Deep Learning Technologies for the Sustainable Development Goals: Issues and Solutions in the Post-COVID Era

254 Pages·2023·6.772 MB·English

by  Virender Kadyan, T. P. Singh, Chidiebere Ugwu

Advanced Technologies and Societal Change
Virender Kadyan
T. P. Singh
Chidiebere Ugwu   Editors
Deep Learning
Technologies
for the Sustainable
Development Goals
Issues and Solutions in the Post-COVID
Era
Advanced Technologies and Societal Change
Series Editors
Amit Kumar, Bioaxis DNA Research Centre (P) Ltd, Hyderabad, Telangana, India
Ponnuthurai Nagaratnam Suganthan, School of EEE, Nanyang Technological
University, Singapore, Singapore
Jan Haase, NORDAKADEMIE Hochschule der Wirtschaft, Elmshorn, Germany
Editorial Board
Sabrina Senatore, Department of Computer and Electrical Engineering and Applied
Mathematics, University of Salerno, Fisciano, Italy
Xiao-Zhi Gao , School of Computing, University of Eastern Finland, Kuopio,
Finland
Stefan Mozar, Glenwood, NSW, Australia
Pradeep Kumar Srivastava, Central Drug Research Institute, Lucknow, India
This series covers monographs, both authored and edited, conference proceed-
ings and novel engineering literature related to technology enabled solutions in the
area of Humanitarian and Philanthropic empowerment. The series includes sustain-
able humanitarian research outcomes, engineering innovations, material related to
sustainable and lasting impact on health related challenges, technology enabled solu-
tions to fight disasters, improve quality of life and underserved community solutions
broadly. Impactful solutions fit to be scaled, research socially fit to be adopted and
focused communities with rehabilitation related technological outcomes get a place
in this series. The series also publishes proceedings from reputed engineering and
technology conferences related to solar, water, electricity, green energy, social tech-
nological implications and agricultural solutions apart from humanitarian technology
and human centric community based solutions.
Major areas of submission/contribution into this series include, but not limited
to: Humanitarian solutions enabled by green technologies, medical technology,
photonics technology, artificial intelligence and machine learning approaches, IOT
based solutions, smart manufacturing solutions, smart industrial electronics, smart
hospitals, robotics enabled engineering solutions, spectroscopy based solutions and
sensor technology, smart villages, smart agriculture, any other technology fulfilling
Humanitarian cause and low cost solutions to improve quality of life.
· ·
Virender Kadyan T. P. Singh Chidiebere Ugwu
Editors
Deep Learning Technologies
for the Sustainable
Development Goals
Issues and Solutions in the Post-COVID Era
Editors
Virender Kadyan T. P. Singh
University of Petroleum and Energy Studies University of Petroleum and Energy Studies
Dehradun, Uttarakhand, India Dehradun, Uttarakhand, India
Chidiebere Ugwu
University of Port Harcourt
Port Harcourt, Rivers State, Nigeria
ISSN 2191-6853 ISSN 2191-6861 (electronic)
Advanced Technologies and Societal Change
ISBN 978-981-19-5722-2 ISBN 978-981-19-5723-9 (eBook)
https://doi.org/10.1007/978-981-19-5723-9
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature
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Preface
The emergence of artificial intelligence (AI) is shaping an ever-increasing range of
sectors. For e.g., AI is believed to affect global productivity1, equality and inclusion2,
environmental outcomes3, and several other areas, both in the short and long term4.
Reported potential impacts of AI indicate both positive5 and negative6 impacts on
Sustainable Development. Deep learning spanning from artificial intelligence (AI)
is one of the technologies which has tremendous potential to revolutionize daily
processes in various fields, leading humanity to an era of self-sufficiency and produc-
tivity. There is dire need to inspect AI applications that impacts UN Sustainable
Development Goals, both positively and negatively. The goal is to promote the posi-
tive use of AI for Sustainable Development and to investigate on the negative impact
of AI on Sustainable Development. It is time to discuss implications of how AI can
either enable or inhibit the delivery of all 17 goals and 169 targets recognized in
the 2030 Agenda for Sustainable Development. The focus of this book is to provide
insights, how the deep learning techniques will impact the implementation of SDGs,
what are their promises, limits, and the new challenges. This will also provide a
publication avenue for researchers working on the impact deep learning approaches
