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QUANTUMTECHNOLOGIESFORSMARTCITIES:ACOMPREHENSIVE
REVIEWANDANALYSIS
MariaFedele
UNIVERSITYOFCASSINOANDSOUTHERNLAZIO,Italy
VincenzoFormisano
UNIVERSITYOFCASSINOANDSOUTHERNLAZIO,Italy
AysanBashirpourBonab
UNIVERSITYOFCASSINOANDSOUTHERNLAZIO,Italy
IhorRudko
BINORWEGIANBUSINESSSCHOOL,Norway
AccesstothispaperisrestrictedtoregistereddelegatesoftheEURAM2022(EuropeanAcademyofManagement)
Conference.
ISSN 2466-7498 and ISBN 978-2-9602195-4-8
1
Quantum technologies for smart cities: a comprehensive review and analysis
Abstract
Conventional smart city technologies are based on typical von Neumann architectures in which
single units of data are coded in the form of either “0” or “1.” Novel urban quantum
technologies, on the other hand, are based on the fundamental principles of quantum physics
and, thus, transcend the conventions of classic computer architectures. Although having
substantial technological potential and managerial relevance for smart cities of the near future,
they are still rarely investigated in smart city literature and, in general, as a breakthrough
business model. Moreover, no scholarly articles exist on the potential contributions of quantum
technologies to different facets of conventional smart city technologies, for example, cloud
computing, AI, and blockchain. This article aims to bridge the ontological gap between the two
types of urban technology. Accordingly, we perform a detailed thematic synthesis of two types
of quantum technologies having the highest implementation potential within different urban
infrastructures and, more generally, for thriving urban techno-systems: quantum computing
and quantum communication. This is achieved through a semi-systematic literature review of
80 scholarly documents on the topic within the domain of social sciences. Then, we establish a
comprehensive taxonomy of conventional (non-quantum) smart city technologies based on a
lexical analysis of over 500 abstracts of scholarly documents on different technological aspects
of smart cities. Finally, we relate the two classes of technologies—conventional smart city
technologies, and urban quantum technologies—through quantitative content analysis of 80
papers identified and retrieved for the prior thematic synthesis. For this goal, principal
component analysis is performed, complemented by agglomerative hierarchical clustering.
Keywords: smart city, quantum city, smart city technologies, quantum technologies, semi-
systematic literature review, urban management
2
1. Introduction
Traditional Newtonian city conceptualizations, common in twentieth-century urban theory, are
becoming increasingly unable to deal with the complexity, uncertainty, high risk, and
sometimes even undecidability of contemporary cities (Arida, 2002; Formisano, Fedele, Rudko,
et al., 2021; Macionis & Parrillo, 2017). As the big functionalist narratives of the past lose their
explanatory powers in the new millennium, new city metaphors are required (Lynch, 1984,
1990).
The shifts in the urban sphere can be attributed to various social, economic, demographic, and
technical factors. Moreover, urban-related technological changes can be further divided into
two categories:
• First, the shift toward smart cities and, more generally, sustainable smart city techno-
systems (Formisano, Fedele, & Bashirpour Bonab, 2021). The rate at which an urban region
invests in implementing, using, and expanding smart novel technologies is inextricably
linked to the city’s development. Furthermore, these technologies are a critical component
of urban sustainability (Gouvea et al., 2018). Accordingly, smart technologies such as ICT,
AI, IoT, Blockchain, and Big Data (Bibri, 2018; Bifulco et al., 2016; Quan et al., 2019) play
a critical role in developing smart sustainable cities.
• Second, the shift toward quantum cities. The quantum paradigm is better understood as a
novel metaphorical basis for examining contemporary cities and increasingly complex
urban life. The quantum metaphor, rich in insights and misconceptions, heavily incorporates
language and imagery from physics (Arida, 2002). The Quantum City concept is based on
a set of fundamental laws of quantum mechanics that could help forecast the future
conditions of an urban system with greater accuracy. To achieve the vision of Quantum
3
City, the broader public must willingly adopt quantum technologies and comprehend the
hazards and benefits they may bring to everyday life (Arida, 2002).
Nevertheless, due to the complexities of quantum theory, the notion of Quantum City could be
challenging to communicate appropriately to the public. However, with the increasing scientific
interest in quantum technologies (QTs) and their impact on the future, it is essential to engage
the end-users with reasonable explanations, examples, and metaphors. Only the proper
educational approach toward quantum technologies can positively shape the public’s perception
of a potential quantum urban reality (Arida, 1998, 2002). Hence, the recent implementations of
“prototypical” quantum cities (like Hefei in China) primarily serve as a proof-of-concept of the
urban future and inform the broader public on the use and importance of quantum technologies.
Regardless of the high potential for synergies, two types of technologies, conventional smart
city technologies and urban quantum technologies, have been (so far) studied disjointly. As a
result, the lack of scholarly contributions to understanding the relationships between quantum
technologies and technologies used in smart cities is evident. This article tries to shed light on
this gap.
The article represents the first attempt to reconcile the two types of technologies on both
epistemological and ontological plains. For this purpose, we will first perform a thorough
thematic synthesis of urban quantum technologies through the semi-systematic literature of 80
scholarly records on the topic. Then, we will first derive a comprehensive taxonomy of
conventional (non-quantum) smart city technologies based on the lexical analysis of more than
500 abstracts of articles on technological aspects of smart cities. Finally, we will explore the
thematic relationships between two facets of quantum technologies (quantum communication
and computing) and seven types of smart city technologies within the primarily selected 80
scholarly records through principal component analysis, complemented by agglomerative
hierarchical clustering.
4
2. A semi-systematic literature review of quantum technologies for urban contexts
2.1 Quantum technologies in Quantum Cities: identification and selection of records
Comprehensive taxonomies of quantum technologies are still rare in the literature. Among the
few existing, the one by Acín et al. (2018) is probably the most succinct, albeit all-inclusive.
The authors (Acín et al., 2018) distinguish four types of quantum technologies:
• Quantum communication, in which entangled photons are used to transmit data securely;
• Quantum simulation, in which quantum systems are used to reproduce the behavior of
other, unavailable quantum systems;
• Quantum computation, in which quantum physics is employed to speed up specific types
of calculations;
• Quantum sensing and metrology, in which the higher sensitivity of quantum systems to
outside perturbations is used to increase the sensitivity of physical quantities measurements.
Accordingly, to investigate which types—among the above four—are of the potential usage in
smart cities, a search was performed on Scopus, adopting the above taxonomy as a basis for
keywords. The choice of Scopus comes from the suggestion of Gusenbauer and Haddaway
(2020). According to the authors, Scopus is a suitable primary search engine for the goals of
systematic and semi-systematic literature reviews in the fields of business and management
(Gusenbauer & Haddaway, 2020).
Five separate searches were performed (“quantum communication,” “quantum simulation,”
“quantum computation,” “quantum sensing,” and “quantum metrology”). The “in-title”
specifier was used, and the results were restricted to the domains of “Social Sciences,”
“Business, Management and Accounting,” “Decision Sciences,” and “Economics,
Econometrics, and Finance.” No restrictions on the types of documents were used, allowing for
the interesting “gray” literature to emerge.
5
PRISMA 2020 guidelines for the stages of identification, screening, eligibility assessment, and
inclusion of records were strictly followed (Page et al., 2021). Figure 1 shows the PRISMA-
based chart of the four selection stages. As seen in the figure, 82 records were retrieved in the
end. However, two papers were counted twice—separately for the quantum communication and
computing domains—bringing the total number of analyzed records down to 80.
Figure 1. Criteria of identification and selection of scholarly records
A subsequent thematic analysis of the results revealed quantum computing and quantum
communication as the only relevant types of QTs potentially applicable in an urban context.
Conversely, in the process of deductive coding, quantum sensing and quantum metrology have
not emerged as separate significant categories.
What follows is the qualitative thematic synthesis of the retrieved scholarly records concerning
quantum communication and quantum computing and their relevance in the context of urban
management literature.
6
2.2 Quantum communication in Quantum Cities: a thematic synthesis
Quantum communication in the urban context is concerned with securely transferring and
exchanging quantum information between distant city network nodes connected via quantum
channels, which are used to send qubits (Y. Liu et al., 2010; Sauge et al., 2007). Developing
more sophisticated networks and deploying quantum communication protocols in an urban
setting is a prominent technological feature of quantum communication for smart cities.
Therefore, an urban quantum network should be designed so that it can be scaled up to
complicated scenarios with more nodes, sources, and distances to cover (Y. Liu et al., 2010;
Sauge et al., 2007).
Quantum state teleportation is an exciting quantum physics notion representing a successful
application of the quantum entanglement phenomenon. The purpose of quantum teleportation
is to send an arbitrary quantum state to a remote place (e.g., across nodes in different city areas
or between cities) without sending the physical object that carries the state (Lele, 2021). This
is an impossible undertaking in Newtonian physics; on the other hand, quantum physics
provides an effective working strategy (Aspelmeyer, M et al., 2006; Chehimi & Saad, 2021).
