Synergistic Interaction of Big Data with Cloud Computing for Industry 4.0 (Innovations in Big Data and Machine Learning)

217 Pages·2022·34.352 MB·English

by  Indranath Chatterjee (editor), Rajanish K. Kamat (editor), Sheetal S. Zalte-Gaikwad (editor)

i
Synergistic Interaction of Big
Data with Cloud Computing for
Industry 4.0
The idea behind this book is to simplify the journey of aspiring readers and researchers
to understand the convergence of Big Data with the Cloud. This book presents the
latest information on the adaptation and implementation of Big Data technologies in
various cloud domains and Industry 4.0.
Synergistic Interaction of Big Data with Cloud Computing for Industry 4.0
discusses how to develop adaptive, robust, scalable, and reliable applications that
can be used in solutions for day-t o- day problems. It focuses on the two frontiers —
Big Data and Cloud Computing – and reviews the advantages and consequences of
utilizing Cloud Computing to tackle Big Data issues within the manufacturing and
production sector as part of Industry 4.0. The book unites some of the top Big Data
experts throughout the world who contribute their knowledge and expertise on the
different aspects, approaches, and concepts related to new technologies and novel
findings. Based on the latest technologies, the book offers case studies and covers
the major challenges, issues, and advances in Big Data and Cloud Computing for
Industry 4.0.
By exploring the basic and high- level concepts, this book serves as a guide for
those in the industry, while also helping beginners and more advanced learners under-
stand both basic and more complex aspects of the synergy between Big Data and
Cloud Computing.
ii
Innovations in Big Data and Machine Learning
Series Editors: Rashmi Agrawal and Neha Gupta
This series includes reference books and handbooks that will provide conceptual
and advanced materials that cover building and promoting the field of Big Data and
Machine Learning, which includes theoretical foundations, algorithms and models,
evaluation and experiments, applications and systems, case studies, and applied
analytics in specific domains or on specific issues.
Artificial Intelligence and Internet of Things
Applications in Smart Healthcare
Edited by Lalit Mohan Goyal, Tanzila Saba, Amjad Rehman, and Souad Larabi
Reinventing Manufacturing and Business Processes through Artificial
Intelligence
Edited by Geeta Rana, Alex Khang, Ravindra Sharma, Alok Kumar Goel, and
Ashok Kumar Dubey
Convergence of Blockchain, AI, and IoT
Concepts and Challenges
Edited by R. Indrakumari, R.Lakshmana Kumar, Balamurugan Balusamy, and
Vijanth Sagayan Asirvadam
Exploratory Data Analytics for Healthcare
Edited by R. Lakshmana Kumar, R. Indrakumari, B. Balamurugan, Achyut Shankar
Information Security Handbook
Edited by Abhishek Kumar, Anavatti G. Sreenatha, Ashutosh Kumar Dubey, and
Pramod Singh Rathore
Natural Language Processing In Healthcare
A Special Focus on Low Resource Languages
Edited by Ondrej Bojar, Satya Ranjan Dash, Shantipriya Parida, Esaú Villatoro Tello,
Biswaranjan Acharya
Synergistic Interaction of Big Data with Cloud Computing for Industry 4.0
Edited by Sheetal S. Zalte-Gaikwad, Indranath Chatterjee, and Rajanish K. Kamat
For more information on this series, please visit: www.routle dge.com/ Inno vati ons-
in- Big- Data- and- Mach ine- Learn ing/ book- ser ies/ CRCIB DML
iii
Synergistic Interaction

