University Assignment: Machine Learning for Intelligent IoT Decisions

This report delves into the application of machine learning to enhance intelligent decision-making within the Internet of Things (IoT). It begins by outlining the core concepts of IoT and machine learning, emphasizing their interconnectedness and the potential for data analysis to drive optimal outcomes. The report then provides a comprehensive literature review, examining past and present works in this field, and identifies the project's requirements. It proposes and compares various methodologies for implementing machine learning in IoT, evaluating their efficiency, simplicity, and adaptability to different applications. The report highlights two applicable methodologies and discusses their implementation, ultimately concluding with insights on how to leverage machine learning for more effective and efficient decision-making in IoT systems. The report also considers the commercial implications of these technologies, providing a well-rounded perspective on the topic.

Running head: INTERNET OF THINGS
Internet of Things
Topic: Machine learning to make intelligent decisions in Internet of Things
Name of the Student
Name of the University
Author Note:

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Abstract
The use of machine leaning can be made in order to know what decision has to be taken to
benefit. The machine learning makes the use of various forms of techniques and helps in the
identification of the future scope of the decision. The process of machine learning analyses a
number of data at the particular topic before giving the best possible answers. The report puts
forward the idea how the machine learning technology can be used to make the intelligent
decisions in Internet of things (IOT). The report puts forward the concept of machine learning in
internet of things. The various methodologies of internet of things technology is also presented
here, which are important for the making of the important decisions. The use of one of the
methodologies has been made and how that methodology can implement the machine learning
technology is also presented in the report. Among the five methodologies that have been
presented two methodologies those are applicable here have been discussed. Lastly, the report
concludes how the machine learning process can be used more efficiently and effectively.

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Table of Contents
Introduction:....................................................................................................................................4
Purpose of the report....................................................................................................................4
Expected format of the report......................................................................................................5
Problem statement.......................................................................................................................5
Introduction to the Problem:........................................................................................................6
Structure of the Report:...............................................................................................................6
Literature Review:.......................................................................................................................7
Past and Present Works:..........................................................................................................7
Requirement for the Project:....................................................................................................8
Methodologies for Overcoming the Problem:.........................................................................8
Making smart decisions in the internal of the Organization:...................................................9
Methodologies:............................................................................................................................9
Methodology 1:........................................................................................................................9
Methodology 2:......................................................................................................................10
Methodology 3:......................................................................................................................11
Methodology 4:......................................................................................................................13
Methodology 5:......................................................................................................................14
Comparison of methodology.....................................................................................................15
Efficiency...............................................................................................................................15

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Simplicity...............................................................................................................................15
Extension into another kinds of applications.............................................................................16
Time saving of internet of things...............................................................................................16
Commercial issues.....................................................................................................................17
Implementation of Methodology:..............................................................................................20
Conclusion:....................................................................................................................................23

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Introduction:
The internet of things involve the connection and the interaction of a number of devices.
A large number of devices are connected together in a network. All the devices are connected
and the devices can interact with each other. The various applications of the internet of things
such as the smart city or the smart street lighting system can easily be controlled by the use of
machine learning. The machine learning concept compares the various data and puts forward the
best possible solution. The concept of machine learning can also be used for finding the cyber
security solutions. The report shows how the concept of machine learning technology can be
used in internet of things for making intelligent decisions. The report also puts forward the
methodologies
Purpose of the report
The internet of things concept is the interconnection of a large number of devices to a
certain network that will help in the interaction with the other devices that are present in the
network (Kim et al., 2016). The devices may involve the various sensors, actuators and the other
important devices. The connection to the same network helps in interaction with the large
number of devices at the same time. If any message is to be posted to a large number of systems
at the same time then the use of the internet of things can be brought to practice. The machine
learning process involves the use of the system in order to detect the possible outcomes from a
particular project. The machine learning process is helpful in the execution of the various tasks.
The new form of tasks that the machine may not be able to perform is recorded and the solution
is told to the machine from the other sources. The solution, which was new to the machine is
now stored in the machine such that if such a problem arises in the future then the task would be