Quantum internet is a potential quantum techno-system in which computers, networks, and
sensors exchange information in a fundamentally unique manner, with sensing, communication,
and computing operating together as a unit. As such, it is one conceivable outcome of well-
developed quantum teleportation. The quantum internet’s speed would be so incredible that far-
flung clocks could be synchronized a thousand times more precisely than the most precise
atomic clocks available today once QI became a global reality (Lele, 2021).
As a result, inter-city quantum networks should be made up of far-flung network nodes
comprising physical qubits that are quantumly entangled despite their great distance.
Establishing a viable quantum internet requires a broad physical distribution of entanglement
7
(Lele, 2021). As a result, city managers should be open to upgrading current communication
systems to implement the first practical quantum communication solutions properly.
Security is one of the most essential and sensitive components of quantum communication. The
urge to communicate in secret is at least as old as the first writing systems and can be traced
back to the dawn of civilization. As a result, many ancient communities devised means of secret
communication (Aspelmeyer, M et al., 2006). Today, the security of information within the
urban system is a critical goal for most city planners and managers for various reasons (Malluh
et al., 2014).
Thanks to Shor’s algorithm, many classical cryptosystems can theoretically be broken by
quantum computers (Monz et al., 2016). As a result, several traditional secret communication
protocols are potentially no longer secure, prompting researchers to build new secure
cryptographic systems (Tsai et al., 2005). However, when a quantum computer with super-
powerful parallel computation capabilities is used to quantum decrypt, an encrypted file that
would otherwise take a half year to “crack” by the most powerful conventional computer can
be cracked in just a few minutes. Thus, theoretically, there could exist no meaningful ciphertext
in a quantum computer world (Lele, 2021; Wei & Zhang, 2019). Cities as communication hubs
are among the most vulnerable targets for quantum computer attacks.
A secure communication protocol allows the sender (in cryptography, usually known as
“Alice”) and receiver (often known as “Bob”) to transmit and receive messages safely without
the risk of being decoded by an eavesdropper (in cryptography, commonly known as “Eve”).
Two characteristics must be met for a communication protocol to be called secure. First, the
secret communication must be read out in its original form by the rightful receiver after a
successful transmission. Second, even if an eavesdropper has complete control of the channel,
the encrypted message should provide no information to her (Tsai et al., 2005).
8
Charles Bennett and Gilles Brassard first proposed the concept of quantum cryptography in
1984 (Bennett & Brassard, 1984). The authors presented a new algorithm (BB86) based on
quantum communication networks, in which data is transmitted via quantum particles such as
photons. Heisenberg’s uncertainty principle states that when a quantum state is measured, it is
perturbed, resulting in only partial information about the system. As a result, quantum
cryptography is based on the idea that illegitimately listening on a quantum communication
channel notifies legitimate users (Aspelmeyer, M et al., 2006; Malluh et al., 2014).
The capacity to use and connect vastly disparate technologies in a modular and dependable
manner is essential for creating quantum communication networks in cities (Carvacho et al.,
2021). In other words, quantum communication enables high-quality long-distance quantum
channels that can accommodate the growing complexity of urban infrastructures (Chen et al.,
2010; Resch et al., 2005; Aspelmeyer, M et al., 2006; Lele, 2021). As a result, shopping systems
(Chou et al., 2014), 6G networks (Chehimi & Saad, 2021), local online games (Klauck et al.,
2007), IoT, blockchain (Al-Mohammed & Yaacoub, 2021), financial modeling, traffic
optimization, weather forecasting, AI, solar capture, and medicine can all benefit from urban
quantum communication (Nema & Nene, 2020).
Quantum key distribution (QKD) is one of the most promising quantum communication
approaches nowadays. QKD allows two legitimate remote users (for example, users in different
areas of a city or users in separate cities) to establish a shared secret key via photon transmission
and use that key to encrypt/decrypt secret messages (Chou et al., 2014; Piacentini et al., 2015).
As a result, QKD can be used as a functional component in highly secure city networks (Chou
et al., 2014). It potentially allows two different devices in the city to agree on a shared random
sequence of (conventional) bits, with a meager chance that other devices (eavesdroppers) will
be able to infer the values of those bits successfully. These bit sequences can then be used as
9
secret keys to encrypt and decrypt messages sent between the devices (Aspelmeyer, M et al.,
2006).
Finally, post-quantum cryptography (also known as quantum-proof, quantum-safe, or quantum-
resistant cryptography) refers to cryptographic methods (typically public-key algorithms) that
are secured against a quantum computer attack. Post-quantum cryptography is primarily
concerned with improving existing mathematical-based algorithms and standards to prepare
current systems for the era of quantum vulnerability. An efficient post-quantum cryptography
in an urban setting should be able to withstand quantum computer attacks on a city’s
infrastructure while still securing properties such as variability, unforgeability, identifiability,
and confidentiality (X. Zhang et al., 2015).
Even though quantum cryptography’s future remains uncertain, it is already garnering attention
(and financial resources) from various urban entities. On the experimental side, though, there
is still much work to be done (Aspelmeyer, M et al., 2006).
5.2 Quantum computing in Quantum Cities: a thematic synthesis
According to Chambers-Jones (2021), “In the future, we will not live in a democracy, where
citizens decide how we are governed, not in a bureaucracy, where officials decide […] We will
live in an autocracy, where algorithms decide.” From this perspective, quantum computers
represent the next-generation technology that has the potential to irreversibly alter the
economic, industrial, academic, and social landscapes of our cities (Inglesant et al., 2021;
Meng, 2020; Ten Holter et al., 2021; Uhlig et al., 2019).
Richard Feynman popularized the concept of quantum computing about 40 years ago (Salehi et
al., 2021). Today, it is a cutting-edge area at the intersection of mathematics, computer science,
and physics (Elhaddad & Mohammed, 2016; Trabesinger, 2017). The primary goal of quantum
computing is to effectively progress beyond the traditional von Neumann architecture. For
10
advanced computational processes, quantum computing relies on the principles of quantum
theory and its fundamental phenomena, such as entanglement and quantum superposition. In
other words, quantum computing is the extension of traditional computation to the elaboration
of quantum information using quantum systems such as single photons, atoms, or molecules
(Taha, 2016).
Information is conventionally stored in bits—either 0 (false) or 1 (true)—one at a time (Amiri,
2003). As a result, it is entirely based on Boolean algebra. Quantum computing, on the other
hand, works using quantum bits (or qubits). In contrast to traditional bits, a single qubit can
represent a one, zero, or a mixed state that is both 0 and 1 (Sotelo, 2019; You et al., 2009); in
other words, a quantum computer operates on a probabilistic rather than deterministic basis
(Cuffaro, 2015; Elhaddad & Mohammed, 2016).
According to DeBenedictis (2020), quantum computation can encode one billion operations at
a time. As a result, quantum computers’ most significant advantage is their capacity to solve
computationally demanding problems, which now require a lot of time, effort, and money
(Mosteanu & Faccia, 2021). Furthermore, quantum computers have exponentially larger
memory and can process a large number of inputs simultaneously, making them superior to
regular computers in various aspects (Raisinghani & Emerson, 2001). However, this does not
imply that quantum architectures will completely replace von Neumann architectures; instead,
quantum computers will assist traditional ones in a limited number of tasks (Yetis & Karakoes,
2021).
Artificial intelligence is one of the areas in which the synergetic effect of quantum computing
will be most significant. The relationship, however, is dual. The automation of computer
systems and the minimization of human intervention are two of AI’s most important
contributions to quantum computing (Bhatia et al., 2020). Furthermore, quantum algorithms
and artificial intelligence can reinforce each other: quantum algorithms can improve
11
unsupervised machine learning, while ML can be used to achieve quantum state tomography of
highly entangled states with over a hundred qubits (Palmieri et al., 2020; Torlai et al., 2018).
The use of quantum computing to speed up present machine learning methods holds much
promise for solving complicated urban challenges (Abdelgaber & Nikolopoulos, 2020; Casati,
2020; Jhanwar & Nene, 2021). Some cities are already pursuing quantum computing strategies
and research programs, promising significant investments to ensure global competitiveness.
More than 100 companies were already working on quantum computing in 2020. However,
some members of the scientific community continue to be skeptical of quantum computing’s
possibilities.
Many feel quantum computing still has a long way to go before it is widely embraced
(Gutiérrez-Salcedo et al., 2018; Paraoanu, 2011). The theoretical and practical feasibility of
developing a quantum computer should also be distinguished. On the practical side, issues such
as permitting precise individual qubit control, ambient noise, and quantum algorithm
implementation have hampered efforts to build the first effective computers based on quantum
mechanics principles (Elhaddad & Mohammed, 2016).
According to the assessed scholarly records, some of the most critical usages of quantum
computing include 5G and 6G communications, power grid management, smart factory
optimization, drug discovery (Gutiérrez-Salcedo et al., 2018), cryptography, integer
factorization, database search improvement (Kumar Sharma & Ghunawat, 2019), blockchain,
banking (Aderman, 2019; Krendelev & Sazonova, 2018), finance and business (Chambers-
Jones, 2021), economics (Alaminos et al., 2021), simulation and modeling (Inglesant et al.,
2021; Weder et al., 2020), weather forecasting, market prediction (Shubham et al., 2019),
disease prediction (Swarna et al., 2021), strategic management (Casati, 2020), AI, big data
(Singh & Singh, 2016), education (Gioda et al., 2021; Uhlig et al., 2019), law (Atik & Jeutner,
12
2021; Majot & Yampolskiy, 2015), aircraft industry (Möller & Vuik, 2017), military (Lele,
2021), IoT (Bhatt & Gautam, 2019), and art (Heaney, 2019).
