Table Of ContentAdvanced Computational
Techniques for Sustainable
Computing
Advanced Computational Techniques for Sustainable Computing is considered a multidis-
ciplinary feld encompassing advanced computational techniques across several domains,
including Computer Science, Statistical Computation, and Electronics Engineering. The
core idea of sustainable computing is to deploy algorithms, models, policies, and protocols
to improve energy effciency and management of resources, enhancing ecological balance,
biological sustenance, and other services on societal contexts.
FEATURES
• Offers comprehensive coverage of the most essential topics
• Provides insight on building smart sustainable solutions
• Includes details of applying mining, learning, Internet of Things, and sensor-
based techniques for sustainable computing
• Details data extraction from various sources followed with preprocessing of data
and how to make effective use of extracted data for application-based research
• Involves practical usage of data analytic language, including R, Python, etc., for
improving sustainable services offered by multidisciplinary domains
• Encompasses comparison and analysis of recent technologies and trends
• Includes development of smart models for information gain and effective deci-
sion-making with visualization
Readers will become acquainted with the utilization of massive datasets for intelligent
mining and processing. This book includes the integration of data-mining techniques for
effective decision-making in the social, economic, and global environmental domains to
achieve sustainability. The implementation of computational frameworks can be accom-
plished using open-source software for the building of resource-effcient models. The con-
tent of this book demonstrates the usage of data science and the Internet of Things for the
advent of smart and realistic solutions for attaining sustainability.
Advanced Computational
Techniques for Sustainable
Computing
Edited by
Megha Rathi
Adwitiya Sinha
First Edition published 2023
by CRC Press
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Library of Congress Cataloging-in-Publication Data
Names: Rathi, Megha, editor. | Sinha, Adwitiya, editor.
Title: Advanced computational techniques for sustainable computing /
edited by Megha Rathi, Adwitiya Sinha.
Description: First edition. | Boca Raton : Chapman & Hall/CRC Press, [2022] |
Includes bibliographical references and index. |
Identifers: LCCN 2021027887 (print) | LCCN 2021027888 (ebook) |
ISBN 9780367495220 (hbk) | ISBN 9780367495282 (pbk) | ISBN 9781003046431 (ebk)
Subjects: LCSH: Sustainable engineering–Data processing. |
Sustainable development–Data processing. | Industries–Data processing.
Classifcation: LCC TA170 .A35 2022 (print) | LCC TA170 (ebook) | DDC 628–dc23
LC record available at https://lccn.loc.gov/2021027887
LC ebook record available at https://lccn.loc.gov/2021027888
ISBN: 978-0-367-49522-0 (hbk)
ISBN: 978-0-367-49528-2 (pbk)
ISBN: 978-1-003-04643-1 (ebk)
DOI: 10.1201/9781003046431
Typeset in Palatino
by codeMantra
Contents
Preface ............................................................................................................................................ vii
Editors ..............................................................................................................................................ix
Contributors ....................................................................................................................................xi
1 Sustainable Computing—An Overview ............................................................................1
Paras Chaudhary, Adwitiya Sinha, and Somya Jain
2 Ambient Air Quality Analysis and Prediction Using Air Quality Index and
Machine Learning Models—The Case Study of Delhi ................................................ 21
Megha Rathi, Muskan Garg, Japsehaj Singh Wahi, and Mayank Deepak Thar
3 Assessing Land Cover and Drought Prediction for Sustainable Agriculture .........33
Anirban Dutta, Anushka Mittal, Shishir Khandelwal, and Adwitiya Sinha
4 Electronic Health Record for Sustainable eHealth ........................................................53
Prapti Miglani, Jagriti Bhandari, Ujjwal Alreja, and Adwitiya Sinha
5 Team Member Selection in Global Software Development—A Blockchain-
Oriented Approach ............................................................................................................... 69
Chetna Gupta and Megha Rathi
6 Machine Learning in Sustainable Healthcare ................................................................79
Dipanwita Thakur and Suparna Biswas
7 Multimedia Audio Signal Analysis for Sustainable Education .................................93
Megha Rathi, Aditya Lahiri, Ayushi Aggarwal, Parul Jindal, and Adwitiya Sinha
8 Smart Health Analytics for Sustainable Energy Monitoring Using IoT
Data Analytics ..................................................................................................................... 107
Sherry Garg and Rajalakshmi Krishnamurthi
9 Customer Analytics for Purchasing Behavior Prediction ..........................................123
Mitushi Agarwal, Priyanka Parashar, Aradhya Mathur, and Adwitiya Sinha
10 Discernment of Malaria-Infected Cells in the Blood Streak Images Using
Advanced Learning Techniques ...................................................................................... 139
Megha Rathi, Chandna Gupta, Rachit Shukla, and Raja Raubins
11 Handwritten Text Recognition with IoT Devices ........................................................ 153
Omkareshwar Tripathi, Mayank Tiwari, and Anish Gupta
12 Circadian Rhythm and Lifestyle Diseases .................................................................... 167
Sakshi Singh and Priyadarshini
v
vi Contents
13 Deep Learning for Automated Disease Detection ...................................................... 183
Neeraj Yadav, Somya Tripathi, Ekam Singh Chahal, and Suruchi Sabherwal
14 Time Series Analysis and Trend Exploration of Stock Market ................................ 197
Ratik Puri, Jagriti Bhandari, Ritik Gupta, and Adwitiya Sinha
15 Medical Search Engine ...................................................................................................... 213
