New Approaches to Data Analytics and Internet of Things Through Digital Twin PDF
Preview New Approaches to Data Analytics and Internet of Things Through Digital Twin
New Approaches to Data Analytics and Internet of Things Through Digital Twin P. Karthikeyan National Chung Cheng University, Chiayi, Taiwan Polinpapilinho F. Katina University of South Carolina Upstate, USA S.P. Anandaraj Presidency University, India A volume in the Advances in Systems Analysis, Software Engineering, and High Performance Computing (ASASEHPC) Book Series Published in the United States of America by IGI Global Engineering Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA, USA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com Copyright © 2023 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Names: Karthikeyan, P., 1981- editor. | Katina, Polinpapilinho F., editor. | Anandaraj, S. P., 1982- editor. Title: New approaches to data analytics and internet of things through digital twin / P. Karthikeyan, Polinpapilinho F Katina, and S.P. Anandaraj, editors. Description: Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2023] | Includes bibliographical references and index. | Summary: “This book investigates that though many data analytics tools have been developed in the past few years, their usage in the field of Digital Twin warrants new approaches considering many aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real time analysis, sampling and dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection”-- Provided by publisher. Identifiers: LCCN 2022018654 (print) | LCCN 2022018655 (ebook) | ISBN 9781668457221 (h/c) | ISBN 9781668457238 (s/c) | ISBN 9781668457245 (ebook) Subjects: LCSH: Internet of things. | Digital twins (Computer simulation) | Data mining. Classification: LCC TK5105.8857 .N49 2023 (print) | LCC TK5105.8857 (ebook) | DDC 004.67/8--dc23/eng/20220701 LC record available at https://lccn.loc.gov/2022018654 LC ebook record available at https://lccn.loc.gov/2022018655 This book is published in the IGI Global book series Advances in Systems Analysis, Software Engineering, and High Performance Computing (ASASEHPC) (ISSN: 2327-3453; eISSN: 2327- 3461) British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher. For electronic access to this publication, please contact: [email protected]. Advances in Systems Analysis, Software Engineering, and High Performance Computing (ASASEHPC) Book Series Vijayan Sugumaran Oakland University, USA ISSN:2327-3453 EISSN:2327-3461 Mission Thetheory and practice of computing applications and distributed systems has emerged as one of the key areas of research driving innovations in business, engineering, and science. The fields of software engineering, systems analysis, and high performance computing offer a wide range of applications and solutions in solving computational problems for any modern organization. The Advances in Systems Analysis, Software Engineering, and High Performance Computing (ASASEHPC) Book Series brings together research in the areas of distributed computing, systems and software engineering, high performance computing, and service science. This collection of publications is useful for academics, researchers, and practitioners seeking the latest practices and knowledge in this field. 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For pricing and ordering information please visit http://www.igi-global. com/book-series/advances-systems-analysis-software-engineering/73689. Postmaster: Send all address changes to above address. Copyright © 2023 IGI Global. All rights, including translation in other languages reserved by the publisher. No part of this series may be reproduced or used in any form or by any means – graphics, electronic, or mechanical, including photocopying, recording, taping, or information and retrieval systems – without written permission from the publisher, except for non commercial, educational use, including classroom teaching purposes. The views expressed in this series are those of the authors, but not necessarily of IGI Global. Titles in this Series For a list of additional titles in this series, please visit: http://www.igi-global.com/book-series/ Futuristic Trends for Sustainable Development and Sustainable Ecosystems Fernando Ortiz-Rodriguez (Tamaulipas Autonomous University, Mexico) Sanju Tiwari (Tamaulipas Autonomous University, Mexico) Sailesh Iyer (Rai University, India) and José Melchor Medina-Quintero (Tamaulipas Autonomous University, Mexico) Engineering Science Reference • © 2022 • 320pp • H/C (ISBN: 9781668442258) • US $270.00 Emerging Technologies for Innovation Management in the Software Industry Varun Gupta (Universidad de Alcalá, Madrid, Spain) and Chetna Gupta (Jaypee Institute of Information Technology, Noida, India) Engineering Science Reference • © 2022 • 282pp • H/C (ISBN: 9781799890591) • US $270.00 Technology Road Mapping for Quantum Computing and Engineering Brojo Kishore Mishra (GIET University, India) Engineering Science Reference • © 2022 • 243pp • H/C (ISBN: 9781799891833) • US $250.00 Designing User Interfaces With a Data Science Approach Abhijit Narayanrao Banubakode (MET Institute of Computer Science, India) Ganesh Dattatray Bhutkar (Vishwakarma Institute of Technology, India) Yohannes Kurniawan (Bina Nusantara University, Indonesia) and Chhaya Santosh Gosavi (MKSSS’s Cummins College of Engineering, India) Engineering Science Reference • © 2022 • 325pp • H/C (ISBN: 9781799891215) • US $270.00 Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms Veljko Milutinović (Indiana University, Bloomington, USA) Nenad Mitić (University of Belgrade, Serbia) Aleksandar Kartelj (University of Belgrade, Serbia) and Miloš Kotlar (University of