There are three distinct visions of quantum computing’s future. For the first, we are on the verge
of an era of computing far more powerful than anything that has come before. The second vision
aims to determine the short-term practical consequences of quantum computing. Third, the idea
of “quantum supremacy” is concerned with many technical problems, regardless of real-world
applications (Inglesant et al., 2021). In the early phases of development, it is difficult to predict
and manage the potentially hazardous effects of quantum computing. However, changing the
course later on, after the results are visible, is infinitely more difficult (Sotelo, 2021). One of
the most significant threats of quantum computing is that it would “break the internet,”
rendering existing types of data encryption insecure, for example, by significantly speeding up
Shor’s algorithm to break public-key cryptography schemes (Inglesant et al., 2021; F. Zhang,
2020).
Different cryptographic vulnerabilities can undermine security in financial and other key
organizations in cities (Covers & Doeland, 2020). Cryptography, however, is one of the
disciplines where quantum computing is highly valued (Mogos, 2009; Shubham et al., 2019).
Accordingly, for the emergence of large-scale quantum computers to become a constructive
milestone in human history, we must first make our cryptographic infrastructures secure against
quantum attacks (Mitchell, 2020; Mosca, 2018). According to Majot and Yampolskiy (2015),
the adverse effects of quantum computing on city security systems highlight the need for clear
regulations that encourage the containment and responsible use of quantum computers to “help
alleviate some of the security issues posed by outdated cryptographic systems in a post-quantum
environment.”
Finally, if quantum computers are effectively deployed in cities, there would likely be an
increase in inequality due to a lack of knowledge or financial resources to acquire the new
13
technology (de Wolf, 2017). Thus, openness and accessibility are the best ways to ensure that
quantum computers’ beneficial influence outweighs their negative impact: related scientific
knowledge should be made publicly available as much as possible, and quantum computing
capacity should be accessible via the cloud (de Wolf, 2017). Furthermore, to reinforce the sound
effects of quantum computing in cities, urbanities must begin to think in new ways consistent
with quantum theory and quantum technologies. It does not mean that individuals should start
thinking like quantum computers; instead, they should learn what a quantum computer can
perform and how to interpret its output. It is possible to achieve this through proper education
and the gamification of education centered on the quantum paradigm (DeBenedictis, 2020;
Gordon & Gordon, 2012; Mykhailova & Svore, 2020; Uhlig et al., 2019).
If quantum computing achieves widespread technical implementation (and perhaps even
industrial production), it will trigger dramatic social challenges (Berezin, 2007). For this reason
alone, city managers must plan to adopt quantum computing beforehand, and strategies should
be deployed to remove barriers hindering the embracement of revolutionary technology (Bhasin
& Tripathi, 2021). The race is currently on to “create the world’s first meaningful quantum
computer as it has been theoretically conceived” (Lele, 2021). So far, however, only
rudimentary quantum computers have been engineered, and most experts think that advanced
fully-performant quantum computers are still in their nascent phases (Prince, 2014).
3. The relationship between quantum technologies and conventional smart city
technologies
3.1 Classifying smart city technologies
Before investigating the contribution of quantum technologies to a smart city, a proper practical
definition of the latter is needed. One way to define a smart city in more practical terms is by
systematically deriving a taxonomy of technologies used therein.
14
Contrary to relying on the existing classification, like that of quantum technologies (Acín et al.,
2018) in the preceding section, we derived a new taxonomy based on the lexical analysis of the
abstracts of related scholarly records.
Keywords “smart city” and “technology” were searched on Scopus (linked by the AND
operator) to retrieve all scholarly records containing those keywords in their titles. No
restrictions were imposed on the academic field or type of publication. As a result, 567
academic documents were identified (as of 09.01.2022).
The abstracts were then downloaded, and lexical analysis was performed in MAXQDA (release
22.0.1). The absolute frequency of all words and possible word combinations was analyzed.
The lemmatization was applied to control for different spellings and inflected forms. The
frequency table was then assessed, selecting the most frequent words and word combinations
related to class smart city technologies. As a result, forty such keywords were identified (Figure
2).
Figure 2. Most frequent smart city technologies-related words and word combinations across 567 scholarly
records
15
The obtained keywords were then thoroughly analyzed, including their usage in the context of
abstracts. As a result, seven categories of smart city technologies were identified:
• Artificial intelligence;
• Internet of Things;
• Information and communication technologies;
• Big data;
• Blockchain;
• Cloud computing;
• Smart transportation technologies.
The resulting taxonomy has the merit of being derived in an a-theoretical manner through the
lexical analysis of more than half a thousand abstracts of smart-city-related scholarly records.
Therefore, it is also among the most exhaustive.
3.2 Quantum technologies for smart cities: quantitative content analysis and thematic synthesis
For the proper evaluation of the relationships between the two facets of urban quantum
technology (quantum communication and quantum computing) and the seven pillars of smart
city technology (as determined in the previous sub-section), we performed a quantitative
content analysis (Bryman, 2016; Stemler, 2015) of 80 previously retrieved articles (Figure 1).
Again, the initial lexical analysis was performed in MAXQDA (release 22.0.1). We searched
and automatically coded all sentences containing keywords pertinent to the seven types of smart
city technologies. Analogous searches and automatic coding were also performed for quantum
computing and quantum communication. The keywords for the latter two were derived based
on the previous thematic analysis.
16
Figure 3 shows the hierarchical code structures resulting from the automatic coding. The
numbers over the arrows indicate the absolute frequencies of codes across the retrieved articles.
Figure 3. The hierarchical code structure of different city technologies across 80 articles
For each record, absolute frequencies of all 28 lower-level codes were then transformed into
relative, allowing the proper comparison between units of analysis. The following expression
was used for the transformation:
where i denotes the unit of analysis (80 selected articles), k and j denote a generic keyword (one
of 28).
17
The data was then imported into RStudio (version 1.4.1717), the variance was scaled to one,
and principal component analysis (PCA) was run. Twenty-eight lower-level codes entered the
analysis as active variables (in terms of their absolute frequencies across 80 records). PCA was
preferred to exploratory factor analysis since no a priori hypotheses about the potential
association between various classes of city-related technologies were made (Bartholomew et
al., 2008).
Twenty-eight active variables yielded an equal number of uncorrelated dimensions, implying
that the identified themes were already mostly uncorrelated across the analyzed records.
However, the first two dimensions stood out, accounting for approximately 31% of the total
inertia. Accordingly, only the first two dimensions were chosen for further analysis.
As shown in Figure 4, horizontal (and, thus, the most significant dimension) confirmed the
distinction between two classes of scholarly records: quantum computing (QC) to the left and
quantum communication (QCM) to the right. Additionally, the vertical axis captures the
relevance of typical smart city technologies (SSTs) in those documents. In particular, both
quantum communication and quantum computing-related papers in the northern part of the
plane are more likely to deal with conventional smart city technologies than papers in the
southern part of the plane.
In terms of the actual distribution of retrieved records, approximately half landed in the northern
part of the graph and half in the southern (see Figure 6). Thus, theoretically, four clusters of
quantum technology-related papers exist. These are papers on QC or QCM with an emphasis
on conventional smart city technologies and papers on QC or QCM without an emphasis on
conventional smart city technologies.
18
Figure 4. PCA. Active variables on the two most significant dimensions
N.B. cos2 measures the quality of representation of variables on the plane
As for the relationship between individual facets of QCM, QC, and conventional SSTs, little
can be inferred from PCA. Indeed, as Figure 4 shows, QCM, QC, and SSTs variables are mainly
orthogonal. To better understand the nested relationships between the two types of quantum
technologies and conventional smart city technologies, agglomerative hierarchical clustering
was performed.
For the clustering, the five most important PCA dimensions were preserved. The Euclidean
distance was used to compare the similarity between pairs of records. As a measure of group
proximity, Ward’s technique was preferred to ensure partitioning with low within-class
variability and high between-class variability. The related cluster dendrogram is shown in
Figure 5. In addition, Figure 6 depicts the hierarchical tree projected on the PCA factor map.
19
Because inertia increases from five classes and on, the clustering of records into four classes
was deemed the most appropriate; indeed, the remaining branches of the dendrogram are
substantially shorter (Figure 5). Furthermore, the sum of within-cluster inertia for each partition
was automatically calculated, and the suggested 4-fold partition was selected as the most
suitable.
Figure 5. Cluster analysis. Hierarchical tree
20
Figure 6. Cluster analysis. Hierarchical tree on the factor map
Figure 7 shows all the significant positive contributions of the active PCA variables to the
creation of the clusters.
