ArticlePDF Available

A Review of Technical Standards for Smart Cities

MDPI
Clean Technologies
Authors:

Abstract

Smart cities employ technology and data to increase efficiencies, economic development, sustainability, and life quality for citizens in urban areas. Inevitably, clean technologies promote smart cities development including for energy, transportation and health. The smart city concept is ambitious and is being refined with standards. Standards are used to help with regulating how smart cities function and contributing to define a smart city. Smart cities must be officially recognized by national and international authorities and organizations in order to promote societal advancement. There are many research and review articles on smart cities. However, technical standards are seldom discussed in the current literature. This review firstly presents the study of smart city definitions and domain. The well-known smart city standards will be presented to better recognize the smart city concept. Well-defined standards allow meaningful comparisons among smart cities implementation. How smart city initiatives make a city smarter and improve the quality of life will be discussed for various countries. This review highlights that technical standards are important for smart cities implementation. This paper serves as a guide to the most recent developments of smart cities standards.
clean
technologies
Review
A Review of Technical Standards for Smart Cities
Chun Sing Lai 1,2 , Youwei Jia 3,*, Zhekang Dong 4,*, Dongxiao Wang 5, Yingshan Tao 2,
Qi Hong Lai 6, Richard T. K. Wong 7, Ahmed F. Zobaa 1, * , Ruiheng Wu 1and Loi Lei Lai 2,*
1Department of Electronic and Computer Engineering, Brunel University London, London UB8 3PH, UK;
chunsing.lai@brunel.ac.uk (C.S.L.); ruiheng.wu@brunel.ac.uk (R.W.)
2Department of Electrical Engineering, School of Automation, Guangdong University of Technology,
Guangzhou 510006, China; 2111704005@mail2.gdut.edu.cn
3Department of Electrical and Electronic Engineering, Southern University of Science and Technology,
Shenzhen 518055, China
4School of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310018, China
5
System Design and Engineering Department, Australia Energy Market Operator, Melbourne 3000, Australia;
dongxiao.wang@aemo.com.au
6Sir William Dunn School of Pathology, University of Oxford, Oxford OX1 3RE, UK; qi.lai@path.ox.ac.uk
7
Department of Computing and Information Systems, School of Science and Technology, Sunway University,
Selangor 47500, Malaysia; richardwtk@sunway.edu.my
*Correspondence: jiayw@sustech.edu.cn (Y.J.); englishp@hdu.edu.cn (Z.D.); azobaa@ieee.org (A.F.Z.);
l.l.lai@ieee.org (L.L.L.)
Received: 14 June 2020; Accepted: 12 August 2020; Published: 17 August 2020


Abstract:
Smart cities employ technology and data to increase eciencies, economic development,
sustainability, and life quality for citizens in urban areas. Inevitably, clean technologies promote
smart cities development including for energy, transportation and health. The smart city concept is
ambitious and is being refined with standards. Standards are used to help with regulating how smart
cities function and contributing to define a smart city. Smart cities must be ocially recognized by
national and international authorities and organizations in order to promote societal advancement.
There are many research and review articles on smart cities. However, technical standards are
seldom discussed in the current literature. This review firstly presents the study of smart city
definitions and domain. The well-known smart city standards will be presented to better recognize
the smart city concept. Well-defined standards allow meaningful comparisons among smart cities
implementation. How smart city initiatives make a city smarter and improve the quality of life will
be discussed for various countries. This review highlights that technical standards are important for
smart cities implementation. This paper serves as a guide to the most recent developments of smart
cities standards.
Keywords:
smart city; technical standard; smart energy; smart health; smart transportation; smart
governance; smart education
1. Introduction
By 2050, it is expected that 66% of the global population will dwell in urban regions [
1
].
The challenge will be to supply these populations with essential resources including sucient
energy, clean water, and safe food while simultaneously warranting complete economic, social,
and environmental sustainability.
Several cities today have aspirations of transforming into the smart cities of tomorrow. However,
the challenges to be overcome to accomplish this include the planning of a complicated plan that
comprises public and private participants, product vendors, and information technology infrastructure
Clean Technol. 2020,2, 290–310; doi:10.3390/cleantechnol2030019 www.mdpi.com/journal/cleantechnol
Clean Technol. 2020,2291
providers. A smart city needs the foundation of standards-based information technology infrastructure
that fulfils and supports a wide range of requirements and can adapt to novel technologies, such as
advanced sensors, measurement and analytics tools, and solutions driven by machine learning and
artificial intelligence. Smart city development requires support from public organizations, citizens,
state and local government, and private enterprises. The benefits of a smart city include the creation
of major prospects for sustainability, disaster prevention, business, public safety, and quality of life
enhancements. However, there are key challenges that need to be addressed for a smart city including:
Commodification: As discussed by Gandy and Nemorin [
2
], a major concern regarding the smart
cities’ development is the motivation to support this worldwide initiative, from the pursuit of new
markets by transnational corporations. Corporate organizations are keen to mine personal data, such as
biometric data [
3
]. Data brokers could create consumer profiles including biometric information,
and identities can be located and tracked as citizens move in a smart city. These profiles can also
intensify commodification by mining the freshly available sources of data, with the ubiquity of sensors
as dynamic data collection points.
Social and digital exclusion: In designing smart cities solutions, it is important to use suitable
means to engage and empower population groups which are hard to reach, such as citizens living in
poverty and/or social exclusion, migrants, younger and older people, or people with disabilities [
4
].
Smart city technologies should be made aordable and able to be accessed by all groups of consumers.
A smart city should be an age-friendly environment. The World Health Organization defines
age-friendly environments as ones which “foster health and well-being and the participation of
people as they age” [
5
]. These environments are accessible, equitable, inclusive, safe and secure,
and supportive. Senior citizens may experience negative attitudes and discrimination based on their
age. Creating age-friendly environments acknowledges diversity, fights ageism, and ensures that
everyone has the opportunity to fully participate.
Privacy and surveillance: Privacy becomes a major concern when the data collected could lead to
linking or identifying an individual, especially when gathered from numerous information sources.
Data storage by governments is generally non-transparent. The likelihood for cross-sharing data within
government services could lead to third parties to have access to the data, where the provider has no
intention for it to happen. Zoonen [
6
] constructed a four-quadrant privacy framework to theorize if
and how smart city technologies and urban big data produce privacy concerns among the people in
these cities. The framework is developed according to two recurring dimensions in research towards
people’s concerns about privacy: one dimension signifies that people see specific data as more personal
and sensitive than others, the other dimension signifies that people’s privacy concerns vary according
to the purpose for which data is gathered, in contrast to the surveillance and service purposes which
are the most dominant. The work concludes that the smart technology options and the use of specific
data and analytic tools are important factors to comprehend people’s privacy concerns in smart cities,
as well as to their awareness of what type of data to use to serve a purpose. A smart city should address
(1) an applied need to substantiate the empirical relation between purpose, and technologies, and;
(2) to produce a theoretical and situated comprehension of people’s privacy anxieties in smart cities.
In addition, building a smart city is a gigantic task as there are several working parts and
components involved, namely the smart cities domains [
7
]. Many smart cities are not constructed
from scratch or all in a single attempt. Smart city development is a gradually evolving process that
witnesses the city becoming smarter, bit by bit. As time progresses, the individual regions of smartness
develop together and interconnect, but on the condition for them using the same consistent technical
rules that are stipulated by technical standards.
Several researchers have reviewed smart city projects from dierent perspectives. Camero and
Alba [
8
] explored the computer science and information technology used for a smart city. There is
no agreement on a smart city definition and in fact, several definitions are being developed.
One explanation is for the iterative process where cities become smarter as time progresses. There are
Clean Technol. 2020,2292
very few studies on the inclusion of policy and urban planning recommendations in information
technology and computer science literature.
Caird and Hallett [
9
] examined the creation of appropriate, valid, credible, and valuable approaches
to smart city evaluation by studying conceptual, measurement, and evaluation challenges for five UK
smart city projects. Caird and Hallett [
9
] identified that a critical challenge for evaluation design is in
creating standardized smart city development and performance indicators that give useful citizen and
city-centered evaluations. There is a significant amount of work on standardization and smart urban
metrics driven by international standards organizations. Specifically, the Smart and Sustainable Cities
and Communities Coordination Group advises on European interests and requirements concerning
standardization on Smart and Sustainable cities and communities. The International Organization for
Standardization (ISO) has concurred on standards for ‘Smart Community Infrastructures performance
metrics. ISO Technical Report 37150:2014 (Smart community infrastructures—Review of existing activities
relevant to metrics) [
10
] reports community infrastructures including water, energy, waste transportation,
and Information and Communications Technology (ICT). The standard concentrates on the technical
features of current activities which are available. Political, societal, or economic aspects are not studied
in this standard. ISO Technical Report 37151:2015 (Smart community infrastructures—Principles and
requirements for performance metrics) [
11
] details the principles and stipulates requirements for the
definition, identification, optimization, and harmonization of community infrastructure performance
metrics, and gives recommendations for analysis, including smartness, interoperability, synergy, resilience,
safety, and security of community infrastructures. Funded by the European Union HORIZON 2020
program, the CITYkeys project [
12
] is an important European Commission EUROCITIES initiative that
aims to create acceptable city performance measurement frameworks: Key Performance Indicators.
The initiative creates standardized data collection processes to increase the adoption rate of smart city
solutions. It is anticipated that comparable, scalable, and replicable smart city solutions can be achieved
across cities. The authors concluded that standardized smart urban metrics and indicators are not widely
adopted by cities while the development of standards is at the early stages.
Hasija [
13
] examined the current global advancements in smart city initiatives. The study was
categorized into three themes, namely data access and collection, end-user utility, and economic feasibility
of different solutions. The economic viability is crucial to the success of a smart city initiative. The potential
ideas to enhance city operations could not be delivered if it they are economically unsustainable.
For business strategies, prudent analysis is required to examine the trade-offs that determine the efficacy
of such initiatives. A bike-sharing scheme is an affordable and convenient mode of transportation in
China. However, not all bike-sharing companies are successful. Some of the issues contribute to the
failure of bike-sharing initiatives include (1) no regulation: bikes could end up in different places and
be dumped along city streets; (2) lack of operational sustainability: many bike-sharing platforms do not
need a security deposit; (3) no optimization: lack of consideration for how and where the bikes should be
located to maximize utilization and to avoid bikes piling up on streets.
Anthopoulos [
14
] examined twenty smart cities projects of various scales in dierent countries
and continents. Furthermore, the review documented the challenges that the cities meet as they
work towards being a smart city. The review examines smart cities in relation to climate change,
sustainability, natural disasters, and community resiliency. A smart city project is complex and
expensive. Anthopoulous [
14
] firstly examined the project management guidelines and frameworks for
agile and complex projects, including a smart city. ISO 21500:2012 Guidance on project management
is an international standard that can be used by private or public organizations for all kinds of
projects. The aim is to provide a guide to project managers on how to apply project management
disciplines into a business environment to increase the possibilities for enhanced business results
and project success. An important aspect is the use of the common language and processes by all
project stakeholders, which enhances communication and cooperation. ISO 21500 gives a high-level
description of concepts and processes to create good practices in project management. The cities
reviewed focuses on the project management perspective including scope, organization, time, cost,
Clean Technol. 2020,2293
quality, risk, and procurement. The smart city projects are well documented with great detail in the
project development. However, there is a lack of discussion on technical standards of the smart city
projects apart from project management.
Van Winden and Van den Buuse [
15
] analyzed the procedures of upscaling, concentrating on smart
city pilot projects where numerous stakeholders with dissimilar missions, agendas, and incentives
work together. If technical standards can be smoothly adapted to fit with the geospatial context,
then the solution becomes more attractive to many cities. Numerous works on smart cities have
been conducted and review literature for smart cities exists. However, most recent literature lacks
discussions on an important topic of international standards for smart cities. International standards
are technical standards developed by international organizations. International standards can greatly
assist tailor-made solutions development for bespoke conditions of a city. Standards stipulate the
anticipated level of performance and technologies compatibility. Standards are generic metrics that
allow solutions to be benchmarked and compared. Section 2presents the definitions and domains
of smart cities. As international standards are the basis of building a smart city, Section 3exhibits
international standards for a smart city. Section 4describes the current smart city projects for various
countries and the standards adopted. The conclusion is given in Section 5.