of Big Data with Cloud
Computing for Industry 4.0
Edited by
Sheetal S. Zalte-Gaikwad, Indranath Chatterjee,
and Rajanish K. Kamat
iv
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DOI: 10.1201/ 9781003279044
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Contents
Preface ......................................................................................................................vii
Editors’ Biographies .................................................................................................ix
Contributors ..............................................................................................................xi
Chapter 1 Big Data Based on Fuzzy Time- Series Forecasting for
Stock Index Prediction .........................................................................1
Ruchismita Majumder, Partha Pratim Deb,
and Diptendu Bhattacharya
Chapter 2 Big Data- Based Time- Series Forecasting Using FbProphet for
the Stock Index ...................................................................................25
Debankita Mukhopadhyay, Sourabarna Roy, and
Partha Pratim Deb
Chapter 3 The Impact of Artificial Intelligence and Big Data in the
Postal Sector .......................................................................................47
Mary Olawuyi Ojo, Indranath Chatterjee,
and Sheetal S. Zalte-Gaikwad
Chapter 4 Advances in Cloud Technologies and Future Trends .........................61
Indra Kumari, Jungsuk Song, and Buseung Cho
Chapter 5 Reinforcement of the Multi- Cloud Infrastructure with
Edge Computing .................................................................................75
L. Steffina Morin and P. Murali
Chapter 6 Study and Investigation of PKI- Based Blockchain Infrastructure .....87
Rashmi Deshmukh and Sheetal S. Zalte-Gaikwad
Chapter 7 Stock Index Forecasting Using Stacked Long Short- Term
Memory (LSTM): Deep Learning and Big Data ................................97
Debasmita Pal and Partha Pratim Deb
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vi Contents
Chapter 8 A Comparative Study and Analysis of Time- Series and Deep
Learning Algorithms for Bitcoin Price Prediction ...........................113
Sagar Chakraborty, Nivedita Das, and Kisor Ray
Chapter 9 Machine Learning for Healthcare.....................................................133
Udeechee and T.V. Vijay Kumar
Chapter 10 Transfer Learning and Fine- Tuning- Based Early Detection of
Cotton Plant Disease ........................................................................149
Himani Bhatheja and N. Jayanthi
Chapter 11 Recognition of Facial Expressions in Infrared Images for Lie
Detection with the Use of Support Vector Machines .......................163
Rupali Dhabarde, D.V. Kodavade, Rashmi Deshmukh,
and Sheetal S. Zalte-Gaikwad
Chapter 12 Support Vector Machines for the Classification of Remote
Sensing Images: A Review ...............................................................175
Parijata Majumdar, Suchanda Dey, Sourav Bardhan,
and Sanjoy Mitra
Chapter 13 A Study on Data Cleaning of Hydrocarbon Resources under
Deep Sea Water Using Imputation Technique- Based Data
Science Approaches ..........................................................................181
Dipjyoti Deb
Index ......................................................................................................................199
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Preface
The computing and data sector has seen tremendous changes in platform scale and
application reach during the last decade. Computers, smartphones, clouds, and social
media platforms need outstanding performance and a high level of machine intelli-
gence. We are approaching a period of big data analysis and cognitive computing.
The extensive use of mobile phones, storage, and computing clouds, the resurrection
of artificial intelligence in practice, extended supercomputer applications, and broad
deployment of Internet of Things (IoT) and Blockchain technologies are indicators of
this popular trend. This book, entitled Synergistic Interaction of Big Data with Cloud
Computing, aims to provide state- of- the- art research in the significant areas of com-
puter science, such as Big Data, Cloud Computing, Blockchain, Machine Learning,
and IoT technologies.
Big data, low- cost commodity technology, and new information management and
analytic tools have created a watershed moment in data analysis history. Due to the
apparent confluence of these developments, we now have the capabilities to ana-
lyze massive data sets quickly and inexpensively for the first time in history. These
advancements are not hypothetical or straightforward. They are a significant step for-
ward and have clear potential to achieve massive benefits in efficiency, productivity,
revenue, and profitability.
Both big data and cloud computing play a significant part in our digital world.
It is undeniable. When the two are combined, people with excellent ideas but few
resources have a chance to succeed in business. These technologies also enable
existing firms to use data that they already collect but could not previously analyze.
Artificial intelligence and other current components of cloud infrastructure’s trad-
itional “Software as a Service” architecture enable organizations to gain insights from
their big data. Businesses can take advantage of all of this for a bit of cost with a well-
designed system, leaving competitors who refuse to embrace these new technologies
in the dust.
The technologies that will be covered in this book are fundamental in the era of
Industry 4.0. This knowledge is highly essential for readers, starting from beginner
students to advanced level academicians. The confluence of big data, cloud com-
puting, and machine learning were always examples of highly influential research.
However, this book introduces the confluence of big data and blockchain technolo-
gies, which is novel in the field. We believe this will pave a path to a new way of
thinking.
The Editors:
Sheetal S. Zalte-Gaikwad
Indranath Chatterjee
Rajanish K. Kamat
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ix
Editors’ Biographies
Sheetal S. Zalte-Gaikwad is an assistant pro-
fessor in Computer Science Department at
Shivaji University, Kolhapur, India. She pursued
a Bachelor of Computer Science from Pune
University, India, in 2002 and a Master of
Computer Science from Pune, India, in the year
2004. She earned her Ph.D. in Mobile Adhoc
Network at Shivaji University. She has 14 years
of teaching experience in computer science. She
has published 20+ research papers in reputed
international journals and conferences, including
IEEE, also available online. She has also authored
book chapters with Springer. Her research areas
are MANET, VANET, and Blockchain Security.
Indranath Chatterjee is working as a professor
in the Department of Computer Engineering at
Tongmyong University, Busan, South Korea. He
received his Ph.D. in computational neurosci-
ence from the Department of Computer Science,
University of Delhi, India. His research areas
include computational neuroscience, schizo-
phrenia, medical imaging, fMRI, and machine
learning. He has authored and edited eight
books on computer science and neuroscience
published by renowned international publishers.
He has published numerous research papers in
international journals and conferences. He is
a recipient of various global awards in neuroscience. He is currently serving as a
chief section editor of a few renowned international journals, is a member of the edi-
torial board of various international journals, and he is an advisory board member in
various “Open- Science” organizations worldwide. He is presently working on sev-
eral projects for government and non-g overnment organizations as PI/c o- PI, related
to medical imaging and machine learning for a broader societal impact, for which
he is collaborating with several universities globally. He is an active professional
member of the Association of Computing Machinery (ACM, USA), the Organization
of Human Brain Mapping (OHBM, USA), the Federations of European Neuroscience
Society (FENS, Belgium), the Association for Clinical Neurology and Mental Health
(ACNM, India), the Korean Society of Brain and Neural Science (KSBNS, Korea),
and the International Neuroinformatics Coordinating Facility (INCF, Sweden).
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