Figure 7. Most significant (p-value less or equal to 0.05) variables in each cluster
N.B. top left – Cluster 1; top right – Cluster 2; down-left – Cluster 3; down-right – Cluster 4
21
Cluster analysis partially confirms the intuition behind the PCA results. In particular, Clusters
1 and 4 reflect the division of articles according to their belonging either to the quantum
computing or quantum communication category. Cluster 3 is mainly composed of scholarly
records of a broader scope, dealing with both types of quantum technologies. Cluster 2,
however, is the most interesting. As Figure 6 reveals, it mainly contains the records in the
northern part of the PCA plane (all three classes of variables are present, with SSTs being the
predominant).
The study of the components contributing to the creation of the second cluster reveals AI as the
most critical smart city technology, based on the frequency with which it is mentioned in the
related quantum technologies literature. The other conventional smart city technologies with
the highest potential for quantum synergies are (according to Figure 7) ICT, big data, cloud
computing, blockchain, and smart transportation.
A quantitative content analysis, however detailed, would be incomplete without more in-depth
qualitative insights into the topic. Accordingly, Table 1 summarizes the most important
contributions of quantum communication (second column) and quantum computing (fourth
column) to the seven smart city technology types.
SSTs
QCM
Relevant works
QC
Relevant works
Blockchain
Quantum computing attacks
pose a significant barrier to
securing blockchain-based
smart cities of the near future.
Therefore, post-quantum
cryptography has been proposed
as a solution to the issue.
Elegantly designed and
efficiently implemented
quantum-assisted distributed
ledgers have enormous potential
for protecting smart city
network communications.
Abd El-Latif et
al., 2021; Allam
& Jones, 2020;
Azzaoui & Park,
2020; Chen et
al., 2021;
Chiang et al.,
2020; Guo et al.,
2021; Gupta et
al., 2021; A.
Kumari et al.,
2021; McKee et
al., 2017;
Toapanta et al.,
2020; Xie et al.,
2019; Zhu et al.,
2019
Quantum computing is the
foundation of blockchain
technology since it
requires high-performance
computation. Traditional
protocols cannot support
memory mining; therefore,
each block on a blockchain
has a finite transaction
capacity that must be
extended. Thus, new post-
quantum techniques may
provide efficient memory
mining for quantum
computers.
Chen et al.,
2021; Moorman
& Stricklen,
2020;
Vivekanadam
B, 2020; Zhu et
al., 2019
22
IoT
Security in IoT remains a hurdle
due to the resource-constrained
nature of devices, networks, and
numerous attack vectors such as
quantum computers. Quantum
cryptography and lattice-based
cryptographic algorithms have
been offered as a possible
approach for post-quantum
security.
Garcia-Morchon
et al., 2015;
Imran et al.,
2020; Kumar et
al., n.d.; S.
Kumari et al.,
2021; Nieto-
Chaupis, 2018;
Ning & Liu,
2015; Routray
et al., 2019; Zhu
et al., 2019
Quantum computing will
enable the Internet of
Things with huge data
processing efficiency.
Quantum computers have
the potential to neutralize
IoT conspiracies by
safeguarding them.
Quantum Photonic
Computers (QPC) are
potential countermeasures
to IoT network abuse. Due
to the environmentally
beneficial characteristics
of QCs, they will serve as
viable alternatives in future
6G networks, avoiding the
misuse of 5G
IoT. Additionally, the IoT
chip with a quantum
number generator can
generate non-deterministic
real random numbers for
completely protected IoT
networks.
Kaatuzian,
2020; Kumar et
al., n.d.; Ning &
Liu, 2015;
Ramachandran,
2018
ICT
Post-Quantum ciphers are
crucial for 5G
networks, 6G networks, and
beyond, as the possibility of a
quantum attack is not
neglectable. Quantum
encryption and other emerging
encryption technologies will
assure the secure transfer of
information through ICT
platforms. New encryption
technologies, such as quantum
encryption, will ensure the
secure transmission of
information.
Park et al.,
2021; Tariq et
al., 2020
Superdense coding, which
is used in quantum
networking, increases data
transfer by optimizing how
information is presented to
the chain. As the amount
of information packets
increases, the need for
resources increases
proportionately. Thus, the
need for powerful quantum
computing technology
rises. Integrating quantum
computing and information
communications
technology infrastructures
in cities will significantly
improve the connection
between nodes in the grid
and its users.
Liang et al.,
2018; Toapanta
et al., 2020
Big data
and cloud
computing
At the higher level,
communication requires the
highest level of security to
maintain the system’s integrity
and safety. Quantum-assisted
security protection is required to
safeguard data and the cloud in
Smart City at different levels of
confidentiality.
Abd El-Latif et
al., 2018;
Chiang et al.,
2020; Jabbar et
al., 2020; Qian,
Cao, Dong, et
al., 2021; Qian,
Cao, Lu, et al.,
2021
While the volume of big
data continues to grow,
quantum computing
technology can overcome
limits in data collecting,
analysis, error detection,
resource management, and
processing.
AlSuwaidan,
2021; Balicki,
2022; Balicki et
al., 2019; Juma,
2020
AI
Artificial intelligence can design
high-intensity cryptography and
ensure cryptography design
automation. Quantum
Communications technologies
are exploited to provide services
Baonan et al.,
2019;
Manzalini,
2020; Wallnöfer
et al., 2020
An intelligent framework
that comprises all services
of smart cities can be
presented based on
quantum deep learning
techniques. Complex,
Balicki, 2022;
Lindgren, 2020;
Mukherjee &
Mandal, 2020;
Sharma &
Kumar, 2019
23
Table 1. A thematic synthesis of the relationships between smart city technologies and quantum technologies
such as ultra-massive scale
communications for connected
AI agendas, new paradigms of
brain-computer interactions, and
atomized forms of
communications. Machine
learning can also be used to
identify central quantum
protocols, including
teleportation, entanglement
purification, and the quantum
repeater. This is particularly
important in developing long-
distance communication
schemes and opens the way to
using machine learning in the
design and implementation of
quantum networks.
intelligent algorithms
based on machine learning,
deep learning, data mining,
big data analysis, cloud
computing, computer
network security, and
quantum simulations can
be performed with
exponential ease by means
of quantum computing
systems.
Smart
transport
Integrating artificial intelligence
and the Internet of Things into
the transportation system can
improve the communication
system’s efficiency. Likewise,
post-quantum cryptography can
play a key role in developing
intelligent and automated
transportation systems in future
smart cities.
Lv et al., 2021;
Otto, 2013
Quantum computers and
quantum algorithms can
significantly improve the
efficiency of transportation
systems when used in the
application of moving
target tracking in smart
cities. Additionally, smart
mobility is a critical
component of global smart
city initiatives. The bike-
sharing system intends to
provide an alternate form
of transportation for smart
mobility. Effective bike-
sharing system operation
requires rebalancing
analysis, which entails the
transfer of bikes between
different bike stations to
ensure that supply meets
anticipated demand. Proper
management of
rebalancing vehicle carrier
operations is crucial
for managing a bike-
sharing system. The above
issues can be efficiently
managed by using
quantum computational
power.
Harikrishnakum
ar et al., 2021;
Liu et al., 2020;
Manna et al.,
2021;
Manzalini,
2020; Santos,
2021; Zhang et
al., 2020
24
4. Discussion and conclusions
As revealed by the literature review, quantum communication and quantum computing
represent the most important quantum technologies for successful urban planning and
management. As a result, proper investment in quantum communication and computing could
provide cities with a significant first-mover advantage in terms of internal efficiency and future
appeal to the investors.
Quantum technologies rely on quantum mechanics’ more abstract and counterintuitive ideas.
Embracing those technologies for everyday use necessitates city managers and planners to
effectively communicate the benefits and drawbacks of novel QTs, as well as the fundamental
principles of their operation, which, in turn, demands increasing “quantum literacy” of
urbanities, analogous to the introduction of conventional computers and their subsequent
diffusion from universities to business, and finally to private usage.
In contrast, smart city technologies represent a more concrete set of instruments that can
significantly contribute to the everyday existence of a city’s techno-system. In evaluating the
impact of the quantum paradigm on smart city technologies, we noticed that most of the
research focuses on the security dangers posed by quantum computers and the solutions
proposed by quantum communication. However, such a short-sighted approach to the concept
appears to lead to a new sort of “cold war” (albeit between technologies, not countries),
consuming a significant amount of resources and producing tension without contributing to
humanity’s welfare or the betterment of everyday life. Quantum technologies, meanwhile,
detain enormous potential for speeding up and simplifying processes within urban
infrastructures and the related eco and techno-systems.
As a result, this paper strongly advises scholars and city managers to shift their attention and
the potential quantum technology investments away from defensive strategies (mainly that of
digital warfare) toward more useful everyday applications. Indeed, as the quantitative content
25
analysis revealed, interconnections between quantum computing, quantum communication, and
seven facets of smart city technology (AI, ICT, IoT, blockchain, big data, cloud computing, and
transportation) in the analyzed QT literature within social science are significant, albeit not yet
strong. To achieve a further increase in the speed of the shift from quantum technology defense
practices to common smart city applications, a novel form of education and training should
orient new generations to perceive the world in safer, although undecidable, terms, in a context
where we are yet unable to forecast all of the implications of these futuristic technologies. As a
result, in addition to technology expenditure, educational investments are highly required
(Formisano, Fedele, & Bashirpour Bonab, 2021).
