Master Research Proposal in Data Analytics | Report

MASTER RESEARCH PROPOSAL
IN DATA ANALYTICS
Faculty of Data
Analytics Dublin
Business school
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Author: Nishkriya Janakiraman Supervisor:
E-mail: [e-mail] E-mail:
Phone: [phone] Phone:
Defense
Planned:
List of Contents
Proposed Topic................................................................................................................... 3
Research hypothesis.......................................................................................................... 3
Introduction to the research............................................................................................ 3
Overview of literature review........................................................................................... 4
Literature review................................................................................................................ 4
Literature Gap..................................................................................................................... 5
Methodology and Implementation................................................................................... 6
Future work......................................................................................................................... 6
References........................................................................................................................... 7
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Proposed Topic
Use of machine learning to improve the Internet of Things based applications
Research hypothesis
Research hypothesis is defined as the type of statement which helps in
understanding the probable (Kumar and Gandhi 2018) outcome of a research
paper. The testable proposition of a research is also identified with the help of
research hypothesis (Lade, Ghosh and Srinivasan 2017). There are diverse
categories of research hypothesis which are considered in research proposals such
as the null hypothesis (H0) and alternative hypothesis (H1).
The hypothesis of this research is as follows:
H0: Machine Learning techniques have no impact on the IoT based devices.
H1: Machine Learning techniques can improve the IoT based applications.
Introduction to the research
There are diverse categories of challenges related with the use of IoT based devices
such as the scalability issues, interoperability issues, and data security issues (Lee
et al. 2016). Each of these issues is having a direct adverse impact on the
performance of the IoT devices (Outchakoucht, Hamza and Leroy 2017).
Machine learning algorithms is very much useful to improve the capability of any
advanced system these days such as the Management Information System (Lee et
al. 2018).
The notable determination of this poster is to identify whether the challenges of IoT
devices can be resolved using Machine Learning techniques or not. Secondary data
collection procedure shall be considered in this research.
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