![Published in the United States of America by
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All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the
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For electronic access to this publication, please contact: eresources@igi-global.com.
Names: Zhao, Jingyuan, 1968- editor. | Kumar, V. Vinoth, 1988- editor.
Title: Handbook of research on innovations and Applications of AI, IoT, and
Cognitive Technologies / Jingyuan Zhao, and V. Vinoth Kumar, editors.
Description: Hershey, PA : Engineering Science Reference, an imprint of IGI
Global, [2021] | Includes bibliographical references and index. |
Summary: “This book provides perspectives of academics and industrial
practitioners offering the latest innovations and applications of
artificial intelligence (AI), Internet-of-Things (IoT) and cognitive
based smart systems to provide information for all those interested in
AI, IoT and Cognitive Technologies in emerging and developed economies
in terms of their respective development situation toward public
policies, technologies and intellectual capital, innovation systems,
competition and strategies, marketing and growth capability, governance
and relegation model etc”-- Provided by publisher.
Identifiers: LCCN 2020046720 (print) | LCCN 2020046721 (ebook) | ISBN
9781799868705 (hardcover) | ISBN 9781799868729 (ebook)
Subjects: LCSH: Internet of things--Industrial applications. | Artificial
intelligence--Industrial applications.
Classification: LCC TK5105.8857 .I493 2021 (print) | LCC TK5105.8857
(ebook) | DDC 004.67/8--dc23
LC record available at https://lccn.loc.gov/2020046720
LC ebook record available at https://lccn.loc.gov/2020046721
This book is published in the IGI Global book series Advances in Computational Intelligence and Robotics (ACIR) (ISSN:
2327-0411; eISSN: 2327-042X)](https://image.slidesharecdn.com/24378361-250510142118-8dee5f5a/85/Innovations-And-Applications-Of-Ai-Iot-And-Cognitive-Technologies-Jingyuan-Zhao-7-320.jpg)
![
Detailed Table of Contents
Preface.
................................................................................................................................................ xxx
Section 1
AI and IoT: A Blend in Future Technologies and Systems
Section 1 introduces emerging AI and IoT technologies and systems, as well as their innovations and
applications that are responsible for the digitization of all the sectors through automation and together
rules the technological aspects of our lives. Section 1 is organized into 18 chapters.
Chapter 1
Algorithms Optimization for Intelligent IoV Applications..................................................................... 1
Elmustafa Sayed Ali Ahmed, Sudan University of Science and Technology, Sudan Red Sea
University, Sudan
Zahraa Tagelsir Mohammed, Red Sea University, Sudan
Mona Bakri Hassan, Sudan University of Science and Technology, Sudan
Rashid A. Saeed, Sudan University of Science and Technology, Sudan Taif University,
Saudi Arabia
Internet of vehicles (IoV) has recently become an emerging promising field of research due to the
increasing number of vehicles each day. It is a part of the internet of things (IoT) which deals with vehicle
communications. As vehicular nodes are considered always in motion, they cause frequent changes in the
network topology. These changes cause issues in IoV such as scalability, dynamic topology changes, and
shortest path for routing. In this chapter, the authors will discuss different optimization algorithms (i.e.,
clusteringalgorithms,antcolonyoptimization,bestinterfaceselection[BIS]algorithm,mobilityadaptive
density connected clustering algorithm, meta-heuristics algorithms, and quality of service [QoS]-based
optimization). These algorithms provide an important intelligent role to optimize the operation of IoV
networks and promise to develop new intelligent IoV applications.
Chapter 2
Cooperative Relaying Communication in IoT Applications for 5G Radio Networks.
........................... 26
Rajeev Kumar, Central University of Karnataka, India
Ashraf Hossain, National Institute of Technology, Silchar, India
ThischapterpresentscooperativerelayingnetworksthatarehelpfulinInternetofThing(IoT)applications
for fifth-generation (5G) radio networks. It provides reliable connectivity as the wireless device is out of
range from cellular network, high throughput gains and enhance the lifetime of wireless networks. These
features can be achieved by designing the advanced protocols. The design of advanced protocols plays](https://image.slidesharecdn.com/24378361-250510142118-8dee5f5a/85/Innovations-And-Applications-Of-Ai-Iot-And-Cognitive-Technologies-Jingyuan-Zhao-20-320.jpg)
![Preface
ORGANIZATION OF THE BOOK
This book has been divided into two sections:
Section 1, “AI and IoT: A Blend in Future Technologies and Systems,” introduces emerging AI and
IoT technologies and systems, as well as their innovations and applications that are responsible for the
digitization of all the sectors through automation and together rules the technological aspects of our
lives. Section 1 is organized into 18 chapters. A synopsis of each chapter is given below.
Chapter1(AlgorithmsOptimizationforIntelligentIoVApplications)introducesdifferentoptimization
algorithms i.e. clustering algorithms, Ant colony optimization, Best Interface Selection (BIS) Algorithm,
Mobility adaptive density connected clustering algorithm, Meta-Heuristics Algorithms and Quality of
Service (QoS) based optimization. These algorithms provide an important intelligent role to optimize
the operation of IoV networks and promise to develop new intelligent IoV applications.
Chapter2(CooperativeRelayingCommunicationinIoTApplicationsfor5GRadioNetworks)presents
cooperative relaying networks that are helpful in Internet of Thing (IoT) applications for fifth generation
(5G) radio networks. The design of advanced protocols plays an important role to combat the effect of
channel fading, data packet scheduling at the buffered relay, average delay, and traffic intensity.
Chapter 3 (The Rise of IoT and Big Data Analytics for Disaster Management System) explains the
reason why IoT and Big Data are needed to cope with disasters, as well as how these technologies work
to solve the problem. The developments in Big Data and the Internet of Things (IoT) have made a greater
contribution to accuracy and timely decision-making in the Disaster Management System (DMS).
Chapter 4 (IoT-Based Smart Agriculture) explores the current state of advanced farm management
systems by revisiting each critical phase, from data collection in crop fields to variable rate applications,
in order for growers to make informed decisions save money while also protecting the environment and
transforming how food is grown to meet potential population growth.
Chapter 5 (Mobile Geo-Fencing Triggers for Alerting Entries Into COVID-19 Containment Zones
Using IoT) discusses a Containment Zone alert system by means of Geo-fencing technology to identify
the movement of public, deliver info about the danger to the public in travel and also send an alert to
the police when there is an entry or exit detected in the containment zone by the use of Location-Based
Services (LBS).
Chapter 6 (Fine Tuning Smart Manufacturing Enterprise System: A Perspective of Internet of Things-
Based Service-Oriented Architecture) proposes the integration of standard workflow model between
business system level and manufacturing production level with IoT-enabled SOA framework.
Chapter 7 (A Quantum Technology-Based LiFi Security Using Quantum Key Distribution) discusses
Wireless Fidelity (Wi-Fi) and focuses on some drawbacks that include speed and bandwidth limit,
security issues, and attacks by malicious users, which yield Wi-Fi as less reliable as compared to LiFi.
Chapter 8 (Role of Artificial Intelligence of Things [AIoT] to Combat Pandemic COVID-19) studies
on AIoT entails AI through machine learning and decision making to IoT; and renovates IoT to add data
exchange and analytics to AI. Through this chapter, AIoT will serve as potential analytical tool to fight
against the pandemic.
Chapter 9 (Recent Trends in Wearable Device Technology for Health State Monitoring) proposes that
the main function of wearable devices is said to be collecting the user personal health data. Eg: such
devices include measurement on fitness of body, heart beat measurement, ECG Measurement, blood
pressure monitoring etc.
xxxi](https://image.slidesharecdn.com/24378361-250510142118-8dee5f5a/85/Innovations-And-Applications-Of-Ai-Iot-And-Cognitive-Technologies-Jingyuan-Zhao-36-320.jpg)
![1
Copyright © 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Chapter 1
DOI: 10.4018/978-1-7998-6870-5.ch001
ABSTRACT
Internet of vehicles (IoV) has recently become an emerging promising field of research due to the in-
creasing number of vehicles each day. It is a part of the internet of things (IoT) which deals with vehicle
communications. As vehicular nodes are considered always in motion, they cause frequent changes in
the network topology. These changes cause issues in IoV such as scalability, dynamic topology changes,
and shortest path for routing. In this chapter, the authors will discuss different optimization algorithms
(i.e., clustering algorithms, ant colony optimization, best interface selection [BIS] algorithm, mobility
adaptive density connected clustering algorithm, meta-heuristics algorithms, and quality of service
[QoS]-based optimization). These algorithms provide an important intelligent role to optimize the op-
eration of IoV networks and promise to develop new intelligent IoV applications.
Algorithms Optimization for
Intelligent IoV Applications
Elmustafa Sayed Ali Ahmed
https://orcid.org/0000-0003-4738-3216
Sudan University of Science and Technology, Sudan Red Sea University, Sudan
Zahraa Tagelsir Mohammed
Red Sea University, Sudan
Mona Bakri Hassan
Sudan University of Science and Technology, Sudan
Rashid A. Saeed
https://orcid.org/0000-0002-9872-081X
Sudan University of Science and Technology, Sudan Taif University, Saudi Arabia](https://image.slidesharecdn.com/24378361-250510142118-8dee5f5a/85/Innovations-And-Applications-Of-Ai-Iot-And-Cognitive-Technologies-Jingyuan-Zhao-41-320.jpg)
![14
Algorithms Optimization for Intelligent IoV Applications
p t
S t f t
S t f t
j
ij
k
ij y
Allowed kto i ij y
( )=
( ) ( )
( ) ( )
∉
∑
[ ] [ ]
[ ] [ ]
,
,
β
β
A
A
Otherwise
i
k
0,
. (5)
Where, p t
ij
k
( ) representstheprobabilitythatbeektravelsfromnodeitojiniterationt. A Tabu
i
k
k
= −
Φ
denotes the available nodes for bee k, i.e., the points that satisfy all constraints but have not been previ-
ously visited by the bee). Tabu k is the tabu list of bee k, which prevents the nodes already visited by
bee k from being repeatedly visited. In some applications (i.e., router optimization), it is also convenient
that the bee can return through the original path. sij(t) and fij(t) represent the bee colony and heuristic
information, respectively, while α and β are the weight coefficients (Ajay et al,2019).