To conclude, several limitations characterize our study.
First, the connections between quantum technologies and conventional smart city technologies
were hypothesized based on the frequency of related keywords across the retrieved scholarly
records on QTs within the social sciences. As such, they should not be considered as exact
operational definitions of quantum technologies or smart city technologies. Instead, what is
studied here are the potential connections between research ideas rather than the actual
contribution of quantum computing and quantum communication to seven facets of smart city
technologies. Such measurements would require advanced and ubiquitous QTs, which, for now,
are only in their nascent phases of reification.
Second, only simple Boolean queries were performed for the literature search. We do not
exclude that some important papers could have been omitted from the analysis. However, given
the high number of papers considered (80 for the content analysis/thematic synthesis and more
than 500 for the derivation of the smart city technologies taxonomy), we consider theoretical
saturation to be appropriately reached. Thus, it is unlikely that some novel insights could have
emerged from the omitted scholarly documents.
26
References
Abd El-Latif, A. A., Abd-El-Atty, B., Hossain, M. S., Rahman, Md. A., Alamri, A., & Gupta,
B. B. (2018). Efficient Quantum Information Hiding for Remote Medical Image
Sharing. IEEE Access, 6, 21075–21083.
https://doi.org/10.1109/ACCESS.2018.2820603
Abd El-Latif, A. A., Abd-El-Atty, B., Mehmood, I., Muhammad, K., Venegas-Andraca, S. E.,
& Peng, J. (2021). Quantum-Inspired Blockchain-Based Cybersecurity: Securing
Smart Edge Utilities in IoT-Based Smart Cities. Information Processing &
Management, 58(4), 102549. https://doi.org/10.1016/j.ipm.2021.102549
Abdelgaber, N., & Nikolopoulos, C. (2020). Overview on Quantum Computing and its
Applications in Artificial Intelligence. 2020 IEEE Third International Conference on
Artificial Intelligence and Knowledge Engineering (AIKE), 198–199.
https://doi.org/10.1109/AIKE48582.2020.00038
Acín, A., Bloch, I., Buhrman, H., Calarco, T., Eichler, C., Eisert, J., Esteve, D., Gisin, N.,
Glaser, S. J., Jelezko, F., Kuhr, S., Lewenstein, M., Riedel, M. F., Schmidt, P. O.,
Thew, R., Wallraff, A., Walmsley, I., & Wilhelm, F. K. (2018). The quantum
technologies roadmap: A European community view. New Journal of Physics, 20(8),
080201. https://doi.org/10.1088/1367-2630/aad1ea
Aderman, T. L. (2019). An Introduction to Quantum Computers and Their Effect on Banking
Institutions. International Journal of Financial Research, 10(4), 17–24.
Alaminos, D., Salas, M. B., & Fernández-Gámez, M. A. (2021). Quantum Computing and
Deep Learning Methods for GDP Growth Forecasting. Computational Economics.
https://doi.org/10.1007/s10614-021-10110-z
Allam, Z., & Jones, D. S. (2020). On the Coronavirus (COVID-19) Outbreak and the Smart
City Network: Universal Data Sharing Standards Coupled with Artificial Intelligence
(AI) to Benefit Urban Health Monitoring and Management. Healthcare, 8(1), 46.
https://doi.org/10.3390/healthcare8010046
Al-Mohammed, H. A., & Yaacoub, E. (2021). On The Use of Quantum Communications for
Securing IoT Devices in the 6G Era. 2021 IEEE International Conference on
Communications Workshops (ICC Workshops), 1–6.
https://doi.org/10.1109/ICCWorkshops50388.2021.9473793
27
AlSuwaidan, L. (2021). The role of data management in the Industrial Internet of Things.
Concurrency and Computation: Practice and Experience, 33(23), e6031.
https://doi.org/10.1002/cpe.6031
Amiri, P. K. (2003). Quantum computers. IEEE Potentials, 21(5), 6–9.
https://doi.org/10.1109/MP.2002.1166617
Arida, A. (1998). Quantum environments: Urban design in the post-Cartesian paradigm.
Urban Design International, 3, 141–148. https://doi.org/10.1080/135753198350415
Arida, A. (2002). Quantum City. Routledge.
Aspelmeyer, M, Zeilinger, A, Böhm, H. R, Fedrizzi, A, Gasparoni, S, Lindenthal, M, Molina-
Terriza, G, Poppe, A, Resch, K, Ursin, R, & Walther, P. (2006). Advanced Quantum
Communications Experiments with Entangled Photons. In Quantum Communications
and Cryptography. CRC Press.
Atik, J., & Jeutner, V. (2021). Quantum computing and computational law. Law, Innovation
and Technology, 0(0), 1–23. https://doi.org/10.1080/17579961.2021.1977216
Azzaoui, A. E., & Park, J. H. (2020). Post-Quantum Blockchain for a Scalable Smart City.
Journal of Internet Technology, 21(4), 1171–1178.
Balicki, J. (2022). Many-Objective Quantum-Inspired Particle Swarm Optimization
Algorithm for Placement of Virtual Machines in Smart Computing Cloud. Entropy,
24(1), 58. https://doi.org/10.3390/e24010058
Balicki, J., Balicka, H., Dryja, P., & Tyszka, M. (2019). Big Data and the Internet of Things
in Edge Computing for Smart City. In K. Saeed, R. Chaki, & V. Janev (Eds.),
Computer Information Systems and Industrial Management (pp. 99–109). Springer
International Publishing. https://doi.org/10.1007/978-3-030-28957-7_9
Baonan, W., Feng, H., Huanguo, Z., & Chao, W. (2019). From Evolutionary Cryptography to
Quantum Artificial Intelligent Cryptography. Journal of Computer Research and
Development, 56(10), 2112. https://doi.org/10.7544/issn1000-1239.2019.20190374
Bennett, C. H., & Brassard, G. (1984). An Update on Quantum Cryptography. In G. R.
Blakley & D. Chaum (Eds.), Advances in Cryptology (pp. 475–480). Springer.
https://doi.org/10.1007/3-540-39568-7_39
Berezin, A. A. (2007). Quantum computing and security of information systems. Safety and
Security Engineering II, I, 149–159. https://doi.org/10.2495/SAFE070151
Bhasin, A., & Tripathi, M. (2021). Quantum Computing at an Inflection Point: Are we Ready
for a New Paradigm. IEEE Transactions on Engineering Management, 1–12.
https://doi.org/10.1109/TEM.2021.3103904
28
Bhatia, A., Bibhu, V., Lohani, B. P., & Kushwaha, P. K. (2020). An Application Framework
for Quantum Computing using Artificial intelligence Techniques. 2020 Research,
Innovation, Knowledge Management and Technology Application for Business
Sustainability (INBUSH), 264–269.
https://doi.org/10.1109/INBUSH46973.2020.9392164
Bhatt, H., & Gautam, S. (2019). Quantum Computing: A New Era of Computer Science. 2019
6th International Conference on Computing for Sustainable Global Development
(INDIACom), 558–561.
Bibri, S. E. (2018). The IoT for smart sustainable cities of the future: An analytical framework
for sensor-based big data applications for environmental sustainability. Sustainable
Cities and Society, 38, 230–253. https://doi.org/10.1016/j.scs.2017.12.034
Bifulco, F., Tregua, M., Amitrano, C. C., & D’Auria, A. (2016). ICT and sustainability in
smart cities management. International Journal of Public Sector Management, 29(2),
132–147. https://doi.org/10.1108/IJPSM-07-2015-0132
Bryman, A. (2016). Social Research Methods. Oxford University Press.
Carvacho, G., Roccia, E., Valeri, M., Basset, F. B., Poderini, D., Pardo, C., Polino, E.,
Carosini, L., Rota, M. B., Neuwirth, J., da Silva, S. F. C., Rastelli, A., Spagnolo, N.,
Chaves, R., Trotta, R., & Sciarrino, F. (2021). Quantum violation of local causality in
urban network with hybrid photonic technologies. ArXiv:2109.06823 [Quant-Ph].
http://arxiv.org/abs/2109.06823
Casati, N. M. (2020). Current and Future Global Challenges in Management and Leadership:
Finance and Quantum Computing. In B. S. Thakkar (Ed.), Paradigm Shift in
Management Philosophy: Future Challenges in Global Organizations (pp. 103–131).
Springer International Publishing. https://doi.org/10.1007/978-3-030-29710-7_6
Chambers-Jones, C. (2021). AI, big data, quantum computing, and financial exclusion:
Tempering enthusiasm and offering a human-centric approach to policy. In FinTech,
Artificial Intelligence and the Law. Routledge.