2. Smart City Definitions and Domains
One of the reasons behind the lack of unified definitions of a smart city is because of the various
entities involved and the functions the smart city provides. Hence, existing definitions can vary
greatly. There are several definitions for a smart city which are defined by various organizations
and stakeholders.
The most common consensus is that the smart city employs various kinds of digital and electronic
technologies to transform the living environments with ICTs [
16
,
17
]. Deakin [
18
] labeled the smart city
as a city that employs ICT to meet the market (the citizens’) needs. There is a need for larger community
involvement to achieve a smart city. A smart city does not simply contain ICT technology but has also
developed the technology to achieve positive impacts to the local community. Some definitions for a
smart city from major professional organizations and government agencies are given as follows:
Association of Southeast Asian Nations [
19
]: “A smart city in ASEAN harnesses technological
and digital solutions as well as innovative non-technological means to address urban challenges,
continuously improving people’s lives and creating new opportunities. A smart city is also
equivalent to a “smart sustainable city”, promoting economic and social development alongside
environmental protection through eective mechanisms to meet the current and future challenges
of its people, while leaving no one behind. As a city’s nature remains an important foundation of
its economic development and competitive advantage, smart city development should also be
designed in accordance with its natural characteristics and potentials”.
British Standard Institution [
20
]: A smart city is an “eective integration of physical, digital and
human systems in the built environment to deliver a sustainable, prosperous and inclusive future
for its citizens”.
Department for Business, Innovation and Skills, UK [
21
]: “A Smart City should enable every
citizen to engage with all the services on oer, public as well as private, in a way best suited to
his or her needs. It brings together hard infrastructure, social capital including local skills and
community institutions, and (digital) technologies to fuel sustainable economic development and
provide an attractive environment for all”.
European Commission [
22
]: “A smart city is a place where traditional networks and services are
made more ecient with the use of digital and telecommunication technologies for the benefit
of its inhabitants and business. A smart city goes beyond the use of ICT for better resource use
and less emissions. It means smarter urban transport networks, upgraded water supply and
waste disposal facilities and more ecient ways to light and heat buildings. It also means a more
Clean Technol. 2020,2294
interactive and responsive city administration, safer public spaces and meeting the needs of an
ageing population”.
Innovation and Technology Bureau, Hong Kong [
23
]: “Embrace innovation and technology to
build a world-famed Smart Hong Kong characterised by a strong economy and high quality of
living”.
Institute of Electrical and Electronics Engineers Smart Cities Community [
24
]: A smart city
gathers government, technology, and society to achieve a minimum of the following factors:
smart mobility, a smart economy, a smart environment, smart cities, smart governance,
smart people, and smart living.
International Electrotechnical Commission [
25
]: “A smart city is one where the individual city
systems are managed in a more integrated and coherent way, through the use of new technologies
and specifically through the increasing availability of data and the way that this can provide solid
evidence for good decision making”.
Japan Smart Community Alliance [
26
]: The expression “Smart Community” is more widespread
than “Smart City” in Japan [
22
]. “A smart community is a community where various
next-generation technologies and advanced social systems are eectively integrated and utilized,
including the ecient use of energy, utilization of heat and unused energy sources, improvement
of local transportation systems and transformation of the everyday lives of citizens”.
Ministry of Housing and Urban Aairs, India [
27
]: “The conceptualisation of Smart City, therefore,
varies from city to city and country to country, depending on the level of development, willingness
to change and reform, resources and aspirations of the city residents. A smart city would have a
dierent connotation in India than, say, Europe. Even in India, there is no one way of defining a
smart city”.
According to the above, the similarity and dierences in smart city definitions can be summarized
as follows:
Similarities:
#
Enhancement of living standards by making informed decisions with advanced technologies
to collect, process, and evaluate data.
#Systems are integrated to exchange information.
#Citizens are better informed about their surroundings.
#Sustainability and environmental conservation should be maximized.
Dierences:
#
Smart city domains or elements e.g., transport, energy, and health (explained in the
following section) can be dierent due to regional interests.
From the above summary, it is shown that for a city to become smart, multiple sources of data from
a range of urban activities and domains must be connected to reveal opportunities to bring innovation
to today’s connected citizens. Deloitte [
28
] stated that a smart city is driven by the innovation success
of six key domains including:
1.
Energy and environment: Sustainable growth is created by technology and cities make better use
of resources from electronic sensors that monitor leakages, as well as gamification and behavioral
economics to support citizens to conduct considerate decisions on resource utilization [
29
].
Renewable energy including solar and wind will be important sources of energy generation [
30
32
].
Data analytics will be used to enhance energy and power system operation [33];
2.
Economy: The economy will be aected by digitization and disruptive technologies, which will
change the needs of several types of jobs. Smart cities need to create strategies to adopt future
jobs that will power Industry 4.0 and beyond [34];
Clean Technol. 2020,2295
3.
Safety and security: As criminals will make use of technology to commit advanced crimes,
public safety and security authorities will also use technology for crime prevention by assessing
multiple streams of social and crowdsourced information, including super-resolution images [
35
]
and image fusion [36];
4.
Health and living: The lives of citizens are enhanced with technology and connectivity.
Connected communities are achieved with smart buildings. Enhanced social programs and
innovated health care sector are data-driven [37];
5.
Mobility: The integrated mobility systems include autonomous vehicles and shared mobility
services achieved with the Internet of Things (IoTs). The concept of IoTs occurs when devices are
communicating with other devices on behalf of people and will dominate the future of Internet
communications [
38
]. Advanced analytics allow citizens and goods to travel in ways that are
safer, cheaper, cleaner, and faster [39];
6.
Education and government: Technological advancement will aid government procedures and
give a seamless experience to businesses. Smart cities use analytics to assist authorities to create
insight-driven policies, monitor performance and outcomes, allow constituent engagement,
and enhance government eciency. Data and analytics will also assist next-generation teachers
to familiarize their counselling and teaching for greater student achievement. More creative and
personalized education plans can be created such as virtual learning environments [40].
Similarly, Ginger et al. [41] described the smart city as having six domains, including:
1.
Smart economy: Consists of features surrounding economic competitiveness including
entrepreneurship, innovation, flexibility, the productivity of the labour market, trademarks,
and participation in the global market.
2.
Smart people: Concerns not only the level of qualification or education received by citizens but
also additional social interactions and perceptions of public life.
3.
Smart governance: Concerns political involvement, citizen services, and administration functions.
4.
Smart mobility: Includes local and global accessibility with the presence of ICTs and sustainable
and relevant transport systems.
5.
Smart environment: Concerns attractive natural conditions including green space,
less extreme climate, reduced pollution, resource management, and working to achieve
environmental protections.
6.
Smart living: Includes many features of quality of life composed of health, housing, culture,
tourism, and safety.
It is worth noting that there are other domains including:
Smart water [
42
,
43
]: Smart water systems employ IoT enabled sensors to collate real-time
data. With precise and reliable data, smart water systems can drive great transformations in water
sector transparency and accountability. There will be governance improvements, risk reductions,
water quality control and eventually a novel business cases for water sector investment [
43
]. The data
allows water facilities optimization by detecting leaks or observing how water is distributed in the
water network. The optimization model empowers citizens to make better decisions about water
management. Smart sensors can detect water pipe leaks and quickly inform engineers to take action
and resolve the issue. Smart water is critical as an estimated 3.3 billion litres of water is wasted daily in
Wales and England due to leaks in water networks [42].
Smart health [
44
,
45
]: The European Commission [
44
] described smart health permits healthcare
providers to reduce illnesses occurrence, to care for patients more eciently, and to cure illnesses more
eectively. Smart health also reduces healthcare expenditure in the growing aging population.
Smart health solutions consist of technological developments in portable and mobile devices,
sensor technology, application development, mobile data connectivity, cloud computing, and big
data analytics, with new ideas on patient co-management, health tracking of remote neighborhoods,
Clean Technol. 2020,2296
and minimizing unhealthy lifestyles. Deloitte [
45
] stated that smart health consists of five features,
including to: (1) empower proactive health and well-being management to make choices that can
proactively improve health, well-being, and quality of life to reduce adverse health outcomes in the
future; (2) foster a sense of community and well-being with virtual and in-person community meetings;
(3) enable digital technology and behavioral science with mobile applications for users to enter and
track data and seek information, e.g., fitness tips and recipes, and deploy the use of coaching and guide
to support adherence and uptake of behaviors associated with healthy, active living; (4) meaningfully
use data to improve outcomes and allow users to track their progress. Consent would be requested from
users to share and use data, to enhance the program and for it to make improved recommendations;
(5) enable new and innovative ecosystems to consist of the collaboration of businesses with all kinds
of organizations e.g., government agencies and academia to align on health outcome measures and
coordinate on investments in communities.
Smart waste [
46
,
47
]: Interreg Europe [
47
] described smart waste as being used “to improve
public policy instruments supporting innovation within waste management procedures. The final
result? Smarter, more eective, sustainable, and cost-ecient waste management, benefiting all
territorial stakeholders”. In the UK, illegal waste activity including fly-tipping costs the UK
economy approximately £600 M annually [
46
]. The present systems for monitoring commercial
and household waste are out-of-date and mainly paper-based. Smart waste employs technology
including blockchain [
48
], electronic chips, and sensors for monitoring waste, waste containers,
and waste vehicles. Smart waste is an element of smart living and smart environments.
In summary, a smart city is an ambitious and crucial transformation of many cities worldwide.
Benefits include improved living conditions are reaped from several sectors/domains. However,
a smart city consists of the development and application of novel technologies. There is a need for
standardized uniform engineering or technical criteria, methods, processes, and practices. The next
section examines how international standards help to build a smart city.
3. International Standards for Smart City
The International Organization for Standardization (ISO) has described standards as “the first
step towards the holy grail of an interoperable, plug-and-play world where cities can mix and match
solutions from dierent vendors without fear of lock-in or obsolescence or dead-end initiatives” [
49
].
International standards are best practice created by global experts. Standards can be used to benchmark
functional and technical performances. Standards make sure that technologies deployed in cities are
ecient, safe, and well-integrated.
The largest and most well-established international standards organizations include ISO [
50
],
the International Electrotechnical Commission (IEC) [
51
], and the International Telecommunication
Union (ITU) [
52
] which were founded between 50 and 150 years ago. The description of these
organizations are as follows:
ISO is a non-governmental and independent global organization with 164 national standards
bodies as members. The standards body for each country (e.g., Bureau de Normalisation (NBN)
in Belgium and Ghana Standards Authority (GSA) in Ghana) works directly with ISO and aims to
minimize diversity in technical definitions. ISO standards are applied in various fields including
quality management, environmental management, IT security, energy management, health and
safety, and food safety [50].
IEC is the world’s forefront organization for the groundwork and publication of international
standards for electronic, electrical, and relevant technologies, i.e., “electrotechnology” [
51
].
IEC described technical and international standards as reflecting “agreements on the technical
description of the characteristics to be fulfilled by the product, system, service or object in question.
They are widely adopted at the regional or national level and are applied by manufacturers,
trade organizations, purchasers, consumers, testing laboratories, governments, regulators and
other interested parties”. Standards help researchers, industry, regulators, and consumers globally
Clean Technol. 2020,2297
to achieve an optimal experience and meet mutual needs for various countries. Standards establish
one of the vital bases for the elimination of technical obstacles to trade.
ITU is the United Nations bespoke agency for ICTs and enables global connectivity of
communications networks [
52
]. ITU manages international satellite orbits and radio spectrum,
creates the international standards that allow technologies and networks to be continuously
interconnected, and aims to enhance ICT access for global communities.
The above organizations have developed standards to specify and establish definitions and
methodologies for a set of smart cities indicators. For example, ISO 37122:2019 (Sustainable Cities
and Communities—Indicators for Smart Cities) [
50
] intends to give a holistic set of indicators to
evaluate advancement in developing a smart city. The standard includes multiple domains including
education, energy, economy, environment and climate change, finance, governance, health, housing,
population and social conditions, recreation, safety, solid waste, sport and culture, telecommunication,
transportation, urban/local agriculture and food safety, urban planning, wastewater, and water.