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solved easily by the machine learning process. The machine learning may not be able to find
some solutions or predict a number of things. The use of internet of things technology may be
helpful in the finding of the various solutions. The system or the devices that are connected to the
internet of things framework can be able to find the solution for the system.
Expected format of the report
The report discusses about how machine learning can be used in the decision- making
intelligently in the internet of things network. The report presents a literature review, which puts
forward the works in the topic, which is to be discussed. The report discusses the various
methods that can be used in order to implement the machine learning process in the internet of
things. The various methodologies are then compared on the various fields and then the best
method that suits the project is then selected.
Problem statement
Rapid developments in hardware, software as well as communication technologies have
allowed the emergence of internet-connected sensory devices. It provides observation as well as
data measurement from physical world. It is estimated that total number of internet-connected
devices will be used between 20 to 25 billion by 2020 (Zhao & Ge, 2013). As the numbers
increase and technologies become mature, the volume of date published will also increase. The
internet-connected devices technology are referred as IOT that continues to extend current
internet through providing connectivity as well as interaction between physical and cyber
volumes (Zhang et al, 2014). Moreover, increased volume of IoT produces Big Data
characterized by velocity in terms of location and time dependency.

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Introduction to the Problem:
Many of the organization cannot take decisions in a proper manner. Due to the wrong
decisions taken by the organization many of the projects end up in failure. Thus the making of
the proper decisions is important for the smooth running of the organization. The making of the
intelligent decisions such as the use of the correct form of technology for the correct purpose is
required. The main problem lies in the choice of the technology and the analysis of the
technology. A proper cost analysis for the implementation of the technology should be done so
that the organization does not have to face the problem in the later half.
Structure of the Report:
The report discusses about the topic and the purpose that the report solves. The report
discusses about the concept of the internet of things and the machine learning technology. The
report then discusses how the machine learning process can be used for the taking of the
intelligent decisions in the IoT in an organization. The literature review presents the use of the
machine learning concept previously and presently for the making of the intelligent decisions.
The use of the various organization has been made in order to properly understand the concept of
implementation of the machine learning and show the works of the previous and the recent times.
The three parts of the reports involve:
 The introduction of the report containing the purpose of the report, the structure of
the report and the summary of the report
 The second part involves the literature review, which gives the various
information on the basis of the past and the present works that is done.
 The last part of the report involves the various methodologies that are involved
and the methodology, which is suitable for the present scenario.

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Literature Review:
Past and Present Works:
The Machine learning process can be helpful in the identification of the process of the
what will be good and what would affect in a bad manner. The use of machine leaning can be
made in order to know what decision has to be taken to benefit (Sridhar & Smys, 2017). The
machine learning makes the use of various forms of techniques and helps in the identification of
the future scope of the decision. The process of machine learning analyses a number of data at
the particular topic before giving the best possible answers(Zhao & Ge, 2013). This is how the
concept of machine learning can be made to make the important decisions in the field of internet
of things. The internet of things can present with a number of solutions to a particular topic.
Among these solutions the most efficient solution is to be found, which can be done with the
help of machine learning process. The intelligent decision that is to be taken in this case is done
with the help of machine learning. The machine learning process can help in the analyzing of the
various data on the fields of the different solutions that are given. The data that best represents
the positives for a particular solution is then selected. The mechanism of machine learning can be
extended further into the various other fields(Ding et al.,2018). This will help in the analyzing of
the data. The machine learning basically performs the task of the data analysis and puts forward
the best possible solution based on the previous solution that had occurred in the past.
The Google makes the use of machine learning to continuously improve its status and
position in the market. The Google provides the best search results and the most compressed
search results by making the use of the machine learning technology. The machine learning
technology implementation helps Google in providing the services it continues to provide over
the years(Zhang et al, 2014). The concept of machine learning has also been applied to the

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various photos and the videos of the Google, which also helps in the management of the large
number of photos and videos in an efficient manner. The machine learning procedure can also
manage the huge amount of the data. The photos and the videos, which have to be shown to the
are checked with the help of the machine learning. Thus, all these important and the intelligent
decisions are taken with the help of the machine learning concept.
Requirement for the Project:
The project requires trained personnel for the carrying out the project as the technology
has to be applied in a proper manner. The systems should be in a proper working condition as the
improper functioning of one may lead to the improper functioning of the other systems. This may
happen as all the systems are connected by the help of internet of technology. If any one of the
system is vulnerable to attack then the other may also have a chance of getting attacked. All the
requirements for the proper implementation of the machine learning concept should be
Methodologies for Overcoming the Problem:
Iris is the other company, which makes the use of the machine learning in order to take
the intelligent decisions that are involved in internet of things. The Iris company is responsible
for the carrying out of the research and the development of various fields. The Iris organization
is basically responsible for the finding out of those articles which are trying to suppress the
importance of the relevant and the truthful source of the data that are present (Sadeghi,
Wachsmann & Waidner, 2015). The company looks to the providing of the correct and the
genuine information, which is hidden under the various articles that have been published with
irrelevant information. There are articles, which are written by the various authors without the
reference of the proper data. In this process the actual data gets lost and the wrong articles are
reviewed. Iris is responsible for the holding on the actual data. People have been referring to Iris