Chehimi, M., & Saad, W. (2021). Entanglement Rate Optimization in Heterogeneous
Quantum Communication Networks. ArXiv:2105.14507 [Quant-Ph].
http://arxiv.org/abs/2105.14507
Chen, J., Gan, W., Hu, M., & Chen, C.-M. (2021). On the construction of a post-quantum
blockchain for smart city. Journal of Information Security and Applications, 58,
102780. https://doi.org/10.1016/j.jisa.2021.102780
29
Chen, T.-Y., Wang, J., Liang, H., Liu, W.-Y., Liu, Y., Jiang, X., Wang, Y., Wan, X., Cai, W.-
Q., Ju, L., Chen, L.-K., Wang, L.-J., Gao, Y., Chen, K., Peng, C.-Z., Chen, Z.-B., &
Pan, J.-W. (2010). Metropolitan all-pass and inter-city quantum communication
network. Optics Express, 18(26), 27217–27225. https://doi.org/10.1364/OE.18.027217
Chiang, C.-F., Sengupta, S., Tekeoglu, A., Novillo, J., & Andriamanalimanana, B. (2020). A
Quantum Assisted Secure Client-Centric Polyvalent Blockchain Architecture for
Smart Cities. 2020 IEEE 17th Annual Consumer Communications Networking
Conference (CCNC), 1–6. https://doi.org/10.1109/CCNC46108.2020.9045188
Chou, Y.-H., Lin, F.-J., & Zeng, G.-J. (2014). An efficient novel online shopping mechanism
based on quantum communication. Electronic Commerce Research, 14(3), 349–367.
https://doi.org/10.1007/s10660-014-9143-6
Covers, O., & Doeland, M. (2020). How the financial sector can anticipate the threats of
quantum computing to keep payments safe and secure. Journal of Payments Strategy
& Systems, 14(2), 147–156.
Cuffaro, M. E. (2015). How-Possibly Explanations in (Quantum) Computer Science.
Philosophy of Science, 82(5), 737–748. https://doi.org/10.1086/683243
de Wolf, R. (2017). The potential impact of quantum computers on society. Ethics and
Information Technology, 19(4), 271–276. https://doi.org/10.1007/s10676-017-9439-z
DeBenedictis, E. P. (2020). Imagining the Future of Quantum Computing. In L. Strous, R.
Johnson, D. A. Grier, & D. Swade (Eds.), Unimagined Futures – ICT Opportunities
and Challenges (pp. 70–83). Springer International Publishing.
https://doi.org/10.1007/978-3-030-64246-4_6
Elhaddad, M. E., & Mohammed, S. A. O. (2016). Analysing the impact of quantum
computing using system dynamics. 2016 International Conference on Engineering
MIS (ICEMIS), 1–5. https://doi.org/10.1109/ICEMIS.2016.7745387
Formisano, V., Fedele, M., & Bashirpour Bonab, A. (2021, September 1). Knowledge
Management and Circular Economy: Novel Solutions to Cope with Uncertain Times.
Formisano, V., Fedele, M., Rudko, I., & Bashirpour Bonab, A. (2021, December 6). Deriving
Perceived Brand Personality Traits of Thriving Cities: Empirical Investigation of
City-Related Subreddits.
Garcia-Morchon, O., Rietman, R., Sharma, S., Tolhuizen, L., & Torre-Arce, J. L. (2015). A
Comprehensive and Lightweight Security Architecture to Secure the IoT Throughout
the Lifecycle of a Device Based on HIMMO. In P. Bose, L. A. Gąsieniec, K. Römer,
30
& R. Wattenhofer (Eds.), Algorithms for Sensor Systems (pp. 112–128). Springer
International Publishing. https://doi.org/10.1007/978-3-319-28472-9_9
Gioda, I., Caputo, D., Fadda, E., Manerba, D., Silva Fernández, B., & Tadei, R. (2021).
Solving assignment problems via Quantum Computing: A case-study in train seating
arrangement. 2021 16th Conference on Computer Science and Intelligence Systems
(FedCSIS), 217–220. https://doi.org/10.15439/2021F74
Gordon, M., & Gordon, G. (2012). Quantum computer games: Schrödinger cat and hounds.
Physics Education, 47(3), 346–354. https://doi.org/10.1088/0031-9120/47/3/346
Gouvea, R., Kapelianis, D., & Kassicieh, S. (2018). Assessing the nexus of sustainability and
information & communications technology. Technological Forecasting and Social
Change, 130, 39–44. https://doi.org/10.1016/j.techfore.2017.07.023
Guo, J., Ding, X., & Wu, W. (2021). A Blockchain-Enabled Ecosystem for Distributed
Electricity Trading in Smart City. IEEE Internet of Things Journal, 8(3), 2040–2050.
https://doi.org/10.1109/JIOT.2020.3015980
Gupta, R., Kumari, A., & Tanwar, S. (2021). Fusion of blockchain and artificial intelligence
for secure drone networking underlying 5G communications. Transactions on
Emerging Telecommunications Technologies, 32(1), e4176.
https://doi.org/10.1002/ett.4176
Gusenbauer, M., & Haddaway, N. R. (2020). Which academic search systems are suitable for
systematic reviews or meta-analyses? Evaluating retrieval qualities of Google Scholar,
PubMed, and 26 other resources. Research Synthesis Methods, 11(2), 181–217.
https://doi.org/10.1002/jrsm.1378
Gutiérrez-Salcedo, M., Martínez, M. Á., Moral-Munoz, J. A., Herrera-Viedma, E., & Cobo,
M. J. (2018). Some bibliometric procedures for analyzing and evaluating research
fields. Applied Intelligence, 48(5), 1275–1287. https://doi.org/10.1007/s10489-017-
1105-y
Harikrishnakumar, R., Borujeni, S. E., Ahmad, S. F., & Nannapaneni, S. (2021). Rebalancing
Bike Sharing Systems under Uncertainty using Quantum Bayesian Networks. 2021
IEEE International Conference on Quantum Computing and Engineering (QCE),
461–462. https://doi.org/10.1109/QCE52317.2021.00078
Heaney, L. (2019). Quantum Computing and Complexity in Art. Leonardo, 52(3), 230–235.
https://doi.org/10.1162/leon_a_01572
31
Imran, Ahmad, S., & Kim, D. H. (2020). Quantum GIS Based Descriptive and Predictive
Data Analysis for Effective Planning of Waste Management. IEEE Access, 8, 46193–
46205. https://doi.org/10.1109/ACCESS.2020.2979015
Inglesant, P., Ten Holter, C., Jirotka, M., & Williams, R. (2021). Asleep at the wheel?
Responsible Innovation in quantum computing. Technology Analysis & Strategic
Management, 33(11), 1364–1376. https://doi.org/10.1080/09537325.2021.1988557
Jabbar, J., Mehmood, H., Hafeez, U., Malik, H., & Salahuddin, H. (2020). On COVID-19
outburst and smart city/urban system connection: Worldwide sharing of data
principles with the collaboration of IoT devices and AI to help urban healthiness
supervision and monitoring. International Journal of Engineering & Technology, 9,
630. https://doi.org/10.14419/ijet.v9i3.30655
Jhanwar, A., & Nene, M. J. (2021). Enhanced Machine Learning using Quantum Computing.
2021 Second International Conference on Electronics and Sustainable
Communication Systems (ICESC), 1407–1413.
https://doi.org/10.1109/ICESC51422.2021.9532638
Juma, H. (2020). Digital Speedway to Future Smart Cities. In A. Abu-Tair, A. Lahrech, K. Al
Marri, & B. Abu-Hijleh (Eds.), Proceedings of the II International Triple Helix
Summit (pp. 193–207). Springer International Publishing. https://doi.org/10.1007/978-
3-030-23898-8_15
Kaatuzian, H. (2020). Quantum Supremacy Versus IoT Conspiracy in Smart Cities. 2020 4th
International Conference on Smart City, Internet of Things and Applications (SCIOT),
77–83. https://doi.org/10.1109/SCIOT50840.2020.9250203
Klauck, H., Nayak, A., Ta-Shma, A., & Zuckerman, D. (2007). Interaction in Quantum
Communication. IEEE Transactions on Information Theory, 53(6), 1970–1982.
https://doi.org/10.1109/TIT.2007.896888
Krendelev, S., & Sazonova, P. (2018). Parametric Hash Function Resistant to Attack by
Quantum Computer. 2018 Federated Conference on Computer Science and
Information Systems (FedCSIS), 387–390.
Kumar, A., Ottaviani, C., Gill, S. S., & Buyya, R. (n.d.). Securing the future internet of things
with post-quantum cryptography. SECURITY AND PRIVACY, n/a(n/a), e200.
https://doi.org/10.1002/spy2.200
Kumar Sharma, A., & Ghunawat, A. (2019). A Review on Quantum Computers with
Emphasize on Linear Optics Quantum Computing. 2019 International Conference on
32
Issues and Challenges in Intelligent Computing Techniques (ICICT), 1, 1–3.
https://doi.org/10.1109/ICICT46931.2019.8977637
Kumari, A., Gupta, R., & Tanwar, S. (2021). Amalgamation of blockchain and IoT for smart
cities underlying 6G communication: A comprehensive review. Computer
Communications, 172, 102–118. https://doi.org/10.1016/j.comcom.2021.03.005
Kumari, S., Singh, M., Singh, R., & Tewari, H. (2021). To Secure the Communication in
Powerful Internet of Things Using Innovative Post-Quantum Cryptographic Method.
Arabian Journal for Science and Engineering. https://doi.org/10.1007/s13369-021-
06166-6
Lele, A. (2021). Quantum Technologies and Military Strategy. Springer Nature.