The World Council on City Data is a prominent initiative in using standardized city data to
create smart cities [
53
]. The initiative hosts a network of innovative cities dedicated to refining
quality of life and services with open city data and delivers a reliable and holistic platform for
standardized urban metrics. The World Council on City Data is an international hub for international
organizations, education partnerships across cities, corporate partners, and academia to expand
innovation, envisage alternative futures, and construct enhanced cities. The initiative developed the
first city data standards, namely, ISO 37120 (Sustainable development of communities: Indicators for
city services and quality of life).
The IEC has identified over 1800 standards that already impact smart cities [
54
]. The SyC Smart
cities promote the coordination of standards eorts of several IEC committees and other organizations,
including ISO, to promote the development of standards to achieve integration, interoperability and
eectiveness of city systems. SyC Smart City is presently developing IEC 63152 as the best practice
tool for city planners. Considering the higher frequency of natural disasters and destruction in some
urban areas, IEC 63152 proposes guidelines to sustain several city services after a disruption occurs.
IEC 63152 provides the fundamental concepts of how several city services can cooperate to uphold the
supply of electricity.
ITU established Study Group 20 and United for Smart Sustainable Cities to develop standard
activities in supporting the utilization of ICTs in a smart city [
55
]. These standards focus on terminologies
for the IoTs and smart cities, high performing ICT infrastructures requirements, and the interoperability
between various ICT or IoT networks. The ICT standard consists of four layers, namely the “application
and support layer”, “data layer”, “communication layer”, and “sensing layer”.
In addition to the above three organizations, the Institute of Electrical and Electronics Engineers
(IEEE) also develops international standards for smart cities. One of the most well-known IEEE
standards is the IEEE 802 family, which was established in the early 1980s and covers local area
networks and metropolitan area networks [
56
]. In recent years, IEEE has established the IEEE Smart
Cities Community, which “brings together IEEE’s broad array of technical societies and organizations
to advance the state of the art for smart city technologies for the benefit of society and to set the global
standard in this regard by serving as a neutral broker of information amongst industry, academic,
and government stakeholders” [57].
In 2017, the IEEE P2784 (Smart City Planning Guide) [
58
] was proposed to develop a framework
that mentions the processes and technologies for planning the smart city transformation. A smart
city requires a unified process planning framework to use IoTs to guarantee agile, interoperable,
and scalable solutions that can be used and supported sustainably. The framework is a method for
technology and cities integrators to plan for technology and innovative solutions for smart cities.
Some of the most recent and first-of-a-kind standard initiatives from IEEE are presented in Tables 15.
Clean Technol. 2020,2298
Table 1. Recent Institute of Electrical and Electronics Engineers (IEEE) Standards in development for a smart grid and smart energy.
Year Title Scope
2016 1889–2018 (Evaluating and Testing the Electrical Performance of Energy
Saving Devices) [59]
Tests and evaluates energy saving devices’ electrical performance.
Measurement methods for observing the power generated or used by the observed load or generator: (1) without the energy saving devices connected to
the circuit; (2) with the energy saving devices connected and powered in the circuit.
Detailed protocols for testing circuits, the accuracy and details of evaluation instrumentation, and the sequence of the test measurements.
Bespoke details for possible sources of measurement errors including from (1) wrong instrumentation connection, (2) inadequate instrumentation, or (3)
wrong results interpretation.
Can be used for all kinds of electrically connected energy saving devices that control electrical power given by a source and powering an electrical load.
2016 P1922.1 (A Method for Calculating Anticipated Emissions caused by
Virtual Machine Migration and Placement) [60]
Methods to compute anticipated emissions created by virtual machine migration and allocation in distributed locations created by various
electricity sources.
Identify the anticipated electric grid’s marginal emissions due to the change in power generation capacity, reflected by the additional power demand
from server accepting the virtual machine and the network supporting virtual machine migration.
Creates a technique to study anticipated gaseous (also greenhouse gases) and particle emissions created by virtual machine migration and allocation in
distributed servers situated in various regions.
2019
P2814 (Techno-economic Metrics Standard for Hybrid Energy and Storage
Systems) [61]
Techno-economic metrics for operation, construction, and development of electrical energy storage systems and renewable energy systems.
2020 P2852 (Intelligent Assessment of Safety Risk for Overhead Transmission
Lines Under Multiple Operating Conditions) [62]
Artificial intelligence methods for a 3-D model of overhead transmission line and locational surroundings, to achieve a precise perception of overhead
conductors to the ground and near buildings and trees.
Identifies safety risk information including distance for overhead transmission lines in various operating conditions and provides an intelligent security
assessment technique.
Useful for intelligent evaluation and control overhead transmission lines safety risk during a typhoon, hot weather, icing, and alternative
operating conditions.
Clean Technol. 2020,2299
Table 2. Recent IEEE Standards in development for smart health.
Year Title Scope
2014 1708–2014 (Wearable Cuess Blood Pressure Measuring Devices) [63]
Creates objective performance and normative definition for assessment of wearable cuess blood pressure measuring devices.
Works for all forms of the device or the vehicle where the device is attached or where it is embedded.
Works for all kinds of wearable blood pressure measurement devices, such as epidermal and unconstrained blood pressure devices that have various
operation modes.
Limited to the assessment of devices that do not use a cuwhilst measuring.
No assessment of all sphygmomanometers operated with an inflatable or occluding cufor the non-intrusive assessment of blood pressure on the upper
wrist or arm.
Manufacturers guidelines to certify and confirm their products, possible purchasers or users to examine and choose potential products, and health care
professionals to perceive the manufacturing practices on wearable blood pressure devices.
2017 P3333.2.5 (Bio-CAD File Format for Medical Three-Dimensional (3D)
Printing) [64]
Establishes the Bio-Computer Aided Design format for 3-D printing from sectional scan image data comprising of volumetric and surface information.
Related to medical 3-D printing services including pathologic services, anatomic models, and medical instrument printing with 2-D images, 3-D medical
data, and alternative medical data.
2017 P1752 (Mobile Health Data) [65]
States requirements for mobile health data applications programming interface and standardized representations for mobile metadata and health data.
Mobile health data consists of personal health data collated from mobile applications and sensors.
2019
1847–2019 (Common Framework of Location Services for Healthcare) [
66
]
The framework consists of location services for healthcare conceptual information model and location services for healthcare common terminology.
2020 P2621.1 (Wireless Diabetes Device Security Assurance: Product Security
Evaluation Program) [67]
A connected electronic product security evaluation program framework consists of:
1. A method to use the ISO/IEC 15408 security evaluation framework in a security evaluation program.
2. Allowing independent testing labs for security evaluation program.
3. Confirming results from authorized labs.
4. Defining and certifying novel security requirements and adjustments to security requirements, from protection profiles and security targets for
security evaluation program.
5. Assurance post-certification maintenance.
Table 3. Recent IEEE Standards in development for smart mobility and transportations.
Year Title Scope
2013 P1884 (Stray Current/Corrosion Mitigation for DC Rail Transit
Systems) [68]
Principles, methods, and data for engineering design, commissioning, installation, observing and evaluating; including mitigation and control
techniques for stray currents in direct current rail transit systems.
2013 P1883 (Electrical and Electro-Mechanical Bench Test Equipment (BTE) for
Transit Rail Projects) [69]
Design factors, documentation, construction materials, and the satisfactory requirement for bench test equipment for novel and current electrical and
electro-mechanical equipment use in transit rail systems.
2014 P2406 (Design and Construction of Non-Load Break Disconnect Switches
for Direct Current Applications on Transit Systems) [70]
Design, usage, and application of direct current non-load or no-load break disconnect switches for isolating direct current power distribution circuits in
transit applications.
2016 P2020 (Automotive System Image Quality) [71]
Deals with key elements of image and quality for applications in automotive advanced driver assistance systems applications, includes recognizing
current metrics and alternative meaningful information associated with these elements.
Formulates objective and subjective evaluation methods for measuring automotive camera image quality.
Presents tools and evaluation techniques to provide standards-based communication and contrast amid original equipment manufacturer and Tier 1
system integrators, and component vendors concerning automotive advanced driver assistance systems image quality.
2017 P2685 (Energy Storage for Stationary Engine-Starting Systems) [72]
Selection, installation design, sizing, installation, maintenance, and evaluating techniques for optimizing the performance and life of energy storage
devices and associated systems for starting stationary engines.
Identify when energy storage devices need replacing. Energy storage devices and related systems including (1) nickel-cadmium and lead-acid batteries;
(2) supercapacitors and electric double-layer capacitors; (3) air-start systems; (4) start/control battery chargers; (5) parallel battery blocking diode systems;
(6) monitoring systems.
Clean Technol. 2020,2300
Table 4. Recent IEEE Standards in development for smart education.
Year Title Scope
2018 P7919.1 (eReaders to Support Learning Applications) [73]
Arranges and explains the eReaders abilities for working as a platform for education, training, learning, and using other approaches for developing
these abilities.
Methodology comprises of industry standards applications and may cover open-source reference code.
2019 P2834 (Secure and Trusted Learning Systems) [74]Details technical specifications for privacy protection and student data management in learning online services and systems.
2019 1876 (Networked Smart Learning Objects for Online Laboratories) [75]
Techniques for saving, retrieving, and using online laboratories as interactive and smart learning objects.
Defines techniques for combining online laboratories as smart learning objects in learning object repositories and learning environments.
2020 1589–2020 (Augmented Reality Learning Experience Model) [76]
Develop an overarching integrated theoretical model to identify interactivities across the real world, digital information, and the user and the conditions
for augmented reality-assisted learning of the environment.
Defines two data models and interface to Extensible Markup Language and JavaScript Object Notation for depicting learning activities and the learning
environment as the tasks are executed.
Table 5. Recent IEEE Standards in development for smart governance.
Year Title Scope
2017 P7005 (Transparent Employer Data Governance) [77]
Methods to assist employers to validate to access, collect, share, utilize, store, and destroy employee data.
Specific metrics and conformance needs on (1) when handling data from trusted global partners and (2) how vendors and employers can react to
handling data.
2017 P7004 (Child and Student Data Governance) [78]Methodologies for stakeholders in certifiable and responsible student and child data governance.
2020 P2145 (Framework and Definitions for Blockchain Governance) [79]
A generic framework and nomenclature for explaining blockchain governance for all kinds of contexts and use cases, comprising of private, public,
permissionless, hybrid, and with permission.
The standard is normative concerning terminology and non-normative considering the particular blockchain systems and protocols design.
2020 P2863 (Organizational Governance of Artificial Intelligence) [80]
States the governance basis including safety, responsibility, accountability, transparency, and reducing bias, and procedures for performance auditing,
useful implementation, training, and compliance in the formulation or deployment of artificial intelligence in organizations.
Clean Technol. 2020,2301
In summary, this section has presented the need for international standards in smart city research
and development. Some of the emerging standard projects are presented for various smart city domains.
The next section examines the dierent smart cities projects worldwide and focuses on the standards
examined and adopted.
4. Smart City Pilot Projects
Having examined the importance of international standards and the emerging ones, the following
section presents some of the smart cities pilot projects from various countries. The focus is on the
application of international standards. Following the alphabetical order of the continents, the smart
cities pilot projects in Africa and Asia are presented in Tables 6and 7, respectively.
Table 6. Smart cities pilot projects in Africa.
Country Description
Kenya
Konza will be a smart city with a connected urban ICT network that provides urban services connections and
ecient management of those services on a great scale [81]. The city will connect the following four key services:
infrastructure services including transportation, utilities, public safety and environment; citizen services including
access and participation; city services including city information, planning, and development; business services
including support services for local commerce. There is no information regarding the standards adopted in the
Konza project.
South Africa
Slavova and Okwechime [82] examined the broader transformative processes taking place in Africa and
developed a vision of the future African cities. The authors showed the alignment of critical aspects of the smart city
concept with the African Union’s Agenda 2063. Several factors could impact on the transformative process including:
(1) balancing the power dimension of smart city projects in Africa; (2) the dichotomy dividing rural regions from urban
spaces needs to be reduced; (3) the rapid adoption of technologies to implement a smart city. The relevant standards
were not discussed by the authors. The Stellenbosch Smart Mobility Lab helps with developing Stellenbosch to be the
first transportation leaning “Smart City” in South Africa [
83
]. The lab assists with the planning and implementation of
mobility applications of the Smart City model. The applications include parking for enhanced vehicle distribution,
real-time trac and transport operations control systems, bicycle-sharing schemes, information services for
commuters, and trac planning platforms. Transport engineers employ big data gained from probe vehicles and
human movement patterns as input into several of the aforementioned applications. There is no information regarding
the standards adopted in the Smart City model.