Figure 6. The Bee Colony algorithm](https://image.slidesharecdn.com/24378361-250510142118-8dee5f5a/85/Innovations-And-Applications-Of-Ai-Iot-And-Cognitive-Technologies-Jingyuan-Zhao-54-320.jpg)
![Humboldt tells us that when the Indians wish to catch these Eels they
drive some wild horses through the pools which the fish inhabit; and that
when the Eels have exhausted their electrical power upon the horses, the
Indians take them without difficulty. He relates an instance in which he says
that the horses, stunned with the shocks they received, sank under water, but
most of them rose again, and gained the shore, where they lay stretched out
on the ground, apparently quite exhausted and without the power of
moving, so much were they stupefied and benumbed. In about a quarter of
an hour, however, the Eels appeared to have exhausted themselves, and,
instead of attacking fresh horses that were driven into the pond, fled before
them. The Indians then entered the water and caught as many fish as they
liked.[B]](https://image.slidesharecdn.com/24378361-250510142118-8dee5f5a/85/Innovations-And-Applications-Of-Ai-Iot-And-Cognitive-Technologies-Jingyuan-Zhao-58-320.jpg)
![[B] See a very animated account of the capture of this fish, in Humboldt’s “Views
of Nature,” page 16 (Bohn’s Edition).
This most singular fish is peculiar to South America, where it is found
only in stagnant pools, at a great distance from the sea.
THE EEL. (Anguilla vulgaris.)
The Eel resembles a serpent in its form, though no two animals can be
more different in every other respect. Eels are fresh-water fish; but as they
are very susceptible of cold, those which inhabit rivers go down every
autumn towards the sea, which is always warmer than a river, and return in
spring. They are said also to spawn in the sea, and great numbers of young
Eels are seen in spring ascending tidal rivers. Mr. Edward Jesse, in his
edition of “Walton’s Angler,” says: “A column of them has been traced in
the Thames from Somerset House to Oxford, about the middle of May, and
I have watched their progress with much interest. No impediment stops
them. They keep as much as possible close alongshore, and as they pass
watercourses, open ditches, and brooks, c., some of them leave the
column and enter these places, along which they eventually make their way
to ponds, smaller rivers, c. So strong is the migratory instinct in these
little eels, that when I have taken some in a bucket and returned them to the
river at some distance from the column, they have immediately rejoined it
without any deviation to the right or left. On the banks of the Thames the
passage is called Eel-fare. Two observers, watching their progress at
Kingston, calculated that from sixteen to eighteen hundred passed a given
line per minute. Rennie saw (on the 13th of May) a column of young eels of](https://image.slidesharecdn.com/24378361-250510142118-8dee5f5a/85/Innovations-And-Applications-Of-Ai-Iot-And-Cognitive-Technologies-Jingyuan-Zhao-59-320.jpg)
Innovations And Applications Of Ai Iot And Cognitive Technologies Jingyuan Zhao
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- 6. Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies Jingyuan Zhao University of Toronto, Canada V. Vinoth Kumar MVJ College of Engineering, India A volume in the Advances in Computational Intelligence and Robotics (ACIR) Book Series
- 7. 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: cust@igi-global.com Web site: http://www.igi-global.com Copyright © 2021 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 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: eresources@igi-global.com. Names: Zhao, Jingyuan, 1968- editor. | Kumar, V. Vinoth, 1988- editor. Title: Handbook of research on innovations and Applications of AI, IoT, and Cognitive Technologies / Jingyuan Zhao, and V. Vinoth Kumar, editors. Description: Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2021] | Includes bibliographical references and index. | Summary: “This book provides perspectives of academics and industrial practitioners offering the latest innovations and applications of artificial intelligence (AI), Internet-of-Things (IoT) and cognitive based smart systems to provide information for all those interested in AI, IoT and Cognitive Technologies in emerging and developed economies in terms of their respective development situation toward public policies, technologies and intellectual capital, innovation systems, competition and strategies, marketing and growth capability, governance and relegation model etc”-- Provided by publisher. Identifiers: LCCN 2020046720 (print) | LCCN 2020046721 (ebook) | ISBN 9781799868705 (hardcover) | ISBN 9781799868729 (ebook) Subjects: LCSH: Internet of things--Industrial applications. | Artificial intelligence--Industrial applications. Classification: LCC TK5105.8857 .I493 2021 (print) | LCC TK5105.8857 (ebook) | DDC 004.67/8--dc23 LC record available at https://lccn.loc.gov/2020046720 LC ebook record available at https://lccn.loc.gov/2020046721 This book is published in the IGI Global book series Advances in Computational Intelligence and Robotics (ACIR) (ISSN: 2327-0411; eISSN: 2327-042X)
- 8. Advances in Computational Intelligence and Robotics (ACIR) Book Series While intelligence is traditionally a term applied to humans and human cognition, technology has pro- gressed in such a way to allow for the development of intelligent systems able to simulate many human traits. With this new era of simulated and artificial intelligence, much research is needed in order to continue to advance the field and also to evaluate the ethical and societal concerns of the existence of artificial life and machine learning. The Advances in Computational Intelligence and Robotics (ACIR) Book Series encourages scholarly discourse on all topics pertaining to evolutionary computing, artificial life, computational intelligence, machine learning, and robotics. ACIR presents the latest research being conducted on di- verse topics in intelligence technologies with the goal of advancing knowledge and applications in this rapidly evolving field. Mission Ivan Giannoccaro University of Salento, Italy ISSN:2327-0411 EISSN:2327-042X • Artificial Intelligence • Algorithmic Learning • Computational Logic • Brain Simulation • Pattern Recognition • Cognitive Informatics • Adaptive and Complex Systems • Synthetic Emotions • Automated Reasoning • Robotics Coverage IGI Global is currently accepting manuscripts for publication within this series. To submit a pro- posal for a volume in this series, please contact our AcquisitionEditorsatAcquisitions@igi-global.com or visit: http://www.igi-global.com/publish/. The Advances in Computational Intelligence and Robotics (ACIR) Book Series (ISSN 2327-0411) is published by IGI Global, 701 E. Chocolate Avenue, Hershey, PA 17033-1240, USA, www.igi-global.com. This series is composed of titles available for purchase individually; each title is edited to be contextually exclusive from any other title within the series. For pricing and ordering information please visit http:// www.igi-global.com/book-series/advances-computational-intelligence-robotics/73674. Postmaster: Send all address changes to above address. Copyright © 2021 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 informa- tion 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.