Liang, X., Shetty, S., & Tosh, D. (2018). Exploring the Attack Surfaces in Blockchain
Enabled Smart Cities. 2018 IEEE International Smart Cities Conference (ISC2), 1–8.
https://doi.org/10.1109/ISC2.2018.8656852
Lindgren, P. (2020). Multi Business Model Innovation in a World of Smart Cities with Future
Wireless Technologies. Wireless Personal Communications, 113(3), 1423–1435.
https://doi.org/10.1007/s11277-020-07314-1
Liu, Y., Zhang, L., & Zhang, X. (2010). A quantum repeater in infrared quantum
communication system. 2010 3rd International Conference on Biomedical
Engineering and Informatics, 7, 2824–2827.
https://doi.org/10.1109/BMEI.2010.5639341
Liu, Z., Shang, J., & Hua, X. (2020). Smart City Moving Target Tracking Algorithm Based
on Quantum Genetic and Particle Filter. Wireless Communications and Mobile
Computing, 2020, e8865298. https://doi.org/10.1155/2020/8865298
Lv, Z., Lou, R., & Singh, A. K. (2021). AI Empowered Communication Systems for
Intelligent Transportation Systems. IEEE Transactions on Intelligent Transportation
Systems, 22(7), 4579–4587. https://doi.org/10.1109/TITS.2020.3017183
Lynch, K. (1984). Good City Form. MIT Press.
Lynch, K. (1990). Wasting Away. Sierra Club Books.
Macionis, J. J., & Parrillo, V. N. (2017). Cities and Urban Life. Pearson.
Majot, A., & Yampolskiy, R. (2015). Global catastrophic risk and security implications of
quantum computers. Futures, 72, 17–26. https://doi.org/10.1016/j.futures.2015.02.006
Malluh, A. A., Elleithy, K. M., Alanazi, A., & Mstafa, R. J. (2014). A highly secure quantum
communication scheme for Blind Signature using qubits and qutrits. Proceedings of
33
the 2014 Zone 1 Conference of the American Society for Engineering Education, 1–6.
https://doi.org/10.1109/ASEEZone1.2014.6820657
Manna, M. L., Perazzo, P., Treccozzi, L., & Dini, G. (2021). Assessing the Cost of Quantum
Security for Automotive Over -The-Air Updates. 2021 IEEE Symposium on
Computers and Communications (ISCC), 1–6.
https://doi.org/10.1109/ISCC53001.2021.9631426
Manzalini, A. (2020). Quantum Communications in Future Networks and Services. Quantum
Reports, 2(1), 221–232. https://doi.org/10.3390/quantum2010014
McKee, D. W., Clement, S. J., Almutairi, J., & Xu, J. (2017). Massive-Scale Automation in
Cyber-Physical Systems: Vision amp; Challenges. 2017 IEEE 13th International
Symposium on Autonomous Decentralized System (ISADS), 5–11.
https://doi.org/10.1109/ISADS.2017.56
MENG, Z. (2020). Review of Quantum Computing. 2020 13th International Conference on
Intelligent Computation Technology and Automation (ICICTA), 210–213.
https://doi.org/10.1109/ICICTA51737.2020.00051
Meng, Z. (2020). Review of Quantum Computing. 2020 13th International Conference on
Intelligent Computation Technology and Automation (ICICTA), 210–213.
https://doi.org/10.1109/ICICTA51737.2020.00051
Mitchell, C. J. (2020). The impact of quantum computing on real-world security: A 5G case
study. Computers & Security, 93, 101825. https://doi.org/10.1016/j.cose.2020.101825
Mogos, G. (2009). Hide Secrets Using the Power of Quantum Computers. Engineering and
Information 2009 International Conference on Computing, 135–139.
https://doi.org/10.1109/ICC.2009.18
Möller, M., & Vuik, C. (2017). On the impact of quantum computing technology on future
developments in high-performance scientific computing. Ethics and Information
Technology, 19(4), 253–269. https://doi.org/10.1007/s10676-017-9438-0
Monz, T., Nigg, D., Martinez, E. A., Brandl, M. F., Schindler, P., Rines, R., Wang, S. X.,
Chuang, I. L., & Blatt, R. (2016). Realization of a scalable Shor algorithm. Science,
351(6277), 1068–1070. https://doi.org/10.1126/science.aad9480
Moorman, J., & Stricklen, M. (2020). Smart Cities Applications of Blockchain. In S.
McClellan (Ed.), Smart Cities in Application: Healthcare, Policy, and Innovation (pp.
101–117). Springer International Publishing. https://doi.org/10.1007/978-3-030-
19396-6_6
34
Mosca, M. (2018). Cybersecurity in an Era with Quantum Computers: Will We Be Ready?
IEEE Security Privacy, 16(5), 38–41. https://doi.org/10.1109/MSP.2018.3761723
Mosteanu, N. R., & Faccia, A. (2021). Fintech Frontiers in Quantum Computing, Fractals,
and Blockchain Distributed Ledger: Paradigm Shifts and Open Innovation. Journal of
Open Innovation: Technology, Market, and Complexity, 7(1), 19.
https://doi.org/10.3390/joitmc7010019
Mukherjee, K., & Mandal, R. K. (2020). A Theme of Smart Cities Based on IOT, Fuzzy
Logic and Quantum-Deep Learning Technique. International Journal of Intelligent
Systems and Applications in Engineering, 8(1), 21–27.
https://doi.org/10.18201/ijisae.2020158885
Mykhailova, M., & Svore, K. M. (2020). Teaching Quantum Computing through a Practical
Software-driven Approach: Experience Report. Proceedings of the 51st ACM
Technical Symposium on Computer Science Education, 1019–1025.
https://doi.org/10.1145/3328778.3366952
Nema, P., & Nene, M. J. (2020). Pauli Matrix based Quantum Communication Protocol. 2020
IEEE International Conference on Advent Trends in Multidisciplinary Research and
Innovation (ICATMRI), 1–6. https://doi.org/10.1109/ICATMRI51801.2020.9398393
Nieto-Chaupis, H. (2018). Modeling the Bit Error Rate for Accessing Hybrid: Quantum and
Classical Networks in Scenarios of the Internet of Things in Middle-Size Smart Cities.
2018 IEEE Biennial Congress of Argentina (ARGENCON), 1–4.
https://doi.org/10.1109/ARGENCON.2018.8646233
Ning, H., & Liu, H. (2015). Cyber-physical-social-thinking space based science and
technology framework for the Internet of Things. Science China Information Sciences,
58(3), 1–19. https://doi.org/10.1007/s11432-014-5209-2
Otto, S. (2013). Communication in Transportation Systems. IGI Global.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D.,
Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J.,
Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson,
E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated
guideline for reporting systematic reviews. BMJ, 372, n71.
https://doi.org/10.1136/bmj.n71
Palmieri, A. M., Kovlakov, E., Bianchi, F., Yudin, D., Straupe, S., Biamonte, J. D., & Kulik,
S. (2020). Experimental neural network enhanced quantum tomography. Npj Quantum
Information, 6(1), 1–5. https://doi.org/10.1038/s41534-020-0248-6
35
Paraoanu, G. S. (2011). Quantum Computing: Theoretical versus Practical Possibility. Physics
in Perspective, 13(3), 359. https://doi.org/10.1007/s00016-011-0057-6
Park, J. H., Rathore, S., Singh, S. K., Salim, M. M., Azzaoui, A. E., Kim, T. W., Pan, Y., &
Park, J. H. (2021). A Comprehensive Survey on Core Technologies and Services for
5G Security: Taxonomies, Issues and Solutions. Human-Centric Computing and
Information Sciences, 1(0), 1–22. https://doi.org/10.22967/HCIS.2021.11.003
Piacentini, F., Adenier, G., Traina, P., Avella, A., Brida, G., Degiovanni, I. P., Gramegna, M.,
Berchera, I. R., & Genovese, M. (2015). Metrology for Quantum Communication.
2015 IEEE Globecom Workshops (GC Wkshps), 1–5.
https://doi.org/10.1109/GLOCOMW.2015.7413960
Prince, J. D. (2014). Quantum Computing: An Introduction. Journal of Electronic Resources
in Medical Libraries, 11(3), 155–158. https://doi.org/10.1080/15424065.2014.939462
Qian, J., Cao, Z., Dong, X., Shen, J., Liu, Z., & Ye, Y. (2021). Two Secure and Efficient
Lightweight Data Aggregation Schemes for Smart Grid. IEEE Transactions on Smart
Grid, 12(3), 2625–2637. https://doi.org/10.1109/TSG.2020.3044916
Qian, J., Cao, Z., Lu, M., Chen, X., Shen, J., & Liu, J. (2021). The Secure Lattice-based Data
Aggregation Scheme in Residential Networks for Smart Grid. IEEE Internet of Things
Journal, 1–1. https://doi.org/10.1109/JIOT.2021.3090270
Quan, S. J., Park, J., Economou, A., & Lee, S. (2019). Artificial intelligence-aided design:
Smart Design for sustainable city development. Environment and Planning B: Urban
Analytics and City Science, 46(8), 1581–1599.
https://doi.org/10.1177/2399808319867946
Raisinghani, M. S., & Emerson, R. W. (2001). Quantum Computers: A New Paradigm in
Information Technology.