Table 7. Smart cities pilot projects in Asia.
Country Description
China
Alibaba’s cloud project, City Brain, uses data collected from video feeds at trac lights to relieve trac congestion
and gridlock in Hangzhou, China. The trac management is 92% precise in recognizing trac violations,
aids emergency vehicles to reach their destinations 50% faster than before, and has permitted trac speeds to grow by
15% [13]. City government leaders and planners can also utilize City Brain to overcome other pressing issues such
alleviating a reduced water supply. Alibaba cloud had adopted numerous international standards to meet security
compliance, including ISO 27001 and ISO 20000 [84].
Dubai
The Smart Dubai initiative improves the living standards of Dubai citizens [85]. There are more than 130
initiatives with the joint eort from government and private sector entities. Examples of initiatives include the Dubai
Data Initiative, the Dubai Blockchain Strategy, the Happiness Agenda, the Dubai AI Roadmap, and the Dubai
Paperless Strategy. Khan et al. [86] identified the best practices linked to Dubai’s smart city and smart tourism.
The city had a large amount of data that were unorganized, unstructured, and had very poor relationships. The Dubai
Data initiative reinforces the Smart Dubai strategy and its applicable major components that enable the ecient
exchange of data and information and modernizes the continuous connectivity for the private and public sectors.
The innovative data-sharing initiative will be managed by international standards and best practices for safe, seamless,
and fair exchanges of data [87]. However, there is no detail regarding the standards that will be adopted.
Hong Kong
Hong Kong’s smart city domains include smart mobility, smart living, smart environment, smart people,
smart government, and smart economy [23]. The Next Generation GovCloud and Big Data Analytics Platform will
modernize the current government cloud infrastructures and implement a new application architecture. Bureaux and
departments can accelerate the development and delivery of digital government services, comprising big data
analytics and artificial intelligence applications [88]. There is no information regarding the standards adopted in the
Next Generation GovCloud and Big Data Analytics Platform. Ma and Lam [89] explored the interrelationships
between several obstacles to open data adoption and suggested practical recommendations to improve open data
development for smart cities. The study concluded that the lack of open data policy should be confronted as a matter
of urgency in Hong Kong. An open mindset and IT literacy in the government organizations continue to be developed.
Clean Technol. 2020,2302
Table 7. Cont.
Country Description
Japan
Japan Smart Community Alliance is the leading authority to promote smart communities in Japan [
26
]. As in Feb.
2019, there are 259 members within the Japan Smart Community Alliance consisting of businesses from the
manufacturing, electricity, gas, heat supply and water, information, and communications sectors. The alliance has also
developed four working groups as follows [26]:
The International Strategy Working Group: Determines policy technological, and market developments
concerning smart communities and shares information with alliance members and international organizations.
The group creates strategies to assist the contributions of Japanese businesses in smart community development
across the globe
The International Standardization Working Group: Expedites eorts in dierent fields in cooperation with
Japan’s Ministry of Economy, Trade, and Industry to attain international smart grid standardization. The group
examines worldwide developments in smart grid standardization and encourages compliance in international
standardization development
Roadmap Working Group: Formulates smart community technology development roadmaps. The group
supports technology development by creating scenarios for next-generation societies in which smart grid
technologies have been implemented. The findings would create a synergistic eect between technology
development and usage
Smart House and Building Working Group: Conducts activities to promote the dissemination of smart houses and
smart buildings by creating work schedules for individual task, comprising the identification and maintenance of
underlying critical devices, evaluating the development of individual task, and stimulating appropriate activities.
Regarding smart cities projects, Woven City is a completely connected ecosystem run by hydrogen fuel cells to be
constructed from early 2021 at the bottom of Mount Fuji [90,91]. This “living laboratory”, a 175-acre urban
development in Higashi-Fuji will comprise full-time residents and researchers who will research and develop
technologies including robotics, autonomy, smart homes, and personal mobility in a real-world setting. Buildings will
be mainly built using carbon-neutral wood and adopt a mixture of robotic production methods and traditional
Japanese joinery methods. Rooftops will be roofed in photovoltaic panels to generate solar power. Electricity will also
be produced by hydrogen fuel cells. All homes will have state-of-the-art human assistance technologies,
from maintaining basic needs and improving daily life to sensor-based artificial intelligence for monitoring personal’s
health. Woven City is an opportunity to utilize connected technology with security and integrity. The original plan is
for 2000 people living in Woven City. The dwellers include Toyota employees and their families, industrial partners,
retailers, retired couples, and visiting scientists. More residents will be invited as the project progresses. There is no
information regarding the standards adopted in the Woven City.
In Australia, the Australian Government established the Smart Cities Plan in 2016 [
92
]. The Plan
highlights the Government’s vision for productive and habitable cities that boost innovation,
upkeep growth and generate jobs. The Plan embodies a framework for a cities policy at the federal level.
City Deals are the important drivers for executing the Smart Cities Plan. They are partnerships between
the three levels of government and the community to strive for a shared vision for liveable and productive
cities. Standards Australia is the country’s leading independent, non-governmental, not-for-profit
standards organization [
93
]. The organization is actively participating in national and international
discussions on smart cities, including being involved in the ISO Technical Management Board United
Nation Sustainable Development Goals Taskforce. The task force will: revisit the mapping of ISO
standards to the Sustainable Development Goals; identify the importance of Sustainable Development
Goals for ISO, leading to the design of a database that can be used by businesses and organizations
to determine the useful standards in promoting Sustainable Development Goals; create guidance
for committees on how to proactively identify the right partnerships including the United Nations
and other international organizations; oer recommendations for which organizations including ISO
should work in standards promotion to support Sustainable Development Goals.
The smart cities pilot projects in Europe, and North America and South America are presented in
Tables 8and 9, respectively.
Clean Technol. 2020,2303
Table 8. Smart cities pilot projects in Europe.
Country Description
Barcelona
Bakici et al. [94] examined the city of Barcelona and analyzed its Smart City initiative, including its urban policy
implications. This article analyzes Barcelona’s transformation in the areas of Smart City management, drivers,
bottlenecks, conditions, and assets. The authors described the Barcelona Smart City model and examined the key
factors of the Smart City strategy while considering living labs, Open Data, e-Services, smart districts, initiatives,
and infrastructures. The Barcelona Smart City model consists of four domains including smart governance,
smart economy, smart living, and smart people. The 22@ Barcelona region is a central point for innovation and
economic development, as small-medium enterprises use the region as a test-bed to trial novel technologies. There is
no information regarding the standards adopted in the 22@ Barcelona region.
Romania
Pop and Pros
,tean [95] studied the implementation approaches for dierent smart cities in Romania.
The considered cities include Craiova, Napoca, Sibiu, and Timisoara. All Romanian smart cities oer mobile
applications to citizens to notify them in real-time of the timing for each individual public transport station.
In Cluj-Napoca, Craiova, and Timisoara, trac management centers are used to monitor trac lights. In addition,
parking systems are available to oer citizens to pay for parking with short message service and identify the number of
accessible parking places in real-time. International standards were not discussed on how the services were managed
and achieved.
The Romanian Association for Smart City [96] is the leading authority of the Smart City Industry in Romania,
which consists of professionals and experts from various industries. The association is also supported by over 200
national and international partners. The association aims to create creative-intelligent communities in Romania and
achieve this by developing activities related to the Smart City ecosystem. The association has introduced 8 ISO
international standards in legislation, however, there are no details regarding them.
Alba Iulia is located in the west-central part of Romania. The pilot project Alba Iulia Smart City has many distinctive
features. The project promotes collaborative partnerships across governmental organizations, research institutions,
local administration, companies, universities, citizens, and associations. The partnerships are not driven by
commercial interests. The solutions are developed and examined by partner companies, with the local administration
providing the required support and infrastructure. It is worth mentioning that there is no technical standard discussed
for the Alba Iulia Smart City project [97].
Sweden
Stockholm aims to achieve environmental goals and ecient cooperation between various stakeholders,
including the private and public sectors [98]. Kista Science City is an important venue for ICT research and
development. The prominent ICT businesses including IBM and Ericsson settled in Kista during the 1970s and more
than 1000 other ICT companies have joined. The city hosts one of the world’s leading ICT clusters and largest urban
business districts. Rob
è
rt [
99
] examined a local travel planning network in Kista Science City where the travel demand
is probable to surpass the capacity of the transport system in the future. There is no information regarding the
standards adopted in Kista Science City.
United
Kingdom
Caird and Hallett [
9
] described that the British Standards Institution (BSI) collaborating with ISO has established a
substantial body of work on smart city standards and urban performance metrics. BSI is the leading organization in
developing smart city standards and urban performance metrics in the UK. Publicly Available Specification (PAS) 180
details industry-concurred understanding of smart city definitions and terms in the UK, to help developing a robust
foundation for imminent standardization and good practices [100]. PAS 180 also helps enhancing smart cities
understanding by setting a common language for designers, developers, clients, and manufacturers. The standard will
support industry to work more eectively and eciently and reduce the probabilities of confusion in the supply chain.
PAS 180 defines terms for smart cities encompassing smart city concepts for various infrastructure and systems’
components. It covers processes, materials, applications, and methodologies.
PAS 181 is a smart city framework for city leaders to create, concur and provide smart city strategies that can assist
transform their city’s capability to encounter its impending challenges and deliver its potential aspirations [101].
The smart city framework is based on current good practices and is a set of dependable and repeatable tasks that city
leaders can use to support create and execute their smart city plans. The framework does not expect to describe a
one-size-fits-all model for the UK cities. PAS 181 emphases on the enabling processes for the pioneering usage of data
and technology, composed with organizational modification, can assist deliver the varied visions for potential UK
cities in increased ecient, sustainable, and eective habits.
Manchester CityVerve [102] uses IoTs technologies to transform the city. The program focuses on four aspects of
transformation including “culture and public realm”, “energy and environment”, “health and social care”, and “travel
and transport”. Milton Keynes is a fast-growing city in the UK. MK:Smart [103] is a large collaborative initiative to
develop innovative solutions to support economic growth in Milton Keynes. The state-of-the-art ‘MK Data Hub’ plays
a critical role in the project which facilitates the acquisition and management of big data of city systems from numerous
data sources. The data concerns with energy and water consumption, transport data, data from satellite technology,
economic and social datasets, and crowdsourced data from social media or specialised apps. Caird and Hallett [9]
examined both projects and concluded that the city authorities were unfamiliar with the smart city indicator
frameworks [9].
Clean Technol. 2020,2304
Table 9. Smart cities pilot projects in North America and South America
Country Description
Brazil
Macke et al. [
104
] described that the city of Curitiba, Southern Brazil to be a green, inclusive and livable city. It is
the top ten smartest cities globally speaking. Curitiba has several well-known sustainability programs.
Eective leadership and devotion to intelligent transportation planning aided Curitiba to turn into a sustainable city
and a standard for eective urban planning. The city’s achievements are considered in six factors namely integrated
urban planning, pedestrian priority zones, environmental awareness, waste management system, eective public
transport system, and social justice. Smart living can be attained by delivering the four factors namely, community
integration socio-structural relations, material well-being, and environmental well-being. International standards are
not discussed in the work. Afonso et al. [105] studied Brazilian capital indicators and developed a maturity model
called Brazilian Smart City Maturity Model to allow transform public databases into useful indicators to assist city
managers in planning. The authors mentioned that the ISO 37120 standard provides 100 dierent performance
indicators for cities. The standard consists of 17 themes, 46 core indicators, and 54 indicators that can help define
public policies based on dierent domains. The model is an ongoing work.
Canada
The Smart Cities Challenge is a national competition open to all municipalities, local or regional governments and
indigenous communities [
106
]. The Challenge promotes communities to adopt a smart cities approach to enhance the
living standards of citizens through data, innovation, and connected technology. The Challenge aims to address four
areas including (1) to realize outcomes for residents; (2) empower communities to innovate; (3) forge new partnerships
and networks; (4) spread the benefit to all Canadians.