in implementing Sustainable Development Goals of UN. This book also covers the
challenges, blockages, and opportunities in various applications of deep learning in
SDGs. The main goal of this book is to present the comprehensive survey on the
major applications and research-oriented articles based on deep learning techniques
those are focused on Sustainable Development Goals. In particular, there is the need
to extend research into deep learning and its broader application to many sectors
and to assess its impact on achieving the Sustainable Development Goals (SDGs).
The chapters in this book will help in finding the use of deep learning across all
sections of SDGs. The rapid development of deep learning needs to be supported
by the organizational insight and oversight necessary for AI-based technologies in
general; here, we shall present and discuss implications of how deep learning enables
the delivery agenda for Sustainable Development.
The book contains the collection of 16 chapters of research findings, reviews, and
case studies by various experts in this volume. The book begins with an introduc-
tion of “How Deep Learning Can Help in Regulating the Subscription Economy to
v
vi Preface
Ensure Sustainable Consumption and Production Patterns (12th Goal of SDGs).”
Each other in this book tried to bring his/her insight of SDG goals with different
real-life applications.
Dehradun, India Virender Kadyan
Dehradun, India T. P. Singh
Port Harcourt, Nigeria Chidiebere Ugwu
Acknowledgements
This SDG book would not be possible without support of my Springer’s editorial
team. The continues encouragement of them will help in completion of this book.
Every book has a hard support of its editors and writers, so I would like to thank
Chandrasekaran Arjunan and Loyola Dsilva from Springer team.
I remain grateful to the key supporter of this book my co-editors whose continuous
help in timely completion of this assignment. Consequently, the success of this is
not possible without the support of each and every reviewers who provided valuable
input to each chapter writers. Dr. Amitoj Singh and Dr. Anupam Singh deservers
special acknowledgment who has inserted his valuable thought in shaping of this
book. Finally, I would like to thank each one of the chapter contributors without
whom this book is not possible. So I am heartfully thank to each one of them for
their hardwork and determinations.
vii
Contents
1 How Deep Learning Can Help in Regulating the Subscription
Economy to Ensure Sustainable Consumption and Production
Patterns (12th Goal of SDGs) ................................... 1
Yogesh Sharma, Rajeev Sijariya, and Priya Gupta
2 Deep Technologies Using Big Data in: Energy and Waste
Management .................................................. 21
Jyotsna Verma
3 QoS Aware Service Provisioning and Resource Distribution
in 4G/5G Heterogeneous Networks .............................. 41
Rintu Nath
4 Leveraging Fog Computing for Healthcare ...................... 51
Avita Katal
5 Intelligent Self-tuning Control Design for Wastewater
Treatment Plant Based on PID and Model Predictive Methods ..... 69
Ujjwal, Neelam Verma, and Anjali Jain
6 Impact of Deep Learning Models for Technology Sustainability
in Tourism Using Big Data Analytics ............................ 83
Ashish Kumar and Rubeena Vohra
7 Study of UAV Management Using Cloud-Based Systems .......... 97
Sonali Vyas, Sourabh Singh Verma, and Ajay Prasad
8 Contemporary Role of Blockchain in Industry 4.0 ................ 111
Shaurya Gupta, Sonali Vyas, and Vinod Kumar Shukla
9 SDGs Laid Down by UN 2030 Document ........................ 123
Vishakha Goyal and Mridul Dharwal
ix
x Contents
10 Healthcare 4P: Systematic Review of Applications
of Decentralized Trust Using Blockchain Technology ............. 133
Deepika Sachdev, Shailendra Kumar Pokhriyal, Sylesh Nechully,
and Sai Shrinvas Sundaram
11 Implementation of an IoT-Based Water and Disaster
Management System Using Hybrid Classification Approach ....... 157
Abhishek Badholia, Anurag Sharma, Gurpreet Singh Chhabra,
and Vijayant Verma
12 ANN: Concept and Application in Brain Tumor Segmentation ..... 175
Amit Verma
13 Automation of Brain Tumor Segmentation Using Deep
Learning ..................................................... 189
Amit Verma
14 Transportation Management Using IoT ......................... 203
Amit Singh
15 Enhancing Shoppers’ Loyalty by Prioritizing Customer-
Centricity Drivers in the Retail Industry ........................ 227
Vishal Srivastava, Manoj Kumar Srivastava, and R. K. Singhal