Big Data in Smart Cities - Utilizing Information Technology for Effective Solutions

Running head: BIG DATA IN SMART CITIES
Big data in smart cities
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Rationale of the project:
Understanding the Problem Domain:
The human world is developing rapidly. All the cities are turning to be more and more
populated. Their social, financial and political aspects are turning to be more complex. The
incensement of the fast population has been making all the processes of the government to be more
time-consuming. In such a situation, there are few issues that are emerging in the cities. These
involve the slowing down of the government services, rise of crime rate, environmental pollution
and limitation of the resource. At this case, the government has been able to hold the stability that
was among the community. This is to secure the self-destruction. Nevertheless, to control the fast
growth of the society. This is through utilizing the usual processes and government services. This,
with more number of staffs have been sufficient. It needs a more developed, quick and accurate
mechanism for providing proper solutions effectively. It is proven by information technology that its
influence lies in fact to provide suitable outcomes. It is known that smart cities have been utilizing
information technology to perform and handle the activities and tasks in cities. Thus, the
transformation of the “big old city” is to be changed to the smart city. It can be considered as the
most effective solution meant for the problem emerging to modern cities.
Discussion on the current purpose and the justification:
As per Townsend, the uses of smart cities, there are various uses of distinct kinds of
collection of electronic data processes. This is to control the order, laws and resources of the cities
effectively. The smart cities are able to control most of the daily activates of the council of the city
with the help of computers. Here, the IoT devices are utilized for processing of data collections. It is
defined in "Role of Big Data and Analytics in Smart Cities" (2016) that a huge data set has been
assessed to reveal those patterns. It also includes the trends and associations for gaining the solutions

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and conclusions for various issues. Moreover, big data has been providing the potential for the cities
in gaining the expensive data that is gathered through IoT devices. Besides, the data can be utilized
to enforce the order and law. This is to develop efficient “facility management services” along with
massive extension of various additional benefits. Though taking into consideration of the
aforementioned realities, the current project undertakes the research on various approaches to do
away with the concerns in smart cities. This is through the bid data by making a discussion on the
deployment of different types of big data into smart cities.
Analysis of the present theoretical and related conceptual framework:
It is discussed by Ram Sharan Mehta (2018), that the theoretical framework reveals the
structure was supporting and holding the research theory. On the other hand, the conceptual
framework makes an analysis of various contexts and variations for the issues and then implement
the best. The current project utilizes the theoretical approach. For providing support to theoretical
framework needed, here, an “inquiry-based learning” has been utilized. This is helpful due to the fact
that the research framework related to the project. Again, as mentioned by Pedaste et al. (2015), this
type of learning delivers the educational strategy. Here, the researchers can flow the practices for
discovering the latest casual relations. Here, the learner can formulate the hypothesis and is able to
test them. This is trough conducting the experiments by undertaking various observations. It is seen
as the approach to resolve the issues, including the skills of problem solving. Here, the inquiry-based
learning comprises of distinct phases and all the phases comprises of various huge groups. These are
been made of various types of smaller sets of different groups. As demonstrated in image below, the
thirty-four inquiry group’s activities are assimilated with greater groups and ultimate to stay with the
common phases.