Ramachandran, R. (2018). The Analysis of Different Types of IoT Sensors and security trend
as Quantum chip for Smart City Management. https://doi.org/10.9790/487X-
2001045560
Resch, K. J., Lindenthal, M., Blauensteiner, B., Böhm, H. R., Fedrizzi, A., Kurtsiefer, C.,
Poppe, A., Schmitt-Manderbach, T., Taraba, M., Ursin, R., Walther, P., Weier, H.,
Weinfurter, H., & Zeilinger, A. (2005). Distributing entanglement and single photons
through an intra-city, free-space quantum channel. Optics Express, 13(1), 202–209.
https://doi.org/10.1364/OPEX.13.000202
Routray, S. K., Sarangi, S. K., & Javali, A. (2019). Smart Cities: The Hopes and Hypes.
ArXiv:1907.05702 [Cs, Eess]. http://arxiv.org/abs/1907.05702
36
Salehi, Ö., Seskir, Z., & Tepe, İ. (2021). A Computer Science-Oriented Approach to
Introduce Quantum Computing to a New Audience. IEEE Transactions on Education,
1–8. https://doi.org/10.1109/TE.2021.3078552
Santos, A. F. de S. T. L. dos. (2021). Quantum Computing for Optimizing Routes in Smart
Cities. https://repositorio-aberto.up.pt/handle/10216/135444
Sauge, S., Swillo, M., Albert-Seifried, S., Xavier, G. B., Waldeback, J., Tengner, M.,
Ljunggren, D., Wang, Q., & Karlsson, A. (2007). Quantum Communication in Optical
Networks: An Overview and Selected Recent Results. 2007 9th International
Conference on Transparent Optical Networks, 1, 30–33.
https://doi.org/10.1109/ICTON.2007.4296023
Sharma, R., & Kumar, V. (2019). The Multidimensional Venture of developing a Smart City.
2019 International Conference on Big Data and Computational Intelligence
(ICBDCI), 1–7. https://doi.org/10.1109/ICBDCI.2019.8686101
Shubham, Sajwan, P., & Jayapandian, N. (2019). Challenges and Opportunities: Quantum
Computing in Machine Learning. 2019 Third International Conference on I-SMAC
(IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 598–602.
https://doi.org/10.1109/I-SMAC47947.2019.9032461
Singh, J., & Singh, M. (2016). Evolution in Quantum Computing. 2016 International
Conference System Modeling Advancement in Research Trends (SMART), 267–270.
https://doi.org/10.1109/SYSMART.2016.7894533
Sotelo, R. (2019). Quantum Computing: What, Why, Who. 2019 IEEE CHILEAN Conference
on Electrical, Electronics Engineering, Information and Communication Technologies
(CHILECON), 1–6. https://doi.org/10.1109/CHILECON47746.2019.8988080
Sotelo, R. (2021). Quantum Computing Entrepreneurship and IEEE TEMS. IEEE
Engineering Management Review, 49(3), 26–29.
https://doi.org/10.1109/EMR.2021.3098260
Stemler, S. E. (2015). Content Analysis. In Emerging Trends in the Social and Behavioral
Sciences (pp. 1–14). John Wiley & Sons, Ltd.
https://doi.org/10.1002/9781118900772.etrds0053
Swarna, S. R., Kumar, A., Dixit, P., & Sairam, T. V. M. (2021). Parkinson’s Disease
Prediction using Adaptive Quantum Computing. 2021 Third International Conference
on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV),
1396–1401. https://doi.org/10.1109/ICICV50876.2021.9388628
37
Taha, S. M. R. (2016). Quantum Logic Circuits and Quantum Computing. In S. M. R. Taha
(Ed.), Reversible Logic Synthesis Methodologies with Application to Quantum
Computing (pp. 135–151). Springer International Publishing.
https://doi.org/10.1007/978-3-319-23479-3_6
Tariq, F., Khandaker, M. R. A., Wong, K.-K., Imran, M. A., Bennis, M., & Debbah, M.
(2020). A Speculative Study on 6G. IEEE Wireless Communications, 27(4), 118–125.
https://doi.org/10.1109/MWC.001.1900488
Ten Holter, C., Inglesant, P., & Jirotka, M. (2021). Reading the road: Challenges and
opportunities on the path to responsible innovation in quantum computing.
Technology Analysis & Strategic Management, 0(0), 1–13.
https://doi.org/10.1080/09537325.2021.1988070
Toapanta, S. M. T., Quimi, F. G. M., Salazar, R. F. R., & Gallegos, L. E. M. (2020).
Cryptographic Algorithms to Mitigate the Risks of Database in the Management of a
Smart City. In X.-S. Yang, S. Sherratt, N. Dey, & A. Joshi (Eds.), Fourth
International Congress on Information and Communication Technology (pp. 449–
461). Springer. https://doi.org/10.1007/978-981-32-9343-4_36
Torlai, G., Mazzola, G., Carrasquilla, J., Troyer, M., Melko, R., & Carleo, G. (2018). Many-
body quantum state tomography with neural networks. Nature Physics, 14(5), 447–
450. https://doi.org/10.1038/s41567-018-0048-5
Trabesinger, A. (2017). Quantum leaps, bit by bit. Nature, 543(7646), S2–S3.
https://doi.org/10.1038/543S2a
Tsai, I.-M., Yu, C.-M., Tu, W.-T., & Kuo, S.-Y. (2005). A Secure Quantum Communication
Protocol Using Insecure Public Channels. In R. Sasaki, S. Qing, E. Okamoto, & H.
Yoshiura (Eds.), Security and Privacy in the Age of Ubiquitous Computing (pp. 113–
126). Springer US. https://doi.org/10.1007/0-387-25660-1_8
Uhlig, R. P., Dey, P. P., Jawad, S., Sinha, B. R., & Amin, M. (2019). Generating Student
Interest in Quantum Computing. 2019 IEEE Frontiers in Education Conference (FIE),
1–9. https://doi.org/10.1109/FIE43999.2019.9028378
Vivekanadam B. (2020). Analysis of Recent Trend and Applications in Block Chain
Technology. Journal of ISMAC, 2(4), 200–206.
https://doi.org/10.36548/jismac.2020.4.003
Wallnöfer, J., Melnikov, A. A., Dür, W., & Briegel, H. J. (2020). Machine Learning for Long-
Distance Quantum Communication. PRX Quantum, 1(1), 010301.
https://doi.org/10.1103/PRXQuantum.1.010301
38
Weder, B., Breitenbücher, U., Leymann, F., & Wild, K. (2020). Integrating Quantum
Computing into Workflow Modeling and Execution. 2020 IEEE/ACM 13th
International Conference on Utility and Cloud Computing (UCC), 279–291.
https://doi.org/10.1109/UCC48980.2020.00046
Wei, Q., & Zhang, F. (2019). Mining New Scientific Research Ideas from Quantum
Computers and Quantum Communications. 2019 14th International Conference on
Computer Science Education (ICCSE), 1069–1074.
https://doi.org/10.1109/ICCSE.2019.8845476
Xie, J., Tang, H., Huang, T., Yu, F. R., Xie, R., Liu, J., & Liu, Y. (2019). A Survey of
Blockchain Technology Applied to Smart Cities: Research Issues and Challenges.
IEEE Communications Surveys Tutorials, 21(3), 2794–2830.
https://doi.org/10.1109/COMST.2019.2899617
Yetis, H., & Karakoes, M. (2021). Investigation of Noise Effects for Different Quantum
Computing Architectures in IBM-Q at NISQ Level. 2021 25th International
Conference on Information Technology (IT), 1–4.
https://doi.org/10.1109/IT51528.2021.9390130
You, X., Miao, X., & Liu, S. (2009). Quantum computing-based Ant Colony Optimization
algorithm for TSP. 2009 2nd International Conference on Power Electronics and
Intelligent Transportation System (PEITS), 3, 359–362.
https://doi.org/10.1109/PEITS.2009.5406879
Zhang, F. (2020). Science Development Fault of and Prediction on Quantum Computers and
Quantum Communication. 2020 15th International Conference on Computer Science
Education (ICCSE), 353–358. https://doi.org/10.1109/ICCSE49874.2020.9201807
Zhang, F., Wu, T.-Y., Wang, Y., Xiong, R., Ding, G., Mei, P., & Liu, L. (2020). Application
of Quantum Genetic Optimization of LVQ Neural Network in Smart City Traffic
Network Prediction. IEEE Access, 8, 104555–104564.
https://doi.org/10.1109/ACCESS.2020.2999608
Zhang, X., Xu, C., Jin, C., & Wen, J. (2015). A post-quantum communication secure identity-
based proxy-signcryption scheme. International Journal of Electronic Security and
Digital Forensics, 7(2), 147–165. https://doi.org/10.1504/IJESDF.2015.069607
Zhu, Q., Loke, S. W., Trujillo-Rasua, R., Jiang, F., & Xiang, Y. (2019). Applications of
Distributed Ledger Technologies to the Internet of Things: A Survey. ACM
Computing Surveys, 52(6), 120:1-120:34. https://doi.org/10.1145/3359982