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in order to get the relevant information. The company makes the working possible by following
the machine learning process, which performs the survey on a number of data and calculates on
an automatic manner. As the use of machine learning is made for the purpose of surveying the
data it is possible for the organization to provide the correct information and the detailed survey
of the data that are collected (Meidan et al, 2017). This also help the organization in getting hold
of the market and there are a large number of customers who seek the help of the website in
order to know about the various information and the data. Iris has even outclassed the Google
Scholar.
Making smart decisions in the internal of the Organization:
The organizations by the implementation of the machine learning concept not only to
gain the benefit in the market or to take important decisions in IoT but also in order to take the
important decisions related to the internal works of the organization. By machine learning the
ways in which the organization can be expanded and the profit of the business can be improved
can also be done. The intelligent decisions are involved within the organization as well for the
smooth running of the organization. This can be done by the method of the pattern recognition,
which is a part of the machine learning(Sicari et al., 2015). By the help of the pattern
recognition, one can check if everybody is doing the work in a proper manner or not. This can be
done by the help of the tracking the work that is done.
Methodologies:
Methodology 1:
The research methodology in first journal is nothing but a theoretical kind of defining and
presenting the basics and various kinds of strategic decision from various kinds of resource in

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domain of field and science of business life(Dunaway et al,2017). However, this kind of
approach contains certain number of advantages and disadvantages like those of effective
practices.
From point view, various kinds of emphasis have been provided regarding subjective and
individual kinds of findings (Zhu et al., 2015). The truth and reality does not relate to the fact of
various figures and understanding considering various kinds of subjective areas which are
generally encountered (Ding et al.,2018).
The actual idea or topic of Internet of things focus on standardization (Wu et al.,2014).
Apart from that research is nothing but a combination of various kinds of research things. One of
the major kinds of targets focus on qualitative kinds of research things, which can be used for
generalization of findings in the form of conclusions. In this paper an idea has been provided
regarding decision making for supply chain and things related to vice-versa.
Methodology 2:
In the second methodology the idea or concept of data and functionality, which can be
accessed from any location and various kinds of device has been introduced (Bello &Zeadally,
2016). In this particular case the fitness bracelet generally acts like a IOT sensor along with
providing means of accessing and consuming of data (Zhong et al., 2017). This particular device
also subsumes other kinds of devices like pedometer by the help of software functionality. If the
provided data is aggregated across a population of users and other kinds of datasets, new kinds of
insights which can easily put focus on epidemiological kind of data, activity level of population,
various kinds of lifestyles and data from demographic (Lee, Kao & Yang,2014). This kind of

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information has a strong kind of value from marketers, healthcare services, insurance firm or
organization and government kind of agencies.
Machine learning algorithm are generally used for making of prediction related to various
kinds of data patterns (Posada, 2015). The same of machine learning and predictive algorithm are
used for a basis for a number which is connected with intelligent type of consumer devices.
Other kinds of consumer devices are generally leaned from various kinds of voice pattern.
Optimization algorithm also makes use of various kinds of learning mechanism which is
considered to be specific to both sensors and intelligent device which generally interact under
various kinds of dynamic condition (Wang et al.,2016). This kind of parameters cannot go
beyond certain number of parameters. The algorithm is responsible for sense, response and
various kinds of adaptation.
Methodology 3:
In the methodology of thirdjournal the idea or concept of WSN. Machine learning is
generally considered to be viable kind of solution for reducing capital value and operational kind
of expenditure, as well as improving the life of network (Baron &Musolesi, 2017). Sensors are
considered to be key things which helps in tracking of objects or things of the emerging kind of
networks. The aggregation of various kinds of networks form a network whose ultimate goal is
to generate and aggregation of data for various kinds of internal purpose. The data which is
generated from the various kinds of sensors needs to be finely tuned prior to undertaking of any
kind of analytical procedures. The majority of machine learning techniques makes use of
combination kind of framework for feature extraction and modification of certain number of
algorithms which are used for identifying handwriting or speech (Kumar, Goyal& Varma, 2017).
There are various kinds of algorithm on sensory data like telemedicine, quality of air monitoring,