials prioritize smart living followed by environment
and the economy. The analysis also reveals how city size
influences the priorities of citizens and city officials, indicating
that the notion of a smart city in India may vary depending
on the population- and infrastructure-related challenges facing
a city. Cities in India also appear to be pursuing their own
conception of what a smart city should be, which may provide
a more appropriate frame of reference for other developing and
underdeveloped nations who are looking to advance similar
programs.
This research provides a useful frame of reference that will
structure a future study of smart city development in India.
This future study will include interviews with city officials
and members of the core team behind the SCM. The objective
of this research will be to identify how cities in an emerging
economy are expanding infrastructure services that leverage
smart technologies, and what could be done to accelerate the
delivery of these services.
APPENDIX
This section consists of a description of the city clusters
(Table IV) and provides an example of two smart city vision
statements:
Smart City Symposium Prague 2017
TABLE IV: DESCRIPTION OF CITY CLUSTERS BASED ON POPULATION
Population
Range
Cities whose citizen survey were analyzed Cities whose vision statements were analyzed
Less than
100,000
Namchi, Dharamshala and Panaji Namchi, Panaji, Dharamshala and Kohima
100,000
500,000
Dahod, Gandhinagar, Dindigul, NDMC, Haldia, Rourkela, Sagar,
Tirupati, Biharsharif, Oulgaret, Karnal, Shivamogga, Rampur, Kak-
inada, Shillong, Bilaspur, Thoothukudi, Agartala, Bhagalpur, New
Town Kolkata, Udaipur, Belagavi, Erode, Mangaluru
Port blair, Vellore, Thanjavur, NDMC, Imphal, Rourkela, Tiru-
pati, Tumakaru, Shivamogga, Kakinada, Agartala, Bhagalpur,
Newtown Kolkata, Davangere, Udaipur, Belgaum, Mangaluru
500,000
1,000,000
Jhansi, Bidhannagar, Saharanpur, Amravati, Bhubaneswar, Jaland-
har, Aligarh, Tiruppur, Moradabad, Bareilly, Tiruchirappalli, Sola-
pur, Guwahati, Chandigarh
Ujjain, Ajmer, Kochi, Warangal, Salem, Bhubaneswar, Jaland-
har, Hubballi-Dharwad, Solapur, Guwahati, Chandigarh
1,000,000
2,000,000
Raipur, Gwalior, Ranchi, Allahabad, Aurangabad, Varanasi,
Kalyan-Dombivali, Rajkot, Faridabad, Agra, Ludhiana, Ghaziabad
and Vishakhapatnam
Kota, Raipur, Madurai, Coimbatore, Jabalpur, Gwalior, Ranchi,
Amritsar, Aurangabad, Varanasi, Kalyan-Dombivali, Faridabad,
Nashik, Agra, Ludhiana, Vadodara, Visakhapatnam, Bhopal,
Thane, Indore
2,000,000 and
above
Kanpur, Lucknow, Pune, Surat and Ahmedabad Nagpur, Kanpur, Lucknow, Jaipur, Pune, Surat, Chennai,
Ahmedabad
Source: [1] and [3]
Bhubanewar: Bhubaneswar, through participatory
decision-making, responsible governance and open access
to information and technology, aspires to be a: Transit
oriented city with a compact urban form that promotes
active, connected and sustainable mobility choices; Livable
city providing diverse range of housing, educational and
recreational opportunities; while enhancing its heritage, arts
and traditional communities; Child-friendly city providing
accessible, safe, inclusive and vibrant public places; Eco-
city co-existing in harmony with nature for nurturing a
resilient, clean, green, and healthy environment; and Regional
economic centre attracting knowledge based enterprises and
sustainable tourism activities by leveraging and empowering
its institutions, local businesses and informal workforce.
Nashik: Nashik, a city renowned for its cultural heritage
and now as the “ Wine Capital of India” provides diverse cul-
tural and lifestyle experiences in a beautiful natural setting of
the Godavari river waterfront. Being part of the economically
vibrant Mumbai-Pune-Nashik Golden Triangle, Nashik offers
its existing and prospective investors excellent investment and
its residents diverse employment opportunities. A responsive
local government has planned Nashik to being a safe city
to walk and cycle and be a sustainable city with quality
infrastructure and services.”
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... Since in some cases the citizens do not get the chance to evaluate the improvements that take place in their city, the authors in [17] introduce a procedure/model to enhance the citizens' participation in their smart city's development plan. To become smart, a city should develop an approach of services that will mainly focus on citizens so that they could be the primary beneficiaries of the new urban project. ...
... In other words, according to the citizens' satisfaction, the city can proceed with the development, which will be focused on its residents. In [17], the authors use Boyd Cohen's model (Smart Cities Wheel) as a metric model, which consists of six Key Performance Indicators (KPIs), based on Kano methodology, to determine the level of satisfaction that is generated from the citizens. Through the Kano model, the attributes that provide levels of satisfaction are determined and classified. ...
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... This literature review shows that there are different views regarding the complexity of this concept. Several authors (e.g., (Bibri & Krogstie, 2017;Gupta & Hall, 2017;Thrift, 2014)) mention that the complexity of "smart city" refers to the complexity of the term "smartness" that can have multiple meanings such as: safe, connected, intelligent, green, sustainable, etc. In addition, there is not a standard measure to evaluate the smartness level of a smart city Balakrishna, 2012;Jucevičius & Liugailaitė-Radzvickienė, 2014). ...
... According to our analysis of the literature, we identified that IoT technology is expected to substantially support the sustainable development of smart cities (Vlacheas et al., 2013). It can ensure the connection between geospatial objects (Hui et al., 2017), increase security (Qela & Mouftah, 2012), improve services (Vattapparamban et al., 2016), or optimize natural resources (Gupta & Hall, 2017). The main roles of IoT identified from our analysis of the literature in smart cities are: ...
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We analyze and compare 11 city cases in three continents to find out differences and commonalities in the green dimension in smart city plans globally: Shanghai (China), four cities in Japan, Iskandar (Malaysia), New York (United States), and Amsterdam, Málaga, Santander, Tarragona (Europe). The aims of the work has been to test whether there is an environmental ethic embedded in long-term strategic commitments in these local contexts, how different environmental values are, and what lines of research might be interesting to tackle from scientific perspectives in future works where the green dimension is addressed in smart city plans. We find that plan design is very different in the search of a model of a smart city in the 11 cases studied. As we expect choices in plan design to have a long-term impact in terms of environmental outcomes and further resilience, both locally and globally, the environmental ethics attached to the local plans, or the lack thereof, we argue have a strong impact.
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