Paper Title (use style: paper title)
Doi: XXXXXXXXXX/issn XXXXXXXXXX
This is an open access article distributed under the Creative Commons Attribution License 91
A Survey of Data Mining Implementation in Smart
City Applications
1st Zainab Salih Ageed
Translation Dept.
Nawroz University
Duhok, Iraq
XXXXXXXXXX
2nd Subhi R. M. Zeebaree
Culture Center
Duhok Polytechnic University
Duhok, Iraq
XXXXXXXXXX
3rd Mohammed A. M.Sadeeq
Quality Assurance
Duhok Polytechnic University
Duhok, Iraq
XXXXXXXXXX
4th Shakir Fattah Kak
Information Technology Dept.
Duhok Polytechnic University
Duhok -Iraq
XXXXXXXXXX
5th Zryan Najat Rashid
Computer Network Dept.
Sulaimani Polytechnic University
Sulaimani-Iraq
XXXXXXXXXX
6th Azar Abid Salih
Information Technology Management
Dept.
Duhok Polytechnic University
Duhok -Iraq
XXXXXXXXXX
7th Wafaa M. Abdullah
Computer Science Dept.
Nawroz University
Duhok, Iraq
XXXXXXXXXX
https:
doi.org/ XXXXXXXXXX/qaj.v1n2a52
Abstract— Many policymakers envisage using a community
model and Big Data technology to achieve the sustainability
demanded by intelligent city components and raise living
standards. Smart cities use different technology to make their
esidents more successful in their health, housing, electricity,
learning, and water supplies. This involves reducing prices and
the utilization of resources and communicating more
effectively and creatively for our employees. Extensive data
analysis is a comparatively modern technology that is capable
of expanding intelligent u
an facilities. Digital extraction has
esulted in the processing of large volumes of data that can be
used in several valuable areas since digitalization is an essential
part of daily life. In many businesses and utility domains,
including the intelligent u
an domain, successful exploitation
and multiple data use is critical. This paper examines how big
data can be used for more innovative societies. It explores the
possibilities, challenges, and benefits of applying big data
systems in intelligent cities and compares and contrasts
different intelligent cities and big data ideas. It also seeks to
define criteria for the creation of big data applications for
innovative city services.
Keywords— Data Computing, Internet of Things, Data
Mining, Smart City, Cloud Computing.
I. INTRODUCTION
The Internet has experienced immense growth in recent
years, and its content is continually growing and extending.
The Internet of Things is viewed as an Internet application
creation [1]. This means that customers, customers, paper,
objects, and paper are all linked through contact and
exchange of information, but the Internet is central to IoT
[2].
The International Telecommunications Union Internet
Report provides the following definition of IoT: The
connection between the objects and the Internet and the
interaction and communication of information through
different protocols is achieved through various kinds of
sensor systems to achieve an intelligent network identity,
location, management, and control [3]. It has three different
features: Intelligent Twitter sharing in real-time [4].
There have also been many studies in this area on
innovative and wired companies' needs. There have been
many facts, such as fixed and mobile sensors, internet data,
and social data, from several outlets [5, 6].
Just a few of the data collection fields include agriculture,
civic infrastructure, catastrophe management, education and
apprehension, electricity, the efficiency of the environment,
health and wellbeing, including medical, resilience, welfare,
social services, telecommunications, transport, and mobility
[7]. In several ways, a Smart City should be able (including
Big-Data, traditional data sources, and personal information
for users) to retrieve historical and real-time data from a
wide range of sources [8].
The paper structure: have the Background Theory in
Section II, Literature Review In Section III, discussion in
Section IV, the conclusion in section V.
mailto: XXXXXXXXXX
mailto: XXXXXXXXXX
mailto: XXXXXXXXXX
mailto: XXXXXXXXXX
mailto: XXXXXXXXXX
mailto: XXXXXXXXXX
mailto: XXXXXXXXXX
https:
doi.org/ XXXXXXXXXX/qaj.v1n2a52
92
II. BACKGROUND THEORY
A. Data Mining
Significant figures are explosive, with an expected annual
increase in global data production of 40% compared to just 5
percent in global IT expenditure. About 90% of digitized
data worldwide have been registered over the past two years
[9]. As a result, many municipalities worldwide have started
using big data to help intelligent cities develop and sustain
[10]. By recognizing their key smart city features, the cities
have retained standards, values, and specifications for
innovative city applications. Sustainability, long service
cycle, governance, improved quality of life, and smart use of
natural and u
an resources comprise these qualities [11].