Belgrade, Serbia) Engineering Science Reference • © 2022 • 296pp • H/C (ISBN: 9781799883500) • US $270.00 701 East Chocolate Avenue, Hershey, PA 17033, USA Tel: 717-533-8845 x100 • Fax: 717-533-8661 E-Mail: [email protected] • www.igi-global.com Table of Contents Preface xiv Acknowledgment ...............................................................................................xix Chapter 1 Data Analytics: An Overview ................................................................................1 Anu Sayal, Jain University (Deemed), India Chapter 2 Data Management for IoT and Digital Twin........................................................28 Galiveeti Poornima, Presidency University, India Vinay Janardhanachari, Cloud Operations, USA Deepak S. Sakkari, Presidency Univeristy, India Chapter 3 Cybertwin-Driven Resource Provisioning for IoE Applications at 6G-Enabled Edge Networks .....................................................................................................46 Hemapriya K. E., Sri Krishna Arts and Science College, India Saraswathi S., Sri Krishna Arts and Science College, India Chapter 4 Edge Computing on IoT: Architectures, Techniques, and Challenges.................67 Mahalakshmi R., Presidency University, India Uzra Ismat, Presidency University, India Praveena K. N., Presidency University, India Chapter 5 Disease Analysis and Prediction Using Digital Twins and Big Data Analytics ..............................................................................................................98 Rajagopal R., Narsimha Reddy Engineering College, India Karthikeyan P., National Chung Cheng University, Taiwan Menaka E., Vivekanandha College of Engineering and Technology for Women, India Karunakaran V., Jain University (Deemed), India Harshavaradhanan Pon, Vellore Institute of Technology, Bhopal, India Chapter 6 Knowledge Discovery Through Intelligent Data Analytics in Healthcare.........115 Kowsalya S., Sri Krishna Arts and Science College, India Saraswathi S., Sri Krishna Arts and Science College, India Chapter 7 A Novel Dual Image-Based Reversible Hiding Technique Using LSB Matching- Digital World .....................................................................................................135 Kalyanapu Srinivas, Kakatiya Institute of Technology and Science, India K. Mounika, Kakatiya Institute of Technology and Science, IndiaVyshnavi Kandukuri, Kakatiya Institute of Technology and Science, IndiaHarshini B., Kakatiya Institute of Technology and Science, India B. Sai Sreeja, Kakatiya Institute of Technology and Science, IndiaAbhinay K., Kakatiya Institute of Technology and Science, India Chapter 8 Using Deep Learning and Big Data Analytics for Managing Cyber-Attacks ..146Sarabjeet Kaur Kochhar, Indraprastha College for Women, University of Delhi, Delhi, India Anishka Bhatia, Indraprastha College for Women, University of Delhi, Delhi, India Nandini Tomer, Indraprastha College for Women, University of Delhi, Delhi, India Chapter 9 Data Analysis of Cognitive, Behavioral, and Emotional Features Having Impact on Student Careers .............................................................................................179 Gouthami Velakanti, Kakatiya Institute of Technology and Science, India Anjali Mathur, KL University (Deemed), India Kalyanapu Srinivas, Kakatiya Institute of Technology and Science, India Chapter 10 Big Data Analytics in Industrial IoT and Cybertwin .........................................191 Rajendran T., Rajalakshmi Institute of Technology, India Surya S., Saveetha Engineering College, India Mohamed Imtiaz N., HKBK College of Engineering, India Babu N., Siddharth Institute of Engineering and Technology, India Chapter 11 The APT Cyber Warriors With TTP Weapons to Battle: An Review on IoT and Cyber Twin..................................................................................................211 DianaArulkumar,KalasalingamAcademyofResearchandEducation,India Kartheeban K., Kalasalingam Academy of Research and Education, India Arulkumaran G., Bule Hora University, Ethiopia Compilation of References ..............................................................................226 Related Readings 246 About the Contributors ...................................................................................301 Index 306 Detailed Table of Contents Preface xiv Acknowledgment ...............................................................................................xix Chapter 1 Data Analytics: An Overview ................................................................................1 Anu Sayal, Jain University (Deemed), India This chapter provides a comprehensive and unified view of data analytics. Data analytics is the process of analyzing the raw data in order to draw inferences about the information in hand. Data analysis techniques are primarily used to get an insight which further facilitates enhancement of the sector under consideration. These techniques are beneficial for optimizing a process under consideration and also for increasing the overall efficiency of a system. These techniques also act as performance boosters as their implementation in the business models help in reduction of costs by considerable amount. It is the most important for any organization as it facilitates better decision-making approaches and also provides an analysis of customer trends as well as satisfaction which further leads to improved products as well as services. It also helps in effective marketing of the products and services. Data analytics has widespread application in various sectors. Various tools are used for carrying out data analytics jobs. All this is discussed in the chapter. Chapter 2 Data Management for IoT and