Edmonton is experiencing a resident-led digital transformation supported by the city’s council. The city developed the
Business Technology Strategy, the first-of-its-kind in Canada to guide data usages, dierent technologies, and business
solutions to enhance citizen’s life [
107
]. The Edmonton’s Smart City Strategy is an innovation ecosystem of academia,
government, residents and industry that abides by ISO 37106:2018. This standard is guidance for leaders in smart cities
and communities across the private, public and voluntary sectors concerning how to create a collaborative, open,
digitally enabled, and citizen-centric operating model for their city that drives a sustainable future. The standard
focuses on creating cities that (1) makes present and future citizen needs as the driver behind investment
decision-making, planning and delivery of entire city spaces and systems; (2) combine physical and digital planning;
(3) determine, foresee and react to emerging challenges in an agile, sustainable, and systematic manner; (4) develop
changes in the capacity for joined-up delivery and innovation within organizational boundaries for the city [108].
Saskatoon aims “to be the city that breaks the cycle of Indigenous youth incarceration by creating a new cycle focused
on building purpose, belonging, security and identity” [
109
]. The ConnectYXE initiative is based on three pillars (1) to
empower indigenous youth and their families by giving real-time information and choices for how to use services
across the city; (2) to work with partners by developing a data repository for all relevant programs and services
accessible; (3) to exploit innovative technology by connecting systems, distributing data and using artificial
intelligence. The collective data will give a city-wide image of what is accessible and the needs of those supports at all
times. This enables service providers and decision-makers to frequently study and recognise gaps, changes, and better
approaches to respond to the needs. Presently, technical standards were not discussed in the proposal for ConnectYXE.
United States
of America
New York aims to become an equitable and smart city to improve government services and citizens living
standards [
110
]. The transformation contains multiple programs including “New York City Connected Communities”,
where the government develops computer centers in the places with highly concentrated poverty rates. Over 100
centers have been developed, which have improved the level of digital literacy and enhanced the quality of life by
developing employment opportunities. The digital centers are in parks, computer resource centers, New York City
Housing Authority Centers, recreation centers, libraries, and senior citizen centers. Another initiative is “LinkNYC”
developed in 2014. The purpose was to develop a free ultra-high speed WiFi network to connect the whole city with
free high-speed internet service. The city has installed over 7500 communication junctions with free WiFi network,
domestic phone calls, and cell phone charging facility. Kansas City, Missouri is one of the smartest cities due to its
successful technology utilization [111]. Along the two-mile track of the Kansas City Streetcar, a 15 million USD
public-private partnership has facilitated the placement of 328 Wi-Fi access points, 178 smart streetlights that can
monitor trac patterns and available parking spaces, 25 video kiosks, pavement sensors, and video cameras. They are
all connected by the city’s fiber-optic data network. It was determined that the three smart city projects including New
York City Connected Communities, LinkNYC, and the Kansas City Streetcar have not discussed technical standards.
In summary, the review on some smart cities developments from various countries and
international standards shows:
1.
There is a lack of discussions on the use of international standards in implementing smart cities.
It is important to acknowledge the currently available standards in development when structuring
and developing a smart city.
2.
With standards and technologies are swiftly evolving, many cities need to avoid getting locked
into one vendor’s integrated solutions, which makes it more dicult for the city to share data
with citizens, developers, and other cities.
3.
International standards should be developed to address some of the most pressing challenges in
a smart city, including potential solutions to a pandemic such as COVID-19 [
112
]. In combating
COVID-19, ISO has made some standards freely available to the public, including ISO 13688:2013
(Protective clothing—General requirements) and ISO 19223:2019 (Lung ventilators and related
equipment—Vocabulary and semantics) [
113
]. Simultaneously, IEC also decided to make some
standards and most relevant normative references for critical care ventilators free of charge to
Clean Technol. 2020,2305
industries who are creating products or converting their existing assembly lines to ventilator
production [
114
]. In the current pandemic, many organizations and governments are sharing
or publishing data. For example, government health agencies are publishing data concerning
regional cases and deaths; symptom trackers are distributing data with researchers and making
data public; technology companies are obtaining mobility data which can help us to understand the
impact of the coronavirus on our lives. Standards need to support data interoperability, the ability
of services and systems that create, exchange, and use data to have clear, shared expectations for
the contents, context, and meaning of that data [115,116].
5. Conclusions
Smart cities are intelligent and sustainable cities. It is well-known that a smart city requires the
use of novel technologies, including robust ICT infrastructures and sensor devices. First, this paper
has revisited and identified some of the new smart city definitions. The definition of a smart city
is continuing to evolve, and one must accept that dierent terminologies exist due to the dierent
scope considered, e.g., the region and community involved. This paper then examines the smart city
from the view of international standards. It is identified that numerous international standards are
currently in development to develop a smart city and the old standards are being revised to become
relevant to address current society needs. Six smart city domains were identified including smart
energy, smart health, smart education, smart mobility, smart economy, and smart governance. There is
a need for researchers and city developers to acknowledge the dierent kinds of standards currently
available and in development, in order to build a city that is functional and sustainable. The review
identified that international standards are by no means as yet pervasive: there is a need for smart city
projects to present details on the international standards adoption, and its implications for a smart city.
Well-defined standards allow meaningful comparisons among smart cities implementation. With the
presence of many standard bodies, challenges exist if international standards are not agreed on by
standards developers and users. This paper serves as a guide on international standards for smart city
researchers and developers.
Author Contributions:
Conceptualization, C.S.L., Y.J., and Z.D.; formal analysis, C.S.L., Y.J., and Z.D.; resources,
A.F.Z., and L.L.L.; data curation, C.S.L., and Z.D.; writing—original draft preparation, C.S.L., Y.J., Z.D., Y.T., Q.H.L.;
writing—review and editing, D.W., R.T.K.W., A.F.Z., R.W., and L.L.L.; project administration, C.S.L.; funding
acquisition, C.S.L., and L.L.L. All authors have read and agreed to the published version of the manuscript.
Funding:
This research was funded by Brunel University London UK BRIEF Funding and the Education
Department of Guangdong Province: New and Integrated Energy System Theory and Technology Research Group
[Project Number 2016KCXTD022].
Acknowledgments:
The authors express gratitude to the Editor-in-Chief, Patricia Luis for the invitation to
contribute to the special issue entitled “Feature Papers 2020”. The authors are extremely grateful to Ronghui Liu
for her comments and suggestions on the work.
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
Smart Cities, International Electrotechnical Commission. Available online: https://www.iec.ch/smartcities/
introduction.htm (accessed on 7 August 2020).
2.
Gandy, O.H., Jr.; Nemorin, S. Toward a political economy of nudge: Smart city variations. Inf. Commun. Soc.
2019,22, 2112–2126. [CrossRef]
3.
Sadowski, J.; Pasquale, F.A. The spectrum of control: A social theory of the smart city. First Monday
2015
,20.
[CrossRef]
4.
Inclusive Smart Cities: A European Manifesto on Citizen Engagement. Available online:
https://eu-smartcities.eu/sites/default/files/2017-09/EIP-SCC%20Manifesto%20on%20Citizen%
20Engagement%20%26%20Inclusive%20Smart%20Cities_0.pdf (accessed on 7 August 2020).
5.
Ageing and Life-Course. Available online: https://www.who.int/ageing/projects/age-friendly-environments/
en (accessed on 7 August 2020).
Clean Technol. 2020,2306
6. Van Zoonen, L. Privacy concerns in smart cities. Gov. Inf. Q. 2016,33, 472–480. [CrossRef]
7.
Lai, C.S.; Lai, L.L.; Lai, Q.H. Smart Grids and Big Data Analytics for Smart Cities, 1st ed.; Springer International
Publishing: New York, NY, USA, 2020.
8. Camero, A.; Alba, E. Smart City and information technology: A review. Cities 2019,93, 84–94. [CrossRef]
9.
Caird, S.P.; Hallett, S.H. Towards evaluation design for smart city development. J. Urban Des.
2019
,24,
188–209. [CrossRef]
10.
ISO/TR 37150:2014(en) Smart Community Infrastructures—Review of Existing Activities Relevant to Metrics.
Available online: https://www.iso.org/obp/ui/#iso:std:iso:tr:37150:ed-1:v1:en (accessed on 7 August 2020).
11.
ISO/TS 37151:2015 Smart Community Infrastructures—Principles and Requirements for Performance Metrics.
Available online: https://www.iso.org/standard/61057.html (accessed on 7 August 2020).
12. Citykeys. Available online: http://citykeys-project.eu (accessed on 7 August 2020).
13.
Hasija, S.; Shen, Z.-J.M.; Teo, C.-P. Smart city operations: Modeling challenges and opportunities. Manuf. Serv.
Oper. Manag. 2020,22, 203–213. [CrossRef]
14.
Anthopoulos, L. Smart City Emergence: Cases From Around the World; Elsevier: Amsterdam, The Netherlands,
2019.
15.
van Winden, W.; van den Buuse, D. Smart city pilot projects: Exploring the dimensions and conditions of
scaling up. J. Urban Technol. 2017,24, 51–72. [CrossRef]
16. Deakin, M.; Al Waer, H. From intelligent to smart cities. Intell. Build. Int. 2011,3, 140–152. [CrossRef]
17.
Chamran, M.K.; Yau, K.-L.A.; Noor, R.; Wong, R. A Distributed Testbed for 5G Scenarios: An Experimental
Study. Sensors 2020,20, 18. [CrossRef]
18. Deakin, M. Smart Cities: Governing, Modelling and Analysing the Transition; Routledge: Oxford, UK, 2013.
19.
ASEAN Smart Cities Framework. Available online: https://asean.org/storage/2019/02/ASCN-ASEAN-Smart-
Cities-Framework.pdf (accessed on 7 August 2020).
20.
Smart Cities Overview—Guide, BSI Standards Publication. Available online: http://shop.bsigroup.com/
upload/Shop/Download/PAS/30313208-PD8100-2015.pdf (accessed on 7 August 2020).
21.
Department for Business Innovation & Skills Smart Cities: Background Paper. Available online:
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/
246019/bis-13-1209-smart- cities-background-paper-digital.pdf (accessed on 7 August 2020).
22.
European Comission Smart Cities. Available online: https://ec.europa.eu/info/eu-regional-and-
urban-development/topics/cities-and-urban- development/city-initiatives/smart-cities_en (accessed on
7 August 2020).
23.
Oce of the Government Chief Information Vision & Mission. Available online: https://www.smartcity.gov.
hk/vision/(accessed on 7 August 2020).
24.
IEEE Smart Cities. Available online: https://smartcities.ieee.org/images/files/pdf/IEEE_Smart_Cities-_Flyer_
Nov_2017.pdf (accessed on 7 August 2020).
25.
Strategic Business Plan (SBP) SMB/6817/R, International Electrotechnical Commission. Available online:
https://www.iec.ch/public/miscfiles/sbp/SYCSMARTCITIES.pdf (accessed on 7 August 2020).
26.
Jpan Smart Community Alliance Smart Community Development. Available online: https://www.smart-
japan.org/english/(accessed on 7 August 2020).
27.
Ministry of Housing and Urban Aairs Government of India Smart Cities Mission. Available online:
http://smartcities.gov.in/content/innerpage/what-is-smart-city.php (accessed on 7 August 2020).
28.
Deloitte Define Your Smart City Strategy. Available online: https://www2.deloitte.com/us/en/pages/
consulting/solutions/smart-cities-strategies.html (accessed on 7 August 2020).
29.
Fedorova, E.; Cal
ó
, A.; Pongr
á
cz, E. Balancing Socio-Eciency and Resilience of Energy Provisioning on a
Regional Level, Case Oulun Energia in Finland. Clean Technol. 2019,1, 273–293. [CrossRef]
30.
Lai, C.S.; Jia, Y.; Lai, L.L.; Xu, Z.; McCulloch, M.D.; Wong, K.P. A comprehensive review on large-scale
photovoltaic system with applications of electrical energy storage. Renew. Sustain. Energy Rev.
2017
.
[CrossRef]
31.