Smart City's well-defined components are mobility,
governance, climate, people, and applications and services
such as healthcare, transport, smart education, and electricity
[12]. Sustainability, longevity, management, more
outstanding living standards, and intelligent utilization of
natural and u
an resources are all virtues. The smart city is
well developed in mobility, governance, atmosphere,
inhabitants, wellbeing, mobility, smart education, and energy
facilities [13, 14]. Big data has developed into a strategic
weapon of immense potential importance that promotes
industry's upgrade and growth as a critical driver for
advancement [15]. It also affects science and methodology.
Big data offers many benefits, including a large pool of
capital and specialized training measurement technology
[16]. As a result of large, complex, and volatile data, the
storage and computational bottlenecks impede conventional
data processing systems [17]. Working environments
improved with time and resolved a range of measurement
problems, including administrative functions at a high level,
program upgrades, and the use of other computer series [18].
Big data mining is a service that collects the essential
information and expertise from and provides the customer
with a large, complex, competitive, high-volume, and low-
density data set [19]. It helps to find valuable knowledge and
expertise instead of traditional data mining. There are,
however, technological, historical shortcomings, data
environments, and mining scope [20]. The diagram below
shows the layout of big data based on data mining
techniques. The three levels of the architecture are networks,
operating layers, and facility supports [21]:
1) Layer platform: The integration of big mixed data
with a range of support technologies dependent on cloud
infrastructure can support big data mining. The integration
of big mixed data with a range of cloud computing support
technologies can support them. Big data mining is also
supported [22]. This cloud environment can not only
provide the rest of the world with information, hardware,
and software. However, it can also quantify moving data to
allow more efficient preprocessing, analysis, and mining of
complex data in several sources [23].
2) Functional layer: this layer can interpret and dig out
data depending on users' requirements. The high efficiency
of storages and computers made available to users as
visuals, data sources, and other high-scalabilité and
expandable technologies is essential for scientific, mining,
and other tools [24].
3) Application Level Layers: Big data mining
communicates automatically with customers, service
providers, and users. The mining results lead to
preprocessing, analysis, and extraction from various
dynamic data sources [25].
B. Smart City and Cloud
City and metropolitan areas are abstruse social
ecosystems, like local government, residents, and
organizations [26]. The ICT is becoming progressively
facilitating and enabling the ICTs to meet particular criteria
elating to key themes, including enterprise and job growth,
economic development, energy and water, public security,
the atmosphere, health care, education, and public services.
Simultaneously, u
an spending is gradually being pressured
y the new tumultuous global economic crisis, which is
causing disastrous impacts not only on maintaining and
upgrading existing ICT infrastructures and facilities but also
on future innovation policies [27]. However, it has been
identified, as an exemplary example of an answer to cu
ent
and future complex challenges of the resource efficiencies,
educing emissions, sustainable health care services for older
people, strengthening young people, and integral cities,
which can be used for intelligent cities, information cities,
digital towns, e-cities, and virtual towns. Smart cities, with
their cameras, built-in computers, vast data
Fig. 1. Smart city G-Cloud platform [28].
Fig. 2. Pilot smart city G-Cloud project [28].
93
Sets and knowledge, and responses have been characterized
to generate a specific spatial intelligence and creativity [29].
It proposes a comprehensive concept of a smart city that
embodies a city that fosters sustainable economic
development and high quality of life through investment in
human and social capital, transportation and modern ICT
infrastructure, and sound management of natural resources
y participatory governments [30]. The requirement for
investing in modern ICT and participatory government
equirements include, in particular, the concept of
empowering cities [31].
A form of democratic innovation that first becomes
popular with the increasing capacity of businesses and
consumers, using software products and services, t Two of
the main issues highlighted in the definition mentioned
above [32]. Propose a typology that defines the traditional
oles inherent in the intelligent City that include smart
market (competitiveness), intelligent citizens (social and
human capital); intelligent administration (intervention);
smart mobility (transport and ICTs) (quality of life) [33]. It is
possible to use creative ICT to build sustainable strategies
that cut expense, concentrate attention on top public
challenges and align groups with common agendas by
providing visual and innovative leadership [34]. The role of
innovation facilitators in vital sectors such as industry,
health, the environment, and ICT is played by cities
worldwide. In their administration of daily public utilities,
city councils look for
ight, cost-efficient ICT strategies
[35]. City and u
an policymakers will use advanced low-
cost technology tools such as cloud analytics to analyze data
and market indicators for effective decision-making and
predict problems to