Digital Twin........................................................28 Galiveeti Poornima, Presidency University, India Vinay Janardhanachari, Cloud Operations, USA Deepak S. Sakkari, Presidency Univeristy, India The internet of things (IoT) is a dynamic and global network infrastructure in which “things”—subsystems and individual physical and virtual entities—can be identified, autonomous, and self-configurable. “Things” are expected to communicate with one another and with the environment by exchanging data generated by sensing, as well as react to events and trigger actions to control the physical world. A digital twin is a synchronised virtual representation of real-world entities and processes. Understanding the data management challenges for DT is critical to understanding the data issues. Data management is a common issue in existing systems, ranging from product design to asset management and maintenance. Chapter 3 Cybertwin-Driven Resource Provisioning for IoE Applications at 6G-Enabled Edge Networks .....................................................................................................46 Hemapriya K. E., Sri Krishna Arts and Science College, India Saraswathi S., Sri Krishna Arts and Science College, India 6G is the latest in wireless communications network technologies supportive for cellular data networks. 6G networks use complex frequencies unlike 5G networks and will empower higher data rates to be achieved and for the 6G network to have a superior global volume. Lower latency levels will almost definitely be a requirement. 6G radio networks will deliver the communication and data congregation essential to accrue data. However, a systems method is mandatory for the 6G technology. It will include data analytics, AI, and next-generation computation abilities using HPC and significant computation. Chapter 4 Edge Computing on IoT: Architectures, Techniques, and Challenges.................67 Mahalakshmi R., Presidency University, India Uzra Ismat, Presidency University, India Praveena K. N., Presidency University, India The internet of things (IoT) is escalating into diverse aspects of our lives with innovative technologies and solutions. In general, IoT devices are restricted to storage and processing power, which results in the lack of performance, reliability, and privacy of IoT applications. The applications in various sectors like agriculture, healthcare, smart cities, smart homes, and production units are enriched by twining the IoT and cloud computing. Cloud analytics is the process of extracting actionable business insights from the data stored in the cloud. Cloud analytics algorithms are applied to large data collections to identify patterns, predict future outcomes, and produce other useful information to business decision makers. Edge computing has arisen to support this intense increase in resource requirements by leveraging the untouched potential away from the enterprise data cores. Processing power is gained by a collective process between various entities at the network edge including the user devices, mobile-based stations, and gateways and access points. Chapter 5 Disease Analysis and Prediction Using Digital Twins and Big Data Analytics ..............................................................................................................98 Rajagopal R., Narsimha Reddy Engineering College, India Karthikeyan P., National Chung Cheng University, Taiwan Menaka E., Vivekanandha College of Engineering and Technology for Women, India Karunakaran V., Jain University (Deemed), India Harshavaradhanan Pon, Vellore Institute of Technology, Bhopal, India The data generated by the big data-based clinical need analysis plays a key role in improving the consideration feature, decreasing waste and blunder, and reducing treatment expenses. The use of big data analytics (BDA) techniques for analyzing disease and predictions is discussed in this investigation. This precise survey of writing means to decide the extent of BDA in disease analysis and difficulties in treatment in the medical filed. Further, this study has discussed the comparative analysis of heart diseases, predictions using BDA techniques, predicting of breast cancer, lung cancer, and brain diseases. Digital twins will be key to delivering highly personalized treatments and interventions. Intelligent digital twins, combining data, knowledge, and algorithms (AI), are set to revolutionise medicine and public health. Chapter 6 Knowledge Discovery Through Intelligent Data Analytics in Healthcare.........115 Kowsalya S., Sri Krishna Arts and Science College, India Saraswathi S., Sri Krishna Arts and Science College, India The chapter aims to embed the demanding computing concepts to attain intelligent data analytics in the domain of healthcare. The targeted outcome provides the pathway to design the brainy decision support system needed to have efficient prediction with trained input patterns. The usage of IoT devices is increasing tremendously to overcome the challenges existing in handling the data related to human-relevant happenings. The volume, velocity, and variety of data are emerging newly and dominating the decision support characteristics. This scenario happens almost in all the computing fields, but more attention is expected to implement in the healthcare sector due to the existence of sensitive data. The traditional data analytics methods are deviating in the performance due to the unpredictable dynamic challenges emerging in the day-to-day operation. The efficient features of demanding computing strategies are motivated to embed together to discover crucial knowledge through intelligent data analytics.
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