Palak Arora, Shresth Singh, and Megha Rathi
16 Assessing Impact of Global Terrorism Using Time Series Analysis .......................225
Satyam Saini, Vidushi Tripathi, Kartik Tyagi, and Adwitiya Sinha
17 Sustainable Statistics for Death Cognizance Analysis............................................... 245
Megha Rathi, Dhananjay Jindal, Manan Thakral, Rishabh, and Palak Arora
18 Modeling the Immune Response of B-C ell Receptor Using Petri Net for
Tuberculosis .........................................................................................................................259
Gajendra Pratap Singh and Madhuri Jha
19 Crop Prediction and the Sustainability of Farming ....................................................273
Megha Rathi, Palak Arora, Tanya Srivastava, Nitya Arora, Jigyasa Agarwal,
and Abhinna Arjun
20 Personalized Heart Disease Framework for Health Sustainability .........................285
Megha Rathi, Amogh Sanjeev Gupta, Ayush Raj, Rizul Singh, and Vishrut Sacheti
21 Sports Analytics for Classifying Player Actions in Basketball Games .................. 301
Ayush Gupta, Ekam Singh Chahal, Ankur Haritosh, Adwitiya Sinha,
and Satish Chandra
Index ............................................................................................................................................. 317
Preface
Sustainable computing is considered a multidisciplinary feld with primary emphasis
on applications of advanced computational techniques from cross disciplines, including
Information Technology, Statistics, Electronics, and Computer Science, to improve and
manage sustainable evolution. This encompasses the development of intelligent mod-
els, frameworks, and applications for effective decision-making dealing with the overall
administration and management of the resources for providing solutions to critical and
real-world problems. The core idea of sustainable computing is to explore the variety of
aspects that may have societal, economic, or ecological impacts. It includes a large spec-
trum of applications that require addressing several open challenges associated with
real-world problem domains by applying a computational paradigm, which involves new
architectures and technological approaches. Sustainability allows framing policies and
developing strategies to reduce overall power consumption, recycle waste products, mini-
mize resource and energy requirements, enhance the quality of ecological, manage sports,
and improve biological and social services. It also aims at reducing wastage of natural
reserves, thereby improving the effcacy of utilization, monitoring, management, and criti-
cal surveillance of primary resources.
Developing sustainable ecofriendly solutions for real-world problems requires a wide
range of disciplines, such as statistics, optimization, decision support systems, data sci-
ence, artifcial intelligence, machine learning, and big social mining. It helps in build-
ing novel algorithms, models, computational frameworks, and techniques for real-time
as well as high-performance computing. Sustainable computing is a holistic approach
that extends from modeling power-aware systems to societal development and combat-
ing terrorism, and from effcient usage of solar power to performing sustainable resource
management. The notion of sustainable computing estimates the impact and beneft of
leading-edge technology and state-of-the-art techniques.
Our book is about the development and application of smart computational techniques
for offering smart solutions to achieve sustainability. The readers would get acquainted
with the utilization of massive datasets for intelligent mining and processing. It includes
the integration of data-mining techniques for effective decision-making in the social, eco-
nomic, and global environmental domains to achieve sustainability. The implementation
of computational frameworks can be accomplished using open-source software for the
building of resource-effcient models. The content of the book demonstrates the usage of
data science and the Internet of Things for the advent of smart and realistic solutions for
attaining sustainability.
vii
Editors
Dr. Megha Rathi has obtained her Ph.D. in Computer Science from Banasthali University
and is presently working as an Assistant Professor (Senior Grade) in the Department of
Computer Science, Jaypee Institute of Information Technology (JIIT), Noida, Sector 62,
Uttar Pradesh, India. She has 10 years of teaching experience and has worked on a research
project at the National Informatics Centre (NIC), Delhi. She has experience in software
development and worked as a Project Associate at the Indian Institute of Technology (IIT),
Delhi. She has organized several special sessions at international conferences and also
delivered invited talk. Her research areas include sustainable computing, data mining,
data science, health analytics, and machine learning.
Dr. Adwitiya Sinha has received her Ph.D. in Computer Science from School of Computer
& Systems Sciences, Jawaharlal Nehru University (JNU), New Delhi, India in 2015. She
has obtained Masters of Technology in Computer Science and Technology in 2010 from
JNU. She was awarded with First Rank certifcate in M.Tech. batch 2008. She received
Senior Research Fellowship (SRF) from the Council of Scientifc & Industrial Research
(CSIR), New Delhi and also awarded research scholarship from the University Grants
Commission (UGC) for her research in wireless sensor networks. She has published more
than 80 papers in international journals, international conferences, book chapters, and
books. She has delivered several invited talks in lecture series on Networks & Graphs,
Wireless Sensor Networks, and Performance Analysis of Computing Systems, organized
by the Consortium for Educational Communication (CEC), UGC, New Delhi in the form
of EDUSAT live lectures. Presently, she is working as an Associate Professor in Jaypee
Institute of Information Technology, Uttar Pradesh, India. She is a Senior Member of IEEE.
Her research area includes complex network analysis, online social media, data science,
large-scale graphs, and performance analysis of wireless sensor and actuator networks.
ix