- 9. Titles in this Series For a list of additional titles in this series, please visit: http://www.igi-global.com/book-series/advances-computational-intelligence-robotics/73674 Genetic Algorithms and Applications for Stock Trading Optimization Vivek Kapoor (Devi Ahilya University, Indore, India) and Shubhamoy Dey (Indian Institute of Management, Indore, India) Engineering Science Reference • © 2021 • 262pp • H/C (ISBN: 9781799841050) • US $225.00 Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities Ismail Butun (Chalmers University of Technology, Sweden Konya Food and Agriculture University, Turkey Royal University of Technology, Sweden) Engineering Science Reference • © 2021 • 285pp • H/C (ISBN: 9781799874683) • US $245.00 Deep Natural Language Processing and AI Applications for Industry 5.0 Poonam Tanwar (Manav Rachna International Institute of Research and Studies, India) Arti Saxena (Manav Rachna International Institute of Research and Studies, India) and C. Priya (Vels Institute of Science, Technology, and Advanced Studies, India) Engineering Science Reference • © 2021 • 240pp • H/C (ISBN: 9781799877288) • US $245.00 AI Tools and Electronic Virtual Assistants for Improved Business Performance Christian Graham (University of Maine, USA) Business Science Reference • © 2021 • 300pp • H/C (ISBN: 9781799838418) • US $245.00 Transforming the Internet of Things for Next-Generation Smart Systems Bhavya Alankar (Jamia Hamdard, India) Harleen Kaur (Hamdard University, India) and Ritu Chauhan (Amity University, India) Engineering Science Reference • © 2021 • 173pp • H/C (ISBN: 9781799875413) • US $245.00 Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security Mohit Dua (National Institute of Technology, Kurukshetra, India) and Ankit Kumar Jain (National Institute of Technology, Kurukshetra, India) Engineering Science Reference • © 2021 • 355pp • H/C (ISBN: 9781799832997) • US $295.00 Driving Innovation and Productivity Through Sustainable Automation Ardavan Amini (EsseSystems, UK) Stephen Bushell (Bushell Investment Group, UK) and Arshad Mahmood (Birmingham City University, UK) Engineering Science Reference • © 2021 • 275pp • H/C (ISBN: 9781799858799) • US $245.00 701 East Chocolate Avenue, Hershey, PA 17033, USA Tel: 717-533-8845 x100 • Fax: 717-533-8661 E-Mail: cust@igi-global.com • www.igi-global.com
- 10. List of Contributors Aamani, R. / Vignan’s Institute of Information Technology, India.................................................... 278 Adilakshmi, Thondepu / Vasavi College of Engineering, India......................................................... 78 Alenazy, Wael Mohammad / CFY Deanship, King Saud University, Riyadh, Saudi Arabia............ 158 Alqahtani, Abdullah Saleh / CFY Deanship King Saud University, Saudi Arabia........................... 420 B., Swapna / Dr. M. G. R. Educational and Research Institute, India. .............................. 148, 195, 485 Bakri Hassan, Mona / Sudan University of Science and Technology, Sudan............................... 1, 336 Butchi Raju, K. / GRIET, India................................................................................................. 171, 450 D., Bhavana / Koneru Lakshmaiah Education Foundation, India. ............................................ 241, 381 D., Vijendra Babu / Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation, India.......................................................................................................................... 171 Dammalapati, Komali / Koneru Lakshmaiah Education Foundation, India. ................................... 359 Efeoglu, Ebru / Istanbul Gedik University, Turkey. ........................................................................... 290 Gopala Krishna, P. / Gokaraju Rangaraju Institute of Engineering and Technology, India............ 359 H., Hemasundari / Dr. M. G. R. Educational and Research Institute, India.................................... 148 Hasane Ahammad, S. K. / Koneru Lakshmaiah Education Foundation, India................................ 468 Hossain, Ashraf / National Institute of Technology, Silchar, India..................................................... 26 I. S., Beschi / St. Joseph’s College, India............................................................................................. 89 Jahangir, Ayesha / Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India.......................................................................................................................... 372 Jain, Arti / Jaypee Institute of Information Technology, Noida, India...................................... 117, 216 Janani, P. / Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India.129 Joseph, Rose Bindu / Christ Academy Institute for Advance Studies, India...................................... 321 K. R., Kumar / Adhiyamaan College of Engineering, India............................................................. 310 K., Amandeep Singh / Dr. M. G. R. Educational and Research Institute, India............................... 187 K., Kishore Kumar / Koneru Lakshmaiah Education Foundation, India........................................... 63 K., Meena / Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India.............................................................................................................................................. 432 K., Saikumar / Malla Reddy Institute of Technology, India.............................................................. 408 K., Sarada / Koneru Lakshmaiah Education Foundation, India....................................................... 408 K., Tejaswini / Koneru Lakshmaiah Education Foundation, India................................................... 381 Kalpana, Pamidimukkala / Koneru Lakshmaiah Education Foundation, India. ............................. 241 Kamalahasan, M. / Dr. M. G. R. Educational and Research Institute, India................................... 485 Kanmani Ruby, E. D. / Veltech Rangarajan Dr. Sakunthala RD Institute of Science and Technology, India.......................................................................................................................... 129 Koppula, Neeraja / MLR Institute of Technology, India................................................................... 278
- 11. Krishna, K. Chaitanya / Koneru Lakshmaiah Education Foundation, India.................................... 381 Kumar, Dhilip / Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India.............................................................................................................................................. 372 Kumar, Pattem Sampath / Malla Reddy Institute of Engineering and Technology, India. ............... 396 Kumar, Rajeev / Central University of Karnataka, India................................................................... 26 Kumar, S.Satheesh / REVA University, India................................................................................... 104 Kumar, Vinoth / MVJ College of Engineering, India....................................................................... 104 Kumta, Samyukta D. / REVA University, India................................................................................. 104 Kushwah, Rashmi / Jaypee Institute of Information Technology, Noida, India............................... 117 M. S., Supriya / Ramaiah University of Applied Sciences, India........................................................ 42 Magesh, S. / Maruthi Technocrat Services, India................................................................................ 89 Mahalakshmi, V. / Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India.......................................................................................................................... 129 Manivannan, S. / Dr. M. G. R. Educational and Research Institute, India....................................... 485 Manjunath, Kannika / Ramaiah University of Applied Sciences, India............................................ 42 Mohammed, Zahraa Tagelsir / Red Sea University, Sudan.................................................................. 1 Muthukumaran, V. / REVA University, India................................................................................... 104 Nagarajan, Senthil Murugan / VIT-AP University, India................................................................... 89 Nagi Reddy, K. / Lords Institute of Engineering and Technology, India. .......................................... 171 Nalajala, Sunanda / Koneru Lakshmaiah Education Foundation, India.......................................... 450 Neelothpala, Adada / Koneru Lakshmaiah Education Foundation, India........................................ 241 Niveditha, V. R. / Dr. M. G. R. Educational and Research Institute, Chennai, India........................ 104 P., Bessy Deborah / Dr. M. G. R. Educational and Research Institute, India.................................... 187 P., Swathi / Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India.372 P., Visu / Velammal Enginerring College, India................................................................................ 310 Patel, Ibrahim / B. V. Raju Institute of Technology, India. ................................................................ 278 Purwar, Archana / Jaypee Institute of Information Technology, Noida, India................................. 216 R, Jothikumar / Department of Computer Science and Engineering, Shadan College of Engineering and Technology, India................................................................................................ 78 R., Jayashree / College of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur, India.................................................................................................................... 258 R., Jothikumar / Shadan College of Engineering and Technology, India........................................ 310 R., Kumar / National Institute of Technology, Nagaland, India. ....................................................... 310 R., Murugesan / REVA University, India. .......................................................................................... 104 R., Vijay Anand / Velloe Institute of Technology, India..................................................................... 310 Raghu, K. / Mahatma Gandhi Institute of Technology, India............................................................ 396 Rajalakshmi, D. / Sri Sairam Institute of Technology, India............................................................. 432 Rajini, S. Nirmala Sigirtha / Dr. M. G. R. Educational and Research Institute, India..................... 204 Ramana Rao, M. V. / Osmania University, India................................................................................ 78 Rao, Koppula Srinivas / MLR Institute of Technology, India.................................................... 396, 408 Rao, Sirasani Srinivasa / Mahatma Gandhi Institute of Technology, India...................................... 450 Ratna Raju, A. / Mahatma Gandhi Institute of Technology, India................................................... 171 Reddy, B. Veerasekhar / MLR Institute of Technology, India. ........................................................... 408 S, Radha RamMohan / Dr. M. G. R. Educational and Research Institute, India.............................. 187 S., Leena Nesamani / Dr. M. G. R. Educational and Research Institute, India................................. 204 S., Magesh / Maruthi Technocrat E-Services, India.......................................................................... 187