Xu, X.; Jia, Y.; Xu, Y.; Xu, Z.; Chai, S.; Lai, C.S. A Multi-agent Reinforcement Learning based Data-driven
Method for Home Energy Management. IEEE Trans. Smart Grid 2020,11, 3201–3211. [CrossRef]
32.
Wang, D.; Wu, R.; Li, X.; Lai, C.S.; Wu, X.; Wei, J.; Xu, Y.; Wu, W.; Lai, L.L. Two-stage optimal scheduling of
air conditioning resources with high photovoltaic penetrations. J. Clean. Prod. 2019. [CrossRef]
Clean Technol. 2020,2307
33.
Vaccaro, A.; Pisica, I.; Lai, L.L.; Zobaa, A.F. A review of enabling methodologies for information processing
in smart grids. Int. J. Electr. Power Energy Syst. 2019,107, 516–522. [CrossRef]
34.
Lasi, H.; Fettke, P.; Kemper, H.-G.; Feld, T.; Homann, M. Industry 4.0. Bus. Inf. Syst. Eng.
2014
,6, 239–242.
[CrossRef]
35.
Dong, Z.; Lai, C.S.; He, Y.; Qi, D.; Duan, S. Hybrid dual-complementary
metal–oxide–semiconductor/memristor synapse-based neural network with its applications in image
super-resolution. IET Circuits Devices Syst. 2019,13, 1241–1248. [CrossRef]
36.
Dong, Z.; Lai, C.S.; Qi, D.; Xu, Z.; Li, C.; Duan, S. A general memristor-based pulse coupled neural network
with variable linking coecient for multi-focus image fusion. Neurocomputing 2018. [CrossRef]
37.
Taha, A.; Wu, R.; Emeakaroha, A.; Krabicka, J. Reduction of electricity Costs in Medway NHS by inducing
pro-environmental behaviour using persuasive technology. Future Cities Environ. 2018,4, 1–10. [CrossRef]
38.
Guerrero-Ibanez, J.A.; Zeadally, S.; Contreras-Castillo, J. Integration challenges of intelligent transportation
systems with connected vehicle, cloud computing, and internet of things technologies. IEEE Wirel. Commun.
2015,22, 122–128. [CrossRef]
39.
Yin, J.; Su, S.; Xun, J.; Tang, T.; Liu, R. Data-driven approaches for modeling train control models: Comparison
and case studies. ISA Trans. 2019. [CrossRef]
40.
Hoel, T.; Mason, J. Standards for smart education–towards a development framework. Smart Learn. Environ.
2018,5, 3. [CrossRef]
41.
Ginger, R.; Christian, F.; Hans, K.; Kalasek, R.; Pichler-Milanovi´c, N.; Evert, M. Smart Cities: Ranking of
European Mid-Sized Cities. Available online: https://ec.europa.eu/digital-agenda/en/smart- cities (accessed on
7 August 2020).
42.
Hitachi Smart Water in Smart Cities. Available online: https://www.hitachi.eu/en-gb/social-innovation-
stories/communities/smart-water-smart-cities (accessed on 7 August 2020).
43.
Hope, R.; Foster, T.; Money, A.; Rouse, M.; Money, N.; Thomas, M. Smart Water Systems, Project Report to UK
Department for International Development. Available online: https://assets.publishing.service.gov.uk/media/
57a08ab9e5274a31e000073c/SmartWaterSystems_FinalReport-Main_Reduced__April2011.pdf (accessed on 7
August 2020).
44.
Case Study Summary: Smart Health. Available online: https://ec.europa.eu/growth/content/smart-health_en
(accessed on 7 August 2020).
45.
Smart Health Communities and the Future of Health. Available online: https://www2.deloitte.com/
content/dam/Deloitte/lu/Documents/life-sciences-health-care/lu-smart-health-communities.pdf (accessed on
7 August 2020).
46.
Gov.UK £1 Million Boost for UK Smart Waste Tracking. Available online: https://www.gov.uk/government/
news/1-million-boost-for-uk-smart-waste-tracking (accessed on 7 August 2020).
47.
Smart Waste Interreg Europe Innovation in Waste Management Policies. Available online: https://www.
interregeurope.eu/smartwaste/(accessed on 7 August 2020).
48. Swan, M. Blockchain: Blueprint for A New Economy; O’Reilly Media, Inc.: Sebastopol, CA, USA, 2015.
49.
What Are Smart Cities? Available online: https://www.iso.org/sites/worldsmartcity/(accessed on
7 August 2020).
50. Standards. Available online: https://www.iso.org/standards.html (accessed on 7 August 2020).
51. About the IEC. Available online: https://www.iec.ch/about/(accessed on 7 August 2020).
52.
About International Telecommunication Union (ITU). Available online: https://www.itu.int/en/about/Pages/
default.aspx (accessed on 7 August 2020).
53.
World Council on City Data ISO 37120. Available online: https://www.dataforcities.org (accessed on
7 August 2020).
54.
Editorial Team Standards Support Smart Cities. Available online: https://blog.iec.ch/2019/07/standards-
support-smart-cities/(accessed on 7 August 2020).
55.
Sang, Z.; Li, K. ITU-T standardisation activities on smart sustainable cities. IET Smart Cities
2019
,1, 3–9.
[CrossRef]
56.
IEEE Standards Association. IEEE 802
®
—Keeping the World Connected. Available online: https://standards.
ieee.org/featured/802/index.html (accessed on 7 August 2020).
57. About IEEE Smart Cities. Available online: https://smartcities.ieee.org/about (accessed on 7 August 2020).
Clean Technol. 2020,2308
58.
IEEE Standards Association. P2784—Guide for the Technology and Process Framework for Planning a Smart
City. Available online: https://standards.ieee.org/project/2784.html (accessed on 7 August 2020).
59.
IEEE Standards Association. 1889–2018—IEEE Guide for Evaluating and Testing the Electrical Performance
of Energy Saving Devices. Available online: https://standards.ieee.org/content/ieee-standards/en/standard/
1889-2018.html (accessed on 7 August 2020).
60.
IEEE Standards Association. P1922.1—Standard for a Method for Calculating Anticipated Emissions Caused
by Virtual Machine Migration and Placement. Available online: https://standards.ieee.org/project/1922_1.html
(accessed on 7 August 2020).
61.
IEEE Standards Association. P2814—Techno-economics Metrics Standard for Hybrid Energy and Storage
Systems. Available online: https://standards.ieee.org/project/2814.html (accessed on 7 August 2020).
62.
IEEE Standards Association. P2852—Intelligent Assessment of Safety Risk for Overhead Transmission
Lines under Multiple Operating Conditions. Available online: https://standards.ieee.org/project/2852.html
(accessed on 7 August 2020).
63.
IEEE Standards Association. 1708–2014—IEEE Standard for Wearable Cuess Blood Pressure Measuring
Devices. Available online: https://standards.ieee.org/standard/1708-2014.html (accessed on 7 August 2020).
64.
IEEE Standards Association. P3333.2.5—Standard for Bio-CAD File Format for Medical Three-Dimensional
(3D) Printing. Available online: https://standards.ieee.org/project/3333_2_5.html (accessed on 7 August 2020).
65. IEEE Standards Association. P1752—Standard for Mobile Health Data. Available online: https://standards.
ieee.org/project/1752.html (accessed on 7 August 2020).
66.
IEEE Standards Association. 1847–2019—IEEE Recommended Practice for Common Framework of Location
Services for Healthcare. Available online: https://standards.ieee.org/standard/1847-2019.html (accessed on
7 August 2020).
67.
IEEE Standards Association. P2621.1—Standard for Wireless Diabetes Device Security Assurance:
Product Security Evaluation Program. Available online: https://standards.ieee.org/project/2621_1.html
(accessed on 7 August 2020).
68.
IEEE Standards Association. P1884—Guide for Stray Current /Corrosion Mitigation for DC Rail Transit
Systems. Available online: https://standards.ieee.org/project/1884.html (accessed on 7 August 2020).
69.
IEEE Standards Association. P1883—Recommended Practice for Electrical and Electro-Mechanical Bench
Test Equipment (BTE) for Transit Rail Projects. Available online: https://standards.ieee.org/project/1883.html
(accessed on 7 August 2020).
70.
IEEE Standards Association. P2406—IEEE Draft Standard for Design and Construction of Non-Load
Break Disconnect Switches for Direct Current Applications on Transit Systems. Available online: https:
//standards.ieee.org/project/2406.html (accessed on 7 August 2020).
71.
IEEE Standards Association. P2020—Standard for Automotive System Image Quality. Available online:
https://standards.ieee.org/project/2020.html (accessed on 7 August 2020).
72.
IEEE Standards Association. P2685—Recommended Practice for Energy Storage for Stationary
Engine-Starting Systems. Available online: https://standards.ieee.org/project/2685.html (accessed on
7 August 2020).
73.
IEEE Standards Association. P7919.1—Requirements for eReaders to Support Learning Applications.
Available online: https://standards.ieee.org/project/7919_1.html (accessed on 7 August 2020).
74.
IEEE Standards Association. P2834—Standard for Secure and Trusted Learning Systems. Available online:
https://standards.ieee.org/project/2834.html (accessed on 7 August 2020).
75.
IEEE Standards Association. 1876–2019—IEEE Standard for Networked Smart Learning Objects for
Online Laboratories. Available online: https://standards.ieee.org/standard/1876-- 2019.html (accessed on
7 August 2020).
76.
IEEE Standards Association. 1589–2020—IEEE Standard for Augmented Reality Learning Experience Model.
Available online: https://standards.ieee.org/standard/1589--2020.html (accessed on 7 August 2020).
77.
IEEE Standards Association. P7005—Standard for Transparent Employer Data Governance. Available online:
https://standards.ieee.org/project/7005.html (accessed on 7 August 2020).
78.
IEEE Standards Association. P7004—Standard for Child and Student Data Governance. Available online:
https://standards.ieee.org/project/7004.html (accessed on 7 August 2020).
79.
IEEE Standards Association. P2145—Standard for Framework and Definitions for Blockchain Governance.
Available online: https://standards.ieee.org/project/2145.html (accessed on 7 August 2020).
Clean Technol. 2020,2309
80.
IEEE Standards Association. P2863—Recommended Practice for Organizational Governance of Artificial
Intelligence. Available online: https://standards.ieee.org/project/2863.html (accessed on 7 August 2020).
81. SmartCity. Available online: https://www.konza.go.ke/smart-city/(accessed on 7 August 2020).
82.
Slavova, M.; Okwechime, E. African smart cities strategies for Agenda 2063. Afr. J. Manag.
2016
,2, 210–229.
[CrossRef]
83.
Smart City. Available online: http://www.sun.ac.za/english/faculty/eng/ssml/research-focus/smart-city
(accessed on 7 August 2020).
84.
Security & Compliance Center. Available online: https://www.alibabacloud.com/trust-center (accessed on
7 August 2020).
85.
Our Vision Is to Make Dubai the Happiest City on Earth. Available online: https://www.smartdubai.ae
(accessed on 7 August 2020).
86.
Khan, M.S.; Woo, M.; Nam, K.; Chathoth, P.K. Smart city and smart tourism: A case of Dubai. Sustainability
2017,9, 2279. [CrossRef]
87.
Smart Dubai and Dubai Economy Launch New Data Initative for Retail Sector. Available online:
https://www.smartdubai.ae/newsroom/news/smart-dubai-and-dubai- economy-launch-new- data-
initiative-for-retail-sector (accessed on 7 August 2020).
88.
Oce of the Government Chief Information Ocer The Government of the Hong Kong Special Administrative
Region. Available online: https://www.ogcio.gov.hk/en/about_us/facts/doc/Fact_Sheet-OGCIO-EN.pdf
(accessed on 7 August 2020).
89.
Ma, R.; Lam, P.T.I. Investigating the barriers faced by stakeholders in open data development: A study on
Hong Kong as a “smart city”. Cities 2019,92, 36–46. [CrossRef]
90. Toyota Woven City. Available online: https://www.woven-city.global (accessed on 7 August 2020).
91.
Toyota to Build A Hydrogen-Powered City of the Future. Available online: https://blog.toyota.co.uk/toyota-
woven-city-hydrogen-power (accessed on 7 August 2020).
92. Cities. Available online: https://www.infrastructure.gov.au/cities/(accessed on 7 August 2020).
93.
Smart Cities. Available online: https://www.standards.org.au/engagement-events/flagship-projects/smart-
cities (accessed on 7 August 2020).
94.
Bakıcı, T.; Almirall, E.; Wareham, J. A smart city initiative: The case of Barcelona. J. Knowl. Econ.
2013
,4,
135–148. [CrossRef]
95.
Pop, M.-D.; Pro
s
,
tean, O. A comparison between smart city approaches in road trac management. Procedia Soc.
Behav. Sci. 2018,238, 29–36. [CrossRef]
96.
The Romanian Association for Smart City. Available online: https://romaniansmartcity.ro (accessed on
7 August 2020).
97.
World Bank Group. The City of Alba Iulia Alba Iulia Project Prioritization for 2014–2020.
Available online: http://documents1.worldbank.org/curated/en/527401468190739988/pdf/Alba-Iulia-project-
prioritization-for-2014-2020.pdf (accessed on 7 August 2020).
98.
The Smart City. Available online: https://international.stockholm.se/city-development/the-smart-city/
(accessed on 7 August 2020).
99.
Rob
è
rt, M. Engaging private actors in transport planning to achieve future emission targets—upscaling the
Climate and Economic Research in Organisations (CERO) process to regional perspectives. J. Clean. Prod.
2017,140, 324–332. [CrossRef]
100.
PAS 180 Smart Cities Vocabulary. Available online: https://www.bsigroup.com/en-GB/smart-cities/Smart-
Cities-Standards-and-Publication/PAS-180-smart- cities-terminology/(accessed on 7 August 2020).
101.
PAS 181 Smart City Framework. Available online: https://www.bsigroup.com/en-GB/smart-cities/Smart-
Cities-Standards-and-Publication/PAS-181-smart- cities-framework/(accessed on 7 August 2020).
102.
What is CityVerve. Available online: https://cityverve.org.uk/what-is-cityverve/(accessed on 7 August 2020).
103. About MKSmart. Available online: http://www.mksmart.org/about/(accessed on 7 August 2020).
104.
Macke, J.; Casagrande, R.M.; Sarate, J.A.R.; Silva, K.A. Smart city and quality of life: Citizens’ perception in a
Brazilian case study. J. Clean. Prod. 2018,182, 717–726. [CrossRef]
105.
Afonso, R.A.; dos Santos Brito, K.; do Nascimento, C.H.; Garcia, V.C.;
Á
lvaro, A. Brazilian Smart Cities:
Using a Maturity Model to Measure and Compare Inequality in Cities. In Proceedings of the 16th Annual
International Conference on Digital Government Research; Association for Computing Machinery: New York,
NY, USA, 2015; pp. 230–238.
Clean Technol. 2020,2310
106.
Smart Cities Challenge. Available online: https://www.infrastructure.gc.ca/cities-villes/index-eng.html
(accessed on 7 August 2020).
107.
Smart City Challenge Edmonton Final Proposal. Available online: https://www.edmonton.ca/city_
government/documents/CityofEdmontonSmartCitiesProposal_21MB.pdf (accessed on 7 August 2020).
108.
ISO 37106:2018(en) Sustainable Cities and Communities—Guidance on Establishing Smart City Operating
Models for Sustainable Communities. Available online: https://www.iso.org/obp/ui/#iso:std:iso:37106:ed-1:
v1:en (accessed on 7 August 2020).
109.
Connectyxe SmartCitiesChallenge. Available online: https://www.saskatoon.ca/sites/default/files/documents/
corporate-performance/communications/Engagement/connectyxe_saskatoon_march_5_2019.pdf
(accessed on 7 August 2020).
110.
The Equitable City—A New Name for New York. Available online: https://www.smartcity.press/new-yorks-
smart-city-initiatives/(accessed on 7 August 2020).
111.
Smart Cities and the Journey to the “Cloud”. Available online: https://www2.deloitte.com/content/
dam/Deloitte/us/Documents/about-deloitte/us-about-deloitte- smart-cities-journey- cloud.pdf (accessed on
7 August 2020).
112.
Andersen, K.G.; Rambaut, A.; Lipkin, W.I.; Holmes, E.C.; Garry, R.F. The proximal origin of SARS-CoV-2.
Nat. Med. 2020,26, 450–452. [CrossRef]
113.
COVID-19 Response: Freely Available ISO Standards. Available online: https://www.iso.org/covid19
(accessed on 7 August 2020).
114.
Access to Key Standards for Critical Care Ventilators. Available online: https://webstore.iec.ch/webstore/
webstore.nsf/xpFAQ.xsp?OpenXPage&id=GFOT-BNAEXA (accessed on 7 August 2020).
115.
Thereaux, O. Data and Covid-19: Why Standards Matter. Available online: https://theodi.org/article/data-
and-covid-19-why- standards-matter/(accessed on 7 August 2020).
116.
What is “Data Interoperability”. Available online: https://datainteroperability.org (accessed on 7 August 2020).
©
2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
... Fatores como o crescente aumento da população nas áreas urbanas, o aumento da poluição do ar, constrangimentos decorrentes do excesso de turismo (overtourism) e o dilema do aquecimento global têm sido apontados como argumentos para a implementação de estratégias inteligentes em várias cidades e países (El Ghorab & Shalaby, 2016). Estas encontram no uso da tecnologia e dos dados uma via para aumentar a eficiência, o desenvolvimento económico, a sustentabilidade e a qualidade de vida dos seus cidadãos (Lai et al., 2020). Ainda que o modelo de smart city tenha maior probabilidade de se adequar às grandes cidades, importa discutir a sua aplicabilidade, também, a pequenas e médias cidades, pelas oportunidades e possibilidades de desenvolvimento que pode apresentar. ...
... É consensual afirmar que não existe uma definição precisa de smart city (Aldegheishem, 2019;Anthopoulos, 2015;Gracias et al., 2023;Kummitha & Crutzen, 2017;Lai et al., 2020). Apesar do interesse crescente entre vários atores e dos esforços para promover a sua prática, tem havido inúmeras críticas ao conceito e à forma como este tem sido adotado e implementado (Hollands, 2008;Kummitha & Crutzen, 2017;Söderström et al., 2014). ...
... Desconsiderando as controvérsias relativamente ao conceito propriamente dito, é comummente aceite que o conceito de smart city está associado ao uso de tecnologias digitais, TICs e análise de dados, capazes de criar um ambiente de serviço eficaz e eficiente que melhore a qualidade de vida urbana e promova a sustentabilidade (Gracias JANUS (Sansaverino et al., 2014). Não obstante as várias abordagens desenvolvidas para definir e avaliar smart cities, académicos, organizações profissionais e agências governamentais, apresentando algumas variações, têm concordado com a associação do conceito a 6 dimensões principais: economia, pessoas, governação, mobilidade, ambiente e vida (Anthopoulos et al., 2016;Lai et al., 2020;Nevado Gil et al., 2020): ...
Article
A crescente massificação das zonas urbanas tem conduzido ao despovoamento das pequenas cidades e zonas rurais, já fragilizadas pela diminuição das infraestruturas e carência de competências digitais, colocando em causa o desenvolvimento sustentável dos territórios. O conceito de smart city, associado à capacidade das cidades aumentarem a eficiência, o desenvolvimento económico, a sustentabilidade e a qualidade de vida dos cidadãos através de TICs, tem-se restringido principalmente à escala urbana, carecendo de uma visão estratégica e territorial mais ampla. O objetivo deste artigo é proporcionar uma reflexão sobre a aplicação do conceito a uma escala mais abrangente através de modelos e estratégias diferenciadas. A questão central explorada foca-se em discutir se a cooperação entre municípios de cidades em áreas rurais ou de interior, desenvolvidas no âmbito de estratégias de marketing territorial assentes em soluções inteligentes, pode contribuir para revitalizar globalmente o território onde se inserem, posicionando-o como inteligente aos olhos dos vários stakeholders.
... This process is based on an adequate integration and management of information and communication technologies. (1,2) Smart cities are characterized by leveraging hardware and software infrastructures to obtain, process and efficiently use information, in addition to integrating and automating their basic systems such as transportation, water, energy, among others. The purpose is to improve citizens' well-being and the city's infrastructure, with a focus on its sustainability and productive vocation. ...
... (iii) The technology utilization process ensures that the acquired IT is effectively used to enhance and innovate the city's processes and intelligence. (2,27) ...
Article
Full-text available
The integration of information technology (IT) into urban processes can significantly enhance public management by providing objective and timely information for decision-making at all levels of governance. It facilitates the administration and control of city resources, strengthens processes, and fosters greater citizen participation, efficiency, and transparency in their execution. This article proposes an IT management framework aligned with the smart city concept. The framework was organized into three levels of IT management: strategic, tactical, and operational, which corresponded to the city's maturity, intelligence, and technology, respectively. The model was based on best practices, international IT standards, and recognized theories. It was developed from the results of an instrument designed to quantify the indicators of two research variables: IT management and smart city, applied to the governing bodies of the city of Santa Marta, Colombia. The analysis of the responses allowed us to quantitatively and qualitatively describe the research variables and their interrelations. It also enabled us to identify strengths and weaknesses in order to make recommendations to improve the technological state and the development of services that increase the level of intelligence from the city of Santa Marta.
... The model is ideal for large projects subject to substantial delay and commercial risks, with the client's employer retaining control to protect its own interests. It is popular in the USA and has been used in the UK since 1997 [42][43][44]. ...
... [43] [44] 6. Electronic Reverse Auction ...
Article
Full-text available
This paper highlights the transition from traditional procurement systems to the newly introduced eProcurement system in Saudi Arabia, emphasizing the differences and improvements and their implications for sustainable development. The new system aims to enhance transparency, clarify purchasing methodologies, and build trust with the government through effective governance of government purchases and tender management. Guided by Royal Decree, this system aligns with the eProcurement Program to transition into digital processes for proficient bids and government purchases, contributing to more efficient and sustainable procurement practices. While some public agencies have attempted to adopt the new model contract for executing construction projects, it has faced challenges due to its lack of alignment with the best practices and sustainability considerations. The authors argue that many large projects remain exempt from this system, which poses obstacles to achieving the goals of sustainable economic development. The objective of this paper is to explore the newly revised Saudi procurement contracts in comparison with traditional public works contracts, with a focus on how they address socio-economic and environmental sustainability. The research provides an overview of various aspects related to public works contracts (PWCs) in Saudi Arabia, including framework agreements, online reverse auctions, industry localization, knowledge transfer, traditional lump sum contracts, two-phase tenders, and construction project competitions, analyzing their alignment with sustainable development goals. There is limited literature on recent models introduced by the Saudi government, but there are extensive resources on general contract law principles and international public policy. This foundation helps with understanding the legal aspects of public works contracts in Saudi Arabia, their alignment with international standards, and their implications for fostering sustainable development. By examining the literature, researchers can gain insights into the legal and policy framework governing public works contracts in Saudi Arabia and their role in promoting sustainability. The importance of this research lies in its comparative analysis, offering valuable insights into the evolution of procurement practices in Saudi Arabia and their contribution to sustainable socio-economic growth.
... Similarly, Fang and Shan (2024) further elaborated on a people-centered analysis methodology for smart city assessment. Their model aimed to maximize user experience while selecting the allocation of investments considering various aspects of smart cities (Lai et al., 2020;Neves et al., 2020;Yigitcanlar et al., 2022). The study developed efficiency evaluation and user demand models to test the analysis and determine the smart city's development direction and emphasis (Bellini et al., 2022;Guo & Zhong, 2022;Patrão et al., 2020;Sharifi, 2020). ...
Article
Full-text available
This study employs Data Envelopment Analysis (DEA) to evaluate the efficiency of the top 20 smart cities in converting Research and Development (R&D) investments into desired outcomes. Using national R&D expenditure (2015–2022) as input and ten criteria from the IMD 2024 Smart City Index report as outputs, the analysis reveals varying levels of efficiency among leading smart cities. Seven cities achieved perfect efficiency scores, while others, including some high-ranking cities, showed unexpected inefficiencies. This study provides valuable insights into resource utilization and identifies specific areas for improvement across structural and technological dimensions. The limitations include the focus on top-performing cities and the use of national R&D data as a proxy for city-specific investments. The findings of this study offer a foundation for policymakers and urban planners to optimize resource allocation and improve smart city initiatives, contributing to the ongoing development of sustainable urban environments in the face of technological advancements and urban challenges.
... With the rapid acceleration of urbanization and the rapid development of information technology in China, the construction of smart cities has become an important strategic choice to promote high-quality urban development. Smart cities, characterized by informatization, intelligence, and green low-carbon features, aim to enhance urban operational efficiency, improve residents' quality of life, and promote sustainable economic and social development [1][2][3][4][5][6][7]. However, the construction of smart cities in isolation is no longer sufficient to meet the needs of urban development, highlighting the importance of interconnection and coordinated development among cities. ...
Article
Full-text available
As urbanization has accelerated, China has started to build smart cities, which have formed smart-city clusters. It is critical to coordinate development within smart-city clusters to enhance the efficiency of city-cluster construction. From the perspective of demographic economics, this study innovatively constructed an evaluation system for the coordinated development of smart-city clusters and utilized the coupled coordination degree model to conduct an in-depth study of smart-city clusters in Jiangsu Province. The results show that there are clear differences in the development between the three regions of Jiangsu Province: Southern Jiangsu, Central Jiangsu, and Northern Jiangsu. The development within Jiangsu Province is imbalanced, where the overall development trend is high in the southern region and low in the northern region. The main driving factors include geography, the Matthew effect, game thinking, and industrial structure. Accordingly, the results suggest the following recommendations for the coordinated development of smart-city clusters: strengthening cross-regional cooperation, promoting data sharing and interoperability, deepening synergistic industrial development, and expanding innovation capacity.
... With the rapid advancement of information technology, smart cities have become a core strategy for promoting sustainable urban development. Smart cities not only enhance a city's overall competitiveness but also foster economic and social progress, paving the way for a PLOS ONE none green, intelligent, and sustainable future [1,2]. However, the development of smart cities is not confined to urban areas; the construction of smart villages, as an extension of smart city initiatives, is gradually becoming a crucial component of rural revitalization strategies. ...
Article
Full-text available
To achieve rural revitalization and enhance the development of rural tourism, this study employs a back propagation neural network (BPNN) to construct a rural revitalization development model. Additionally, the Grey Relation Analysis (GRA) algorithm is used to classify rural revitalization efforts across different cities. Consistency testing is applied to analyze rural revitalization indicators, and a tourism service evaluation model is established to assess rural revitalization tourism services from the perspective of smart cities. The research results indicate that: (1) the training results and expected values of the ten cities are relatively consistent, and the classification of rural revitalization development is good; (2) The five major indicators of tourism information services, tourism security services, tourism transportation services, tourism environment services, and tourism management services all meet the consistency test, and the consistency test results are all less than 0.1, confirming the reliability and effectiveness of the research data; (3) The tourism information and management services are mainly evaluated at level C, accounting for 62% and 62.5% respectively. The tourism transportation and safety services are mainly evaluated at level D, and the model can indicate the level of rural revitalization tourism service; (4) Compared with other algorithms, the GRA-BPNN algorithm performs the best in rural revitalization evaluation, with an accuracy of 92.3%, precision of 91.8%, recall rate of 93.7%, and F1 score of 92.7%. This study optimizes the rural revitalization tourism service platform, enhances the quality of rural tourism, promotes the development of the rural tourism industry, and contributes to the realization of rural revitalization.
Article
Full-text available
This paper proposes a novel framework for home energy management (HEM) based on reinforcement learning in achieving efficient home-based demand response (DR). The concerned hour-ahead energy consumption scheduling problem is duly formulated as a finite Markov decision process (FMDP) with discrete time steps. To tackle this problem, a data-driven method based on neural network (NN) and Q-learning algorithm is developed, which achieves superior performance on cost-effective schedules for HEM system. Specifically, real data of electricity price and solar photovoltaic (PV) generation are timely processed for uncertainty prediction by extreme learning machine (ELM) in the rolling time windows. The scheduling decisions of the household appliances and electric vehicles (EVs) can be subsequently obtained through the newly developed framework, of which the objective is dual, i.e. to minimize the electricity bill as well as the DR induced dissatisfaction. Simulations are performed on a residential house level with multiple home appliances, an EV and several PV panels. The test results demonstrate the effectiveness of the proposed data-driven based HEM framework.
Article
Full-text available
This paper demonstrates the use of Universal Software Radio Peripheral (USRP), together with Raspberry Pi3 B+ (RP3) as the brain (or the decision making engine), to develop a distributed wireless network in which nodes can communicate with other nodes independently and make decision autonomously. In other words, each USRP node (i.e., sensor) is embedded with separate processing units (i.e., RP3), which has not been investigated in the literature, so that each node can make independent decisions in a distributed manner. The proposed testbed in this paper is compared with the traditional distributed testbed, which has been widely used in the literature. In the traditional distributed testbed, there is a single processing unit (i.e., a personal computer) that makes decisions in a centralized manner, and each node (i.e., USRP) is connected to the processing unit via a switch. The single processing unit exchanges control messages with nodes via the switch, while the nodes exchange data packets among themselves using a wireless medium in a distributed manner. The main disadvantage of the traditional testbed is that, despite the network being distributed in nature, decisions are made in a centralized manner. Hence, the response delay of the control message exchange is always neglected. The use of such testbed is mainly due to the limited hardware and monetary cost to acquire a separate processing unit for each node. The experiment in our testbed has shown the increase of end-to-end delay and decrease of packet delivery ratio due to software and hardware delays. The observed multihop transmission is performed using device-to-device (D2D) communication, which has been enabled in 5G. Therefore, nodes can either communicate with other nodes via: (a) a direct communication with the base station at the macrocell, which helps to improve network performance; or (b) D2D that improve spectrum efficiency, whereby traffic is offloaded from macrocell to small cells. Our testbed is the first of its kind in this scale, and it uses RP3 as the distributed decision-making engine incorporated into the USRP/GNU radio platform. This work provides an insight to the development of a 5G network.
Article
Full-text available
Large-scale of controllable air conditioning loads have the potential to participate in distribution network operation via demand side control scheme. At the same time, distributed renewable energy resources are being deployed in distribution networks with increasing penetration rate. In this paper, a two-stage optimal scheduling method is proposed for distribution system with high photovoltaic penetration. The proposed scheduling method is decomposed into two stages to alleviate intra-day random variations of PV generation, electricity prices, and end-user load. In the day-ahead stage, this paper employs a mixed integer linear programming (MILP) method to achieve coordinated control of air conditioning loads, solar photovoltaic (PV) resources and battery energy storage systems (BESSs) under the target of minimizing system overall operation costs. A novel two-parameter lumped thermal model is introduced to more accurately describe the thermal dynamic process of the buildings, which is critical to meet the end users’ thermal comfort in control process. In the real-time stage, a rolling horizon optimization approach is applied for minimization of imbalance costs between the day-ahead energy market and real-time energy market. Simulations are conducted on a radial distribution network, whose results verify that the proposed method can effectively reduce operation cost, lower peak demand and improve the PV penetration level in the distribution network.
Article
Full-text available
The need to reduce CO2 emissions makes companies find new sustainable solutions for energy production. Diverse multiple sourcing energy production value chains became an important strategical development used at a regional level in Finland. This article presents a social sustainability state data visualization framework that allows us to communicate key social aspects to stakeholders and local communities. Core social aspects are defined through the assessment of multiple sourced electricity supply chains available within one region. This framework was tested on a case study covering regional electricity production supply chains in the Oulu sub-region, Finland. The evaluation of social indicators and their impacts presented along regional electricity production supply chains was performed via the conversion of collected data into visual objects. A cumulative social impact assessment of a local energy supply chain revealed that social sustainability impacts have the tendency to accumulate within the region. The results indicate that multiple sourced electricity supply chains are a socially sustainable solution that improve energy security and provide affordable electricity to local communities. The results indicate how by using multiple-sourcing value chains, companies can improve regional social resilience and balance socio-efficiency through building an effective relation between a company’s value added and its social impact on local communities.
Article
Full-text available
Biology‐inspired neural computing is a potential candidate for the implementation of next‐generation intelligent systems. Memristor is a passive electrical element with resistance‐switching dynamics. Owing to its natural advantages of non‐volatility, nanoscale geometries, and variable conductance, memristor can effectively simulate the synaptic connecting strength between the neurones in the multilayer neural networks. This study presents a kind of memristor synapse‐based multilayer neural network hardware architecture with a suitable training methodology. Specifically, a novel dual‐complementary metal–oxide–semiconductor/memristor synaptic circuit is presented, which is capable of performing the negative, zero, and positive synaptic weights via controlling the direction of current passing through the memristors. Then, the neurone circuit synthesised with multiple synaptic circuits and an activation unit is further designed, which can be utilised to constitute a compact multilayer neural network with fully connected configuration. Also, a hardware‐friendly chip‐in‐the‐loop training method is provided during the network training phase. For the verification purpose, the presented neural network is applied for the realisation of single image super‐resolution reconstruction.
Book
This book provides a comprehensive introduction to different elements of smart city infrastructure - smart energy, smart water, smart health, and smart transportation - and how they work independently and together. Theoretical development and practical applications are presented, along with related standards, recommended practices, and professional guidelines. Throughout the book, diagrams and case studies are provided that demonstrate the systems presented, and extensive use of scenarios helps readers better grasp how smart grids, the Internet of Things, big data analytics, and trading models can improve road safety, healthcare, smart water management, and a low-carbon economy. A must-read for practicing engineers, consultants, regulators, utility operators, and environmentalists involved in smart city development, the book will also appeal to city planners and designers, as well as upper-level undergraduate and graduate students studying energy, environmental science, technology, economics, signal processing, information science, and power engineering. • Provides a balanced approach of advanced theory and practical applications • Covers relevant standards, recommended practices, and professional guidelines • Extensive use of case studies and scenarios illuminate the systems presented
Article
We discuss some recent developments in smart city initiatives across the world to motivate the opportunities and challenges that such initiatives pose, and we categorize them into three themes: data access and collection, end-user utility, and economic viability of different solutions. We recognize that the academic literature that can help in addressing some of these challenges is at its nascent state and provide guidelines on how manufacturing and service operations management scholars can contribute to the global smart city movement.
Article
The drive towards open data aims at improving government transparency, motivating citizen participation and unlocking commercial innovation. However, various intertwining barriers hinder the adoption of open data. They are stemming from legislation and licensing, technology and operation, use level, institution and governance, as well as economic considerations. Through the use of social network analysis (SNA), this study identified 43 barriers faced by stakeholders in an open data project in Hong Kong and investigated their interdependencies. Hong Kong was selected as a representative case due to its relatively low ranking in the Global Open Data Index (24th) and poor data quality. It was found that the lack of an open data policy should be tackled as a matter of priority to provide technical guidance for the public sector, ensure data quality and achieve expected outcomes. It is also necessary to improve the IT literacy/mindset of the public sector, refine the governance structure relating to the delivery of open data initiatives, encourage engagement from private entities and provide a feedback loop for users. This study explored the interrelationships between various barriers to open data adoption and proposes practical recommendations to enhance open data development in the context of emerging “smart cities”.
Article
In railway systems, the train dynamics are usually affected by the external environment (e.g., snow and wind) and wear-out of on-board equipment, leading to the performance degradation of automatic train control algorithms. In most existing studies, the train control models were derived from the mechanical analyzation of train motors and wheel-track frictions, which may require many times of field trials and high costs to validate the model parameters. To overcome this issue, we record the explicit train operation data in Beijing Metro within three years and develop three data-driven approaches, involving a linear regression-based model (LAM), a nonlinear regression-based model (NRM), and furthermore a deep neural network based (DNN) model, where the LAM and NRM can act as benchmarks for evaluating DNN. To improve the training efficiency of DNN model, we especially customize the input and output layers of DNN, batch normalization based layers and network parameter initialization techniques according to the unique characteristics of railway train models. From the model training and testing results with field data, we observe that DNN significantly enhances the predicting accuracy for the train control model by using our customized network structure compared with LAM and NRM models. These data-driven approaches are successfully applied to Beijing Metro for designing efficient train control algorithms.