- 12. S., Saravanan / B. V. Raju Institute of Technology, India.................................................................. 396 S., Satheesh Kumar / REVA University, India................................................................................... 321 S., Susi / Shadan Women’s College of Engineering and Technology, India....................................... 310 S., Vaithyasubramanian / D. G. Vaishnav College, India................................................................ 258 Saeed, Rashid A. / Sudan University of Science and Technology, Sudan Taif University, Saudi Arabia........................................................................................................................................ 1, 336 Sah, Nitesh Kumar / Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India.......................................................................................................................... 372 Sahithya, A. N. V. / Koneru Lakshmaiah Education Foundation, India............................................ 381 Saikumar, K. / Mallareddy University, India.................................................................................... 278 Sampath Dakshina Murthy, A. / Vignan’s Institute of Information Technology, India................... 468 Sankara Babu, B. / Gokaraju Rangaraju Institute of Engineering and Technology, India.............. 359 Sarada, K. / KLEF, India................................................................................................................... 278 Sathyasri, B. / Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India.............................................................................................................................................. 129 Sayed Ali Ahmed, Elmustafa / Sudan University of Science and Technology, Sudan Red Sea University, Sudan. ...................................................................................................................... 1, 336 Singamaneni, Kranthi Kumar / Gokaraju Rangaraju Institute of Engineering and Technology, India.............................................................................................................................................. 468 Subba Ramaiah, V. / Mahatma Gandhi Institute of Technology, India............................................ 359 Swaroop, Abhishek / Bhagwan Parshuram Institute of Technology, India....................................... 117 Tuna, Gurkan / Trakya University, Turkey........................................................................................ 290 U. R., Kavana / Ramaiah University of Applied Sciences, India......................................................... 42 Uday, Akshay K. / Dr. M. G. R. Educational and Research Institute, India...................................... 321 V. R., Niveditha / Dr. M. G. R. Educational and Research Institute, India....................................... 187 V. V. S., Sasank / Koneru Lakshmaiah Education Foundation, India............................................... 468 V., Muthukumaran / REVA University, India............................................................................. 89, 321 V., Rajesh / Department of Electronics and Communication Engineering, Koneru Lakshmaiah Educational Foundation, India. ..................................................................................................... 396 V., Vinoth Kumar / MVJ College of Engineering, India............................................................. 89, 321 V., Vinothkumar / MVJ College of Engineering, India.................................................................... 372 Vatambeti, Ramesh / CHRIST University (Deemed), India. ............................................................. 450 Venkatesh, M. Gokul / Sidhartha Medical College, India. .................................................................. 78 Vikas, N. Venkata / Koneru Lakshmaiah Education Foundation, India. ........................................... 381 Vishnu Kumar, S. / Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India.......................................................................................................................... 129 Yadav, Arun / National Institute of Technology, Hamirpur, India.................................................... 117 Yadav, Divakar / National Institute of Technology, Hamirpur, India............................................... 216
- 13. Table of Contents Preface. ................................................................................................................................................ xxx Section 1 AI and IoT: A Blend in Future Technologies and Systems Chapter 1 Algorithms Optimization for Intelligent IoV Applications..................................................................... 1 Elmustafa Sayed Ali Ahmed, Sudan University of Science and Technology, Sudan Red Sea University, Sudan Zahraa Tagelsir Mohammed, Red Sea University, Sudan Mona Bakri Hassan, Sudan University of Science and Technology, Sudan Rashid A. Saeed, Sudan University of Science and Technology, Sudan Taif University, Saudi Arabia Chapter 2 Cooperative Relaying Communication in IoT Applications for 5G Radio Networks. ........................... 26 Rajeev Kumar, Central University of Karnataka, India Ashraf Hossain, National Institute of Technology, Silchar, India Chapter 3 The Rise of IoT and Big Data Analytics for Disaster Management Systems........................................ 42 Supriya M. S., Ramaiah University of Applied Sciences, India Kannika Manjunath, Ramaiah University of Applied Sciences, India Kavana U. R., Ramaiah University of Applied Sciences, India Chapter 4 IoT-Based Smart Agriculture................................................................................................................. 63 Kishore Kumar K., Koneru Lakshmaiah Education Foundation, India
- 14. Chapter 5 Mobile Geo-Fencing Triggers for Alerting Entries Into COVID-19 Containment Zones Using IoT... 78 M. V. Ramana Rao, Osmania University, India Thondepu Adilakshmi, Vasavi College of Engineering, India M. Gokul Venkatesh, Sidhartha Medical College, India Jothikumar R, Department of Computer Science and Engineering, Shadan College of Engineering and Technology, India Chapter 6 Fine Tuning Smart Manufacturing Enterprise Systems: A Perspective of Internet of Things-Based Service-Oriented Architecture............................................................................................................... 89 Senthil Murugan Nagarajan, VIT-AP University, India Muthukumaran V., REVA University, India Vinoth Kumar V., MVJ College of Engineering, India Beschi I. S., St. Joseph’s College, India S. Magesh, Maruthi Technocrat Services, India Chapter 7 A Quantum Technology-Based LiFi Security Using Quantum Key Distribution............................... 104 Vinoth Kumar, MVJ College of Engineering, India V. R. Niveditha, Dr. M. G. R. Educational and Research Institute, Chennai, India V. Muthukumaran, REVA University, India S.Satheesh Kumar, REVA University, India Samyukta D. Kumta, REVA University, India Murugesan R., REVA University, India Chapter 8 Role of Artificial Intelligence of Things (AIoT) to Combat Pandemic COVID-19. ............................ 117 Arti Jain, Jaypee Institute of Information Technology, Noida, India Rashmi Kushwah, Jaypee Institute of Information Technology, Noida, India Abhishek Swaroop, Bhagwan Parshuram Institute of Technology, India Arun Yadav, National Institute of Technology, Hamirpur, India Chapter 9 Recent Trends in Wearable Device Technology for Health State Monitoring. .................................... 129 E. D. Kanmani Ruby, Veltech Rangarajan Dr. Sakunthala RD Institute of Science and Technology, India P. Janani, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India V. Mahalakshmi, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India B. Sathyasri, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India S. Vishnu Kumar, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India
- 15. Chapter 10 IoT-Based Delineation and Evolution of Kid’s Safety Portable Devices............................................. 148 Hemasundari H., Dr. M. G. R. Educational and Research Institute, India Swapna B., Dr. M. G. R. Educational and Research Institute, India Chapter 11 Blockchain-Enabled Internet of Things for Unsupervised Structural Health Monitoring in Potential Building Structures............................................................................................................... 158 Wael Mohammad Alenazy, CFY Deanship, King Saud University, Riyadh, Saudi Arabia Chapter 12 An Advanced Wireless Sensor Networks Design for Energy-Efficient Applications Using Condition-Based Access Protocol. ....................................................................................................... 171 Vijendra Babu D., Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation, India K. Nagi Reddy, Lords Institute of Engineering and Technology, India K. Butchi Raju, GRIET, India A. Ratna Raju, Mahatma Gandhi Institute of Technology, India Chapter 13 Effective Image Fusion of PET-MRI Brain Images Using Wavelet Transforms................................. 187 Magesh S., Maruthi Technocrat E-Services, India Niveditha V. R., Dr. M. G. R. Educational and Research Institute, India Radha RamMohan S, Dr. M. G. R. Educational and Research Institute, India Amandeep Singh K., Dr. M. G. R. Educational and Research Institute, India Bessy Deborah P., Dr. M. G. R. Educational and Research Institute, India Chapter 14 IoT-Enabled Non-Contact-Based Infrared Thermometer for Temperature Recording of a Person..... 195 Swapna B., Dr M. G. R. Educational and Research Institute, India Chapter 15 Predictive Modeling for Classification of Breast Cancer Dataset Using Feature Selection Techniques........................................................................................................................................... 204 Leena Nesamani S., Dr. M. G. R. Educational and Research Institute, India S. Nirmala Sigirtha Rajini, Dr. M. G. R. Educational and Research Institute, India Chapter 16 Credit Card Fraud Detection Using K-Means and Fuzzy C-Means.................................................... 216 Arti Jain, Jaypee Institute of Information Technology, Noida, India Archana Purwar, Jaypee Institute of Information Technology, Noida, India Divakar Yadav, National Institute of Technology, Hamirpur, India
- 16. Chapter 17 A Hybrid Method to Reduce PAPR of OFDM to Support 5G Technology........................................ 241 Bhavana D., Koneru Lakshmaiah Education Foundation, India Adada Neelothpala, Koneru Lakshmaiah Education Foundation, India Pamidimukkala Kalpana, Koneru Lakshmaiah Education Foundation, India Chapter 18 Restricted Boltzmann Machine-Driven Matchmaking Algorithm With Interactive Estimation of Distribution for Websites..................................................................................................................... 258 Jayashree R., College of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur, India Vaithyasubramanian S., D. G. Vaishnav College, India Section 2 Big Data and Cognitive Technologies: Current Applications and Future Challenges Chapter 19 Identification and Recognition of Speaker Voice Using a Neural Network-Based Algorithm: Deep Learning............................................................................................................................................... 278 Neeraja Koppula, MLR Institute of Technology, India K. Sarada, KLEF, India Ibrahim Patel, B. V. Raju Institute of Technology, India R. Aamani, Vignan’s Institute of Information Technology, India K. Saikumar, Mallareddy University, India Chapter 20 Traditional and Innovative Approaches for Detecting Hazardous Liquids.......................................... 290 Ebru Efeoglu, Istanbul Gedik University, Turkey Gurkan Tuna, Trakya University, Turkey Chapter 21 Sentiment Analysis of Tweets on the COVID-19 Pandemic Using Machine Learning Techniques... 310 Jothikumar R., Shadan College of Engineering and Technology, India Vijay Anand R., Velloe Institute of Technology, India Visu P., Velammal Enginerring College, India Kumar R., National Institute of Technology, Nagaland, India Susi S., Shadan Women’s College of Engineering and Technology, India Kumar K. R., Adhiyamaan College of Engineering, India Chapter 22 Intelligent Medical Data Analytics Using Classifiers and Clusters in Machine Learning. .................. 321 Muthukumaran V., REVA University, India Satheesh Kumar S., REVA University, India Rose Bindu Joseph, Christ Academy Institute for Advance Studies, India Vinoth Kumar V., MVJ College of Engineering, India Akshay K. Uday, Dr. M. G. R. Educational and Research Institute, India
- 17. Chapter 23 Machine Learning for Industrial IoT Systems..................................................................................... 336 Mona Bakri Hassan, Sudan University of Science and Technology, Sudan Elmustafa Sayed Ali Ahmed, Sudan University of Science and Technology, Sudan Red Sea University, Sudan Rashid A. Saeed, Sudan University of Science and Technology, Sudan Taif University, Saudi Arabia Chapter 24 A Research on Software Engineering Research in Machine Learning................................................ 359 Komali Dammalapati, Koneru Lakshmaiah Education Foundation, India B. Sankara Babu, Gokaraju Rangaraju Institute of Engineering and Technology, India P. Gopala Krishna, Gokaraju Rangaraju Institute of Engineering and Technology, India V. Subba Ramaiah, Mahatma Gandhi Institute of Technology, India Chapter 25 Intelligent Speech Processing Technique for Suspicious Voice Call Identification Using Adaptive Machine Learning Approach............................................................................................................... 372 Dhilip Kumar, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India Swathi P., Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India Ayesha Jahangir, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India Nitesh Kumar Sah, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India Vinothkumar V., MVJ College of Engineering, India Chapter 26 Image Captioning Using Deep Learning............................................................................................. 381 Bhavana D., Koneru Lakshmaiah Education Foundation, India K. Chaitanya Krishna, Koneru Lakshmaiah Education Foundation, India Tejaswini K., Koneru Lakshmaiah Education Foundation, India N. Venkata Vikas, Koneru Lakshmaiah Education Foundation, India A. N. V. Sahithya, Koneru Lakshmaiah Education Foundation, India Chapter 27 Leveraging Big Data Analytics and Hadoop in Developing India’s Healthcare Services................... 396 Koppula Srinivas Rao, MLR Institute of Technology, India Saravanan S., B. V. Raju Institute of Technology, India Pattem Sampath Kumar, Malla Reddy Institute of Engineering and Technology, India Rajesh V., Department of Electronics and Communication Engineering, Koneru Lakshmaiah Educational Foundation, India K. Raghu, Mahatma Gandhi Institute of Technology, India
- 18. Chapter 28 A Sequential Data Mining Technique for Identification of Fault Zone Using FACTS-Based Transmission........................................................................................................................................ 408 Koppula Srinivas Rao, MLR Institute of Technology, India B. Veerasekhar Reddy, MLR Institute of Technology, India Sarada K., Koneru Lakshmaiah Education Foundation, India Saikumar K., Malla Reddy Institute of Technology, India Chapter 29 K-Means Clustering Machine Learning Concept to Enable Social Distancing in Public Places........ 420 Abdullah Saleh Alqahtani, CFY Deanship King Saud University, Saudi Arabia Chapter 30 An Efficient Selfishness Control Mechanism for Mobile Ad hoc Networks....................................... 432 D. Rajalakshmi, Sri Sairam Institute of Technology, India Meena K., Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India Chapter 31 Estimation of Secured Wireless Sensor Networks and Its Significant Observation for Improving Energy Efficiency Using Cross-Learning Algorithms......................................................................... 450 Sirasani Srinivasa Rao, Mahatma Gandhi Institute of Technology, India K. Butchi Raju, GRIET, India Sunanda Nalajala, Koneru Lakshmaiah Education Foundation, India Ramesh Vatambeti, CHRIST University (Deemed), India Chapter 32 Executing CNN-LSTM Algorithm for Recognizable Proof of Cervical Spondylosis Infection on Spinal Cord MRI Image: Machine Learning Image............................................................................ 468 Sasank V. V. S., Koneru Lakshmaiah Education Foundation, India Kranthi Kumar Singamaneni, Gokaraju Rangaraju Institute of Engineering and Technology, India A. Sampath Dakshina Murthy, Vignan’s Institute of Information Technology, India S. K. Hasane Ahammad, Koneru Lakshmaiah Education Foundation, India Chapter 33 Soil Nutrients and pH Level Testing Using Multivariate Statistical Techniques for Crop Selection.. 485 Swapna B., Dr. M. G. R. Educational and Research Institute, India S. Manivannan, Dr. M. G. R. Educational and Research Institute, India M. Kamalahasan, Dr. M. G. R. Educational and Research Institute, India
- 19. Compilation of References................................................................................................................ 499 About the Contributors..................................................................................................................... 552 Index.................................................................................................................................................... 567
- 20. Detailed Table of Contents Preface. ................................................................................................................................................ xxx Section 1 AI and IoT: A Blend in Future Technologies and Systems Section 1 introduces emerging AI and IoT technologies and systems, as well as their innovations and applications that are responsible for the digitization of all the sectors through automation and together rules the technological aspects of our lives. Section 1 is organized into 18 chapters. Chapter 1 Algorithms Optimization for Intelligent IoV Applications..................................................................... 1 Elmustafa Sayed Ali Ahmed, Sudan University of Science and Technology, Sudan Red Sea University, Sudan Zahraa Tagelsir Mohammed, Red Sea University, Sudan Mona Bakri Hassan, Sudan University of Science and Technology, Sudan Rashid A. Saeed, Sudan University of Science and Technology, Sudan Taif University, Saudi Arabia Internet of vehicles (IoV) has recently become an emerging promising field of research due to the increasing number of vehicles each day. It is a part of the internet of things (IoT) which deals with vehicle communications. As vehicular nodes are considered always in motion, they cause frequent changes in the network topology. These changes cause issues in IoV such as scalability, dynamic topology changes, and shortest path for routing. In this chapter, the authors will discuss different optimization algorithms (i.e., clusteringalgorithms,antcolonyoptimization,bestinterfaceselection[BIS]algorithm,mobilityadaptive density connected clustering algorithm, meta-heuristics algorithms, and quality of service [QoS]-based optimization). These algorithms provide an important intelligent role to optimize the operation of IoV networks and promise to develop new intelligent IoV applications. Chapter 2 Cooperative Relaying Communication in IoT Applications for 5G Radio Networks. ........................... 26 Rajeev Kumar, Central University of Karnataka, India Ashraf Hossain, National Institute of Technology, Silchar, India ThischapterpresentscooperativerelayingnetworksthatarehelpfulinInternetofThing(IoT)applications for fifth-generation (5G) radio networks. It provides reliable connectivity as the wireless device is out of range from cellular network, high throughput gains and enhance the lifetime of wireless networks. These features can be achieved by designing the advanced protocols. The design of advanced protocols plays
- 21. an important role to combat the effect of channel fading, data packet scheduling at the buffered relay, average delay, and traffic intensity. To achieve our goals, we consider two-way cooperative buffered relay networks and then investigate advanced protocols such as without channel state information (CSI) i.e., buffer state information (BSI) only and with partial transmit CSI i.e., BSI/CSI with the assistance of one dimensional Markov chain and transmission policies in fading environment. The outage probability of consecutive links and outage probability of multi-access and broadcast channels are provided in closed- form.Further,thebufferedrelayachievesmaximumthroughputgainsinclosed-formforalltheseprotocols. The objective function of throughput of the buffered relay is evaluated in fractional programming that is transformed into linear program using standard CVX tool. Numerical results show that our proposed protocols performance better as compared to conventional method studied in the literature. Finally, this chapter provides possible future research directions. Chapter 3 The Rise of IoT and Big Data Analytics for Disaster Management Systems........................................ 42 Supriya M. S., Ramaiah University of Applied Sciences, India Kannika Manjunath, Ramaiah University of Applied Sciences, India Kavana U. R., Ramaiah University of Applied Sciences, India Uninvited disasters wreak havoc on society, both economically and psychologically. These losses can be minimized if events can be anticipated ahead of time. The majority of large cities in developing countries with increasing populations are highly vulnerable disaster areas around the world. This is due to a lack of situational information in their authorities in the event of a crisis, which is due to a scarcity of resources. Both natural and human-induced disasters need to be pre-planned and reactive to minimize the risk of causalities and environmental/infrastructural disruption. Disaster recovery systems must also effectively obtain relevant information. The developments in big data and the internet of things (IoT) have made a greater contribution to accuracy and timely decision-making in the disaster management system (DMS). The chapter explains why IoT and big data are needed to cope with disasters, as well as how these technologies work to solve the problem. Chapter 4 IoT-Based Smart Agriculture................................................................................................................. 63 Kishore Kumar K., Koneru Lakshmaiah Education Foundation, India SmartfarmingisanevolvingconceptsinceIoTsensorsarecapableofprovidingagriculturalfieldinformation and then acting on the basis of user feedback. The main factor in improving the yield of efficient crops is the control of environmental conditions. There is a small yard, farmland, or a plantation area for most of us. However, our busy timetable does not allow us to manage it well. But we can easily accomplish it with the use of technology. So, the authors make an IoT-based smart farming system that can control soil moisture. As data has become a critical component in modern agriculture to assist producers with critical decisions and make a decision with objective data obtained from sensors, significant advantages emerge. This chapter explores the current state of advanced farm management systems by revisiting each critical phase, from data collection in crop fields to variable rate applications, in order for growers to make informed decisions save money while also protecting the environment and transforming how food is grown to meet potential population growth.
- 22. Chapter 5 Mobile Geo-Fencing Triggers for Alerting Entries Into COVID-19 Containment Zones Using IoT... 78 M. V. Ramana Rao, Osmania University, India Thondepu Adilakshmi, Vasavi College of Engineering, India M. Gokul Venkatesh, Sidhartha Medical College, India Jothikumar R, Department of Computer Science and Engineering, Shadan College of Engineering and Technology, India In a thickly populated nation like India, it is hard to forecast community transmission of COVID-19. Hence, a number of containment zones had been recognized all over the country separated into red, orange, and green zones, individually. People are restricted to move into these containment zones. This chapter focuses on informing the public about the containment zone when they are in travel and also sends an alert to the police when a person enters the containment zone without permission using the containment zone alert system. This chapter suggests a containment zone alert system by means of geo-fencing technology to identify the movement of public, deliver info about the danger to the public in travel and also send an alert to the police when there is an entry or exit detected in the containment zone by the use of location-based services (LBS). By creating a fence virtually called geo-fence at the containment zones established based on the government info, this system monitors public movements like entry and exit to fence. Chapter 6 Fine Tuning Smart Manufacturing Enterprise Systems: A Perspective of Internet of Things-Based Service-Oriented Architecture............................................................................................................... 89 Senthil Murugan Nagarajan, VIT-AP University, India Muthukumaran V., REVA University, India Vinoth Kumar V., MVJ College of Engineering, India Beschi I. S., St. Joseph’s College, India S. Magesh, Maruthi Technocrat Services, India The workflow between business and manufacturing system level is changing leading to delay in exploring the context of innovative ideas and solutions. Smart manufacturing systems progress rapid growth in integrating the operational capabilities of networking functionality and communication services with cloud-basedenterprisearchitecturesthroughruntimeenvironment.Finetuningaimstoprocessintelligent management, flexible monitoring, dynamic network services using internet of things (IoT)-based service oriented architecture (SOA) solutions in numerous enterprise systems. SOA is an architectural pattern for building software business systems based on loosely coupled enterprise infrastructure services and components. The IoT-based SOA enterprise systems incorporate data elicitation, integrating agile methodologies,orchestrateunderlyingblack-boxservicesbypromotinggrowthinmanufacturerenterprises workflow. This chapter proposes the integration of standard workflow model between business system level and manufacturing production level with an IoT-enabled SOA framework.
- 23. Chapter 7 A Quantum Technology-Based LiFi Security Using Quantum Key Distribution............................... 104 Vinoth Kumar, MVJ College of Engineering, India V. R. Niveditha, Dr. M. G. R. Educational and Research Institute, Chennai, India V. Muthukumaran, REVA University, India S.Satheesh Kumar, REVA University, India Samyukta D. Kumta, REVA University, India Murugesan R., REVA University, India Light fidelity (Li-Fi) is a technology that is used to design a wireless network for communication using light. Current technology based on wireless fidelity (Wi-Fi) has some drawbacks that include speed and bandwidth limit, security issues, and attacks by malicious users, which yield Wi-Fi as less reliable compared to LiFi. The conventional key generation techniques are vulnerable to the current technological improvement in terms of computing power, so the solution is to introduce physics laws based on quantum technology and particle nature of light. Here the authors give a methodology to make the BB84 algorithm, a quantum cryptographic algorithm to generate the secret keys which will be shared by polarizing photons and more secure by eliminating one of its limitations that deals with dependency on the classical channel. The result obtained is sequence of 0 and 1, which is the secret key. The authors make use of the generated shared secret key to encrypt data using a one-time pad technique and transmit the encrypted data using LiFi and removing the disadvantage of the existing one-time pad technique. Chapter 8 Role of Artificial Intelligence of Things (AIoT) to Combat Pandemic COVID-19. ............................ 117 Arti Jain, Jaypee Institute of Information Technology, Noida, India Rashmi Kushwah, Jaypee Institute of Information Technology, Noida, India Abhishek Swaroop, Bhagwan Parshuram Institute of Technology, India Arun Yadav, National Institute of Technology, Hamirpur, India COVID-19 is caused by virus called SARS-CoV-2, which was declared by the WHO as global pandemic. Since the outbreak, there has been a rush to explore Artificial Intelligence (AI) and Internet of Things (IoT) for diagnosing, predicting, and treating infections. At present, individual technologies, AI and IoT, play important roles yet do not impact individually against the pandemic because of constraints like lack of historical data and the existence of biased, noisy, and outlier data. To overcome, balance among data privacy, public health, and human-AI-IoT interaction is must. Artificial Intelligence of Things (AIoT) appears to be a more efficient technological solution that can play a significant role to control COVID-19. IoT devices produce huge data which are gathered and mined for actionable effects in AI. AI converts data into useful results which are utilized by IoT devices. AIoT entails AI through machine learning and decision making to IoT and renovates IoT to add data exchange and analytics to AI. In this chapter, AIoT will serve as a potential analytical tool to fight against the pandemic.
- 24. Chapter 9 Recent Trends in Wearable Device Technology for Health State Monitoring. .................................... 129 E. D. Kanmani Ruby, Veltech Rangarajan Dr. Sakunthala RD Institute of Science and Technology, India P. Janani, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India V. Mahalakshmi, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India B. Sathyasri, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India S. Vishnu Kumar, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India The latest innovative technology products in the market are paving the way for a new growth in the medical field over medical wearable devices. Globally, the medical market is said to be segmented on the basis of global medical wearable report by its type, application level, regional level, and country level. In this medical advisory, these devices are classified as diagnostic, therapeutic, and respiratory. The regions covered include Europe, Asia-Pacific, and the rest of the world. These wearable devices are technically embedded with electronic devices which the users are able to adhere to their body parts. The main function of these wearable devices is said to be collecting users’ personal health data (e.g., such devices include measurement on fitness of body, heartbeat measurement, ECG measurement, blood pressure monitoring, etc.). Chapter 10 IoT-Based Delineation and Evolution of Kid’s Safety Portable Devices............................................. 148 Hemasundari H., Dr. M. G. R. Educational and Research Institute, India Swapna B., Dr. M. G. R. Educational and Research Institute, India Currently there are numerous portables in the retail which assist tracking the day-by-day actions of kids and furthermore help discover the kid utilizing Wi-Fi and Bluetooth directions available on the gadget. Bluetooth gives off an impression of being an untrustworthy mode of correspondence connecting the parent and kid. Along these lines, the pivotal motive of this chapter is to get an authorized corresponding medium that links the kid’s portable and the parents. The genitor can send a book with explicit tags, for example, “location,” “temperature,” “UV,” “SOS,” “BUZZ,” and so forth. The portable device will response with a book encompassing the continuous precise region of the kid, which after monitoring hand down headings to the youngster’s region on Google Maps software will similarly provide the atmospheric temperature and UV ray emission file with a goal that genitors can pursue if temperature or UV emission isn’t reasonable to the kid. Chapter 11 Blockchain-Enabled Internet of Things for Unsupervised Structural Health Monitoring in Potential Building Structures............................................................................................................... 158 Wael Mohammad Alenazy, CFY Deanship, King Saud University, Riyadh, Saudi Arabia The integration of internet of things, artificial intelligence, and blockchain enabled the monitoring of structural health with unattended and automated means. Remote monitoring mandates intelligent automated decision-making capability, which is still absent in present solutions. The proposed solution
- 25. in this chapter contemplates the architecture of smart sensors, customized for individual structures, to regulate the monitoring of structural health through stress, strain, and bolted joints looseness. Long range sensors are deployed for transmitting the messages a longer distance than existing techniques. From the simulated results, different sensors record the monitoring information and transmit to the blockchain platform in terms of pressure points, temperature, pre-tension force, and the architecture deems the criticality of transactions. Blockchain platform will also be responsible for storage and accessibility of information from a decentralized medium, automation, and security. Chapter 12 An Advanced Wireless Sensor Networks Design for Energy-Efficient Applications Using Condition-Based Access Protocol. ....................................................................................................... 171 Vijendra Babu D., Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation, India K. Nagi Reddy, Lords Institute of Engineering and Technology, India K. Butchi Raju, GRIET, India A. Ratna Raju, Mahatma Gandhi Institute of Technology, India A modern wireless sensor and its development majorly depend on distributed condition maintenance protocol. The medium access and its computing have been handled by multi hope sensor mechanism. In this investigation, WSN networks maintenance is balanced through condition-based access (CBA) protocol. The CBA is most useful for real-time 4G and 5G communication to handle internet assistance devices. The following CBA mechanism is energy efficient to increase the battery lifetime. Due to sleep mode and backup mode mechanism, this protocol maintains its energy efficiency as well as network throughput. Finally, 76% of the energy consumption and 42.8% of the speed of operation have been attained using CBI WSN protocol. Chapter 13 Effective Image Fusion of PET-MRI Brain Images Using Wavelet Transforms................................. 187 Magesh S., Maruthi Technocrat E-Services, India Niveditha V. R., Dr. M. G. R. Educational and Research Institute, India Radha RamMohan S, Dr. M. G. R. Educational and Research Institute, India Amandeep Singh K., Dr. M. G. R. Educational and Research Institute, India Bessy Deborah P., Dr. M. G. R. Educational and Research Institute, India Image processing concepts are used in the biomedical domain. Brain tumors are among the dreadful diseases. The primary brain tumors start with errors which are the mutations that take place in the part of DNA. This mutation makes the cells breed in a huge manner and makes the healthier cells die. The mass of the unhealthier cells is called tumor, or the unwanted cell growth in the tissues of the brain are called brain tumors. In this chapter, images from the positron emission tomography (PET) scan and MRI scan are fused as a one image, and from that image, neural network concepts are applied to detect the tumor. The main intention of this proposed approach is to segment and identify brain tumors in an automatic manner using image fusion with neural network concepts. Segmentation of brain images is needed to segment properly from other brain tissues. Perfect detection of size and position of the brain tumor plays an essential role in the identification of the tumor.
- 26. Chapter 14 IoT-Enabled Non-Contact-Based Infrared Thermometer for Temperature Recording of a Person..... 195 Swapna B., Dr M. G. R. Educational and Research Institute, India Laboratoriesareessentialfacilitiesprovidedinprofessionalinstitutesforscientificandtechnologicalwork. The lab must ensure their accuracy to regulatory requirements and maintain their data records so that the laboratory environment can be monitored properly. The laboratory environment temperature (LET) is monitored to ensure proper regulation and maintenance of indoor conditions and also to correlate the collected samples with these conditions. The LET data collection must be stored to influence the quality of the results and to ensure the stability of the laboratory environment. Hence, an IoT solution is presented to supervise real-time temperature and is known as iRT. This method helps to monitor ambient object supervision in real time. It is composed of a hardware prototype to collect the temperature data and to use web application to provide the history of temperature evolution. The result gained from the study is promising, and it provides a significant contribution to IoT-based temperature monitoring systems. Chapter 15 Predictive Modeling for Classification of Breast Cancer Dataset Using Feature Selection Techniques........................................................................................................................................... 204 Leena Nesamani S., Dr. M. G. R. Educational and Research Institute, India S. Nirmala Sigirtha Rajini, Dr. M. G. R. Educational and Research Institute, India Predictive modeling or predict analysis is the process of trying to predict the outcome from data using machine learning models. The quality of the output predominantly depends on the quality of the data that is provided to the model. The process of selecting the best choice of input to a machine learning model depends on a variety of criteria and is referred to as feature engineering. The work is conducted to classify the breast cancer patients into either the recurrence or non-recurrence category. A categorical breast cancer dataset is used in this work from which the best set of features is selected to make accurate predictions.Twofeatureselectiontechniques,namelythechi-squaredtechniqueandthemutualinformation technique, have been used. The selected features were then used by the logistic regression model to make the final prediction. It was identified that the mutual information technique proved to be more efficient and produced higher accuracy in the predictions. Chapter 16 Credit Card Fraud Detection Using K-Means and Fuzzy C-Means.................................................... 216 Arti Jain, Jaypee Institute of Information Technology, Noida, India Archana Purwar, Jaypee Institute of Information Technology, Noida, India Divakar Yadav, National Institute of Technology, Hamirpur, India Machine learning (ML) proven to be an emerging technology from small-scale to large-scale industries. One of the important industries is banking, where ML is being adapted all over the world by employing online banking. The online banking is using ML techniques in detecting fraudulent transactions like credit card fraud detection, etc. Hence, in this chapter, a Credit card Fraud Detection (CFD) system is devised using Luhn’s algorithm and k-means clustering. Moreover, CFD system is also developed using Fuzzy C-Means (FCM) clustering instead of k-means clustering. Performance of CFD using both clustering techniques is compared using precision, recall and f-measure. The FCM gives better results in comparison to k-means clustering. Further, other evaluation metrics such as fraud catching rate, false alarm rate, balanced classification rate, and Mathews correlation coefficient are also calculated to show
- 27. how well the CFD system works in the presence of skewed data. Chapter 17 A Hybrid Method to Reduce PAPR of OFDM to Support 5G Technology........................................ 241 Bhavana D., Koneru Lakshmaiah Education Foundation, India Adada Neelothpala, Koneru Lakshmaiah Education Foundation, India Pamidimukkala Kalpana, Koneru Lakshmaiah Education Foundation, India The orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation scheme used for the transfer of multimedia data. Well-known systems like ADSL (asymmetric digital subscriber line) internet,wirelesslocalareanetworks(LANs),long-termevolution(LTE),and5GtechnologiesuseOFDM. The major limitation of OFDM is the high peak-to-average power ratio (PAPR). High PAPR lowers the power efficiency, thus impeding the implementation of OFDM. The PAPR problem is more significant in an uplink. A high peak-to-average power ratio (PAPR) occurs due to large envelope fluctuations in OFDM signal and requires a highly linear high-power amplifier (HPA). Power amplifiers with a large linear range are expensive, bulky, and difficult to manufacture. In order to reduce the PAPR, a hybrid techniqueisproposedinthischapterwithrepeatedclippingandfiltering(RCF)andprecodingtechniques. The proposed method is improving the PAPR as well as BER. Five types of pre-coding techniques are used and then compared with each other. Chapter 18 Restricted Boltzmann Machine-Driven Matchmaking Algorithm With Interactive Estimation of Distribution for Websites..................................................................................................................... 258 Jayashree R., College of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur, India Vaithyasubramanian S., D. G. Vaishnav College, India In this chapter, restricted Boltzmann machine-driven (RBM) algorithm is presented with an enhanced interactive estimation of distribution (IED) method for websites. Indian matrimonial websites are famous intermediates for finding marriage-partners. Matchmaking is one of the most pursued objectives in matrimonial websites. The complex evaluations and full of zip user preferences are the challenges. An interactiveevolutionaryalgorithmwithpowerfulevolutionarystrategiesisagoodchoiceformatchmaking. Initially, an IED is generated as a probability model for the estimation of a user preference and then two RBM models, one for interested and the other for not-interested, is generated to endow with a set of appropriate matches simultaneously. In the proposed matchmaking method, the RBM model is combined with social group knowledge. Some benchmarks from the matrimonial internet site are pragmatic to empirically reveal the pre-eminence of the anticipated method.
- 28. Section 2 Big Data and Cognitive Technologies: Current Applications and Future Challenges Section2providesinsightsonlearningbasedonbigdataandcognitivecomputingtechnologies,including cutting edge topics (e.g., machine learning for Industrial IoT systems, deep learning, reinforced learning, decision trees for IoT systems, computational intelligence and cognitive systems, cognitive learning for IoT systems, cognitive-inspired computing systems). Section 2 is organized into 17 chapters. Chapter 19 Identification and Recognition of Speaker Voice Using a Neural Network-Based Algorithm: Deep Learning............................................................................................................................................... 278 Neeraja Koppula, MLR Institute of Technology, India K. Sarada, KLEF, India Ibrahim Patel, B. V. Raju Institute of Technology, India R. Aamani, Vignan’s Institute of Information Technology, India K. Saikumar, Mallareddy University, India This chapter explains the speech signal in moving objects depending on the recognition field by retrieving the name of individual voice speech and speaker personality. The adequacy of precisely distinguishing a speaker is centred exclusively on vocal features, as voice contact with machines is getting more pervasive in errands like phone, banking exchanges, and the change of information from discourse data sets. This audit shows the location of text-subordinate speakers, which distinguishes a solitary speaker from a known populace. The highlights are eliminated; the discourse signal is enrolled for six speakers. Extraction of the capacity is accomplished utilizing LPC coefficients, AMDF computation, and DFT. By adding certain highlights as information, the neural organization is prepared. For additional correlation, the attributes are put away in models. The qualities that should be characterized for the speakers were acquired and dissected utilizing back propagation algorithm to a format picture. Chapter 20 Traditional and Innovative Approaches for Detecting Hazardous Liquids.......................................... 290 Ebru Efeoglu, Istanbul Gedik University, Turkey Gurkan Tuna, Trakya University, Turkey In this chapter, traditional and innovative approaches used in hazardous liquid detection are reviewed, and a novel approach for the detection of hazardous liquids is presented. The proposed system is based on electromagnetic response measurements of liquids in the microwave frequency band. Thanks to this technique, liquid classification can be made quickly without pouring the liquid from its bottle and without opening the lid of its bottle. The system can detect solutions with hazardous liquid concentrations of 70% or more, as well as pure hazardous liquids. Since it relies on machine learning methods and the success of all machine learning methods depends on provided data type and dataset, a performance evaluation study has been carried out to find the most suitable method. In the performance evaluation study naive Bayes and sequential minimal optimization has been evaluated, and the results have shown that naive Bayes is more suitable for liquid classification.
- 29. Chapter 21 Sentiment Analysis of Tweets on the COVID-19 Pandemic Using Machine Learning Techniques... 310 Jothikumar R., Shadan College of Engineering and Technology, India Vijay Anand R., Velloe Institute of Technology, India Visu P., Velammal Enginerring College, India Kumar R., National Institute of Technology, Nagaland, India Susi S., Shadan Women’s College of Engineering and Technology, India Kumar K. R., Adhiyamaan College of Engineering, India Sentiment evaluation alludes to separate the sentiments from the characteristic language and to perceive the mentality about the exact theme. Novel corona infection, a harmful malady ailment, is spreading out of the blue through the quarter, which thought processes respiratory tract diseases that can change from gentle to extraordinary levels. Because of its quick nature of spreading and no conceived cure, it ushered in a vibe of stress and pressure. In this chapter, a framework perusing principally based procedure is utilized to discover the musings of the tweets related to COVID and its effect lockdown. The chapter examines the tweets identified with the hash tags of crown infection and lockdown. The tweets were marked fabulous, negative, or fair, and a posting of classifiers has been utilized to investigate the precision and execution. The classifiers utilized have been under the four models which incorporate decision tree, regression, helpful asset vector framework, and naïve Bayes forms. Chapter 22 Intelligent Medical Data Analytics Using Classifiers and Clusters in Machine Learning. .................. 321 Muthukumaran V., REVA University, India Satheesh Kumar S., REVA University, India Rose Bindu Joseph, Christ Academy Institute for Advance Studies, India Vinoth Kumar V., MVJ College of Engineering, India Akshay K. Uday, Dr. M. G. R. Educational and Research Institute, India A privacy-preserving patient-centric clinical decision support system, called PPCD, is based on naive Bayesian classification to help the physician predict disease risks of patients in a privacy-preserving way. First, the authors propose a secure PPCD, which allows the service providers to diagnose a patient’s disease without leaking any patient medical data. In PPCD, the past patient’s historical medical data can be used by a service provider to train the naive Bayesian classifier. Then, the service provider can use the trained classifier to diagnose a patient’s diseases according to his symptoms in a privacy-preserving way. Finally, patients can retrieve the diagnosed results according to their own preference privately without compromising the service provider’s privacy. Chapter 23 Machine Learning for Industrial IoT Systems..................................................................................... 336 Mona Bakri Hassan, Sudan University of Science and Technology, Sudan Elmustafa Sayed Ali Ahmed, Sudan University of Science and Technology, Sudan Red Sea University, Sudan Rashid A. Saeed, Sudan University of Science and Technology, Sudan Taif University, Saudi Arabia The use of AI algorithms in the IoT enhances the ability to analyse big data and various platforms for a number of IoT applications, including industrial applications. AI provides unique solutions in support
- 30. of managing each of the different types of data for the IoT in terms of identification, classification, and decision making. In industrial IoT (IIoT), sensors, and other intelligence can be added to new or existing plants in order to monitor exterior parameters like energy consumption and other industrial parameters levels. In addition, smart devices designed as factory robots, specialized decision-making systems, and other online auxiliary systems are used in the industries IoT. Industrial IoT systems need smart operations management methods. The use of machine learning achieves methods that analyse big data developed for decision-making purposes. Machine learning drives efficient and effective decision making, particularly in the field of data flow and real-time analytics associated with advanced industrial computing networks. Chapter 24 A Research on Software Engineering Research in Machine Learning................................................ 359 Komali Dammalapati, Koneru Lakshmaiah Education Foundation, India B. Sankara Babu, Gokaraju Rangaraju Institute of Engineering and Technology, India P. Gopala Krishna, Gokaraju Rangaraju Institute of Engineering and Technology, India V. Subba Ramaiah, Mahatma Gandhi Institute of Technology, India With rapid growth of various well-known methods implemented by the engineers in the software field in order to create a development in automated tasks for manufacturers and researchers working worldwide, the researchers in the field of software engineering (SE) root for concepts of machine learning (ML), a subfield that utilizes deep learning (DL) for the development of such SE tasks. In essence, these systems would highly cope with the featured automation with inbuilt capabilities in engineering to develop the software simulation models. Nevertheless, it is very tough to condense the present scenario in research of situations that necessitate failures, successes, and openings in DL for software-based technology. The survey works for renowned technology of SE and DL held for the latest journals and conferences leading to the span of 85 issued papers throughout 23 distinctive tasks for SE. Chapter 25 Intelligent Speech Processing Technique for Suspicious Voice Call Identification Using Adaptive Machine Learning Approach............................................................................................................... 372 Dhilip Kumar, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India Swathi P., Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India Ayesha Jahangir, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India Nitesh Kumar Sah, Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India Vinothkumar V., MVJ College of Engineering, India With recent advances in the field of data, there are many advantages of speedy growth of internet and mobile phones in the society, and people are taking full advantage of them. On the other hand, there are a lot of fraudulent happenings everyday by stealing the personal information/credentials through spam calls. Unknowingly, we provide such confidential information to the untrusted callers. Existing applications for detecting such calls give alert as spam to all the unsaved numbers. But all calls might not be spam. To detect and identify such spam calls and telecommunication frauds, the authors developed the application for suspicious call identification using intelligent speech processing. When an incoming call is answered, the application will dynamically analyze the contents of the call in order to identify
- 31. frauds. This system alerts such suspicious calls to the user by detecting the keywords from the speech by comparing the words from the pre-defined data set provided to the software by using intelligent algorithms and natural language processing. Chapter 26 Image Captioning Using Deep Learning............................................................................................. 381 Bhavana D., Koneru Lakshmaiah Education Foundation, India K. Chaitanya Krishna, Koneru Lakshmaiah Education Foundation, India Tejaswini K., Koneru Lakshmaiah Education Foundation, India N. Venkata Vikas, Koneru Lakshmaiah Education Foundation, India A. N. V. Sahithya, Koneru Lakshmaiah Education Foundation, India The task of image caption generator is mainly about extracting the features and ongoings of an image and generating human-readable captions that translate the features of the objects in the image. The contents of an image can be described by having knowledge about natural language processing and computer vision. The features can be extracted using convolution neural networks which makes use of transfer learning to implement the exception model. It stands for extreme inception, which has a feature extraction base with 36 convolution layers. This shows accurate results when compared with the other CNNs. Recurrent neural networks are used for describing the image and to generate accurate sentences. The feature vector that is extracted by using the CNN is fed to the LSTM. The Flicker 8k dataset is used to train the network in which the data is labeled properly. The model will be able to generate accurate captions that nearly describe the activities carried in the image when an input image is given to it. Further, the authors use the BLEU scores to validate the model. Chapter 27 Leveraging Big Data Analytics and Hadoop in Developing India’s Healthcare Services................... 396 Koppula Srinivas Rao, MLR Institute of Technology, India Saravanan S., B. V. Raju Institute of Technology, India Pattem Sampath Kumar, Malla Reddy Institute of Engineering and Technology, India Rajesh V., Department of Electronics and Communication Engineering, Koneru Lakshmaiah Educational Foundation, India K. Raghu, Mahatma Gandhi Institute of Technology, India The benefits of data analytics and Hadoop in application areas where vast volumes of data move in and out are examined and exposed in this report. Developing countries with large populations, such as India, face several challenges in the field of healthcare, including rising costs, addressing the needs of economically disadvantaged people, gaining access to hospitals, and conducting medical research, especially during epidemics. This chapter discusses the role of big data analytics and Hadoop, as well as their effect on providing healthcare services to all at the lowest possible cost.
- 32. Chapter 28 A Sequential Data Mining Technique for Identification of Fault Zone Using FACTS-Based Transmission........................................................................................................................................ 408 Koppula Srinivas Rao, MLR Institute of Technology, India B. Veerasekhar Reddy, MLR Institute of Technology, India Sarada K., Koneru Lakshmaiah Education Foundation, India Saikumar K., Malla Reddy Institute of Technology, India Inthissurvey,theissueofflawzoneidentificationofseparationtransferringin“FACTS-basedtransmission lines” is investigated. Presence of FACTS gadgets on transmission line (TL), while they have been remembered for issue zone, from separation transfer perspective, causes various issues in deciding the specific area of the flaw by varying impedance perceived by hand-off. The degree of these progressions relies upon boundaries that are set in FACTS gadgets. To tackle issues related with these, two instruments for partition and examination of three-line flows, from the hand-off perspective to blame occasion, have been used. In addition, to examine the impacts of TCSC area on deficiency zone recognition of separation hand-off, two spots, one of every 50% of line length and the other in 75% of line length, are deliberated as two situations for affirmation of suggested strategy. Reproductions show that this strategy is powerful in security of FACTS-based TLs. Chapter 29 K-Means Clustering Machine Learning Concept to Enable Social Distancing in Public Places........ 420 Abdullah Saleh Alqahtani, CFY Deanship King Saud University, Saudi Arabia In endemic and pandemic situations, governments will implement social distancing to control the virus spread and control the affected and death rate of the country until the vaccine is introduced. For social distancing, people may forget in some public places for necessary needs. To avoid this situation, the authors develop the Android mobile application to notify the social distancing alert to people to avoid increased levels of the endemic and pandemic spread. This application works in both online and offline mode in the smart phones. This application helps the people to obey the government rule to overcome the endemic and pandemic situations. This application uses k-means clustering algorithms to cluster the data and form the more safety clusters for social distancing. It uses artificial intelligence to track the living location by the mobile camera without the internet facilities. It helps the user to follow social distancing even with no internet with user knowledge. Chapter 30 An Efficient Selfishness Control Mechanism for Mobile Ad hoc Networks....................................... 432 D. Rajalakshmi, Sri Sairam Institute of Technology, India Meena K., Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology, India AMANET(mobileadhocnetwork)isaself-organizedwirelessnetwork.Thisnetworkismorevulnerable to security failure due to dynamic topology, infrastructure-less environment, and energy consumption. Based on this security issue, routing in MANET is very difficult in real time. In these kinds of networks, the mobility and resource constraints could lead to divide the networks and minimize the performance of the entire network. In real time it is not possible because some selfish nodes interacts with other nodes partially or may not share the data entirely. These kind of malicious or selfish nodes degrade the network performance. In this chapter, the authors proposed and implemented the effect of malicious activities
- 33. in a MANETs using self-centered friendship tree routing. It’s a novel replica model motivated by the social relationship. Using this technique, it detects the malicious nodes and prevents hacking issues in routing protocol in future routes. Chapter 31 Estimation of Secured Wireless Sensor Networks and Its Significant Observation for Improving Energy Efficiency Using Cross-Learning Algorithms......................................................................... 450 Sirasani Srinivasa Rao, Mahatma Gandhi Institute of Technology, India K. Butchi Raju, GRIET, India Sunanda Nalajala, Koneru Lakshmaiah Education Foundation, India Ramesh Vatambeti, CHRIST University (Deemed), India Wireless sensor networks (WSNs) have as of late been created as a stage for various significant observation and control applications. WSNs are continuously utilized in different applications, for example, therapeutic, military, and mechanical segments. Since the WSN is helpless against assaults, refined security administrations are required for verifying the information correspondence between hubs. Because of the asset limitations, the symmetric key foundation is considered as the ideal worldview for verifying the key trade in WSN. The sensor hubs in the WSN course gathered data to the base station. Despite the fact that the specially appointed system is adaptable with the variable foundation, they are exposed to different security dangers. Grouping is a successful way to deal with vitality productivity in the system. In bunching, information accumulation is utilized to diminish the measure of information that streams in the system. Chapter 32 Executing CNN-LSTM Algorithm for Recognizable Proof of Cervical Spondylosis Infection on Spinal Cord MRI Image: Machine Learning Image............................................................................ 468 Sasank V. V. S., Koneru Lakshmaiah Education Foundation, India Kranthi Kumar Singamaneni, Gokaraju Rangaraju Institute of Engineering and Technology, India A. Sampath Dakshina Murthy, Vignan’s Institute of Information Technology, India S. K. Hasane Ahammad, Koneru Lakshmaiah Education Foundation, India Various estimating mechanisms are present for evaluating the regional agony, neck torment, neurologic deficiencies of the sphincters at the stage midlevel of cervical spondylosis. It is necessary for the cervical spondylosisthatthesurveynecessitateswiderangeoflearningskillsaboutthesystemizedlife,experience, and ability of the expertise for learning the capability, life system, and experience. Doctors check the analysis of situation through MRI and CT scan, but additional interesting facts have been discovered in the physical test. For this, a programming approach is not available. The authors thereby propose a novel framework that accordingly inspects and investigates the cervical spondylosis employing computation of CNN-LSTM. Machine learning methods such as long short-term memory (LSTM) in fusion with convolution neural networks (CNNs), a kind of neural network (NN), are applied to this strategy to evaluate for making the systematization in various applications.
- 34. Chapter 33 Soil Nutrients and pH Level Testing Using Multivariate Statistical Techniques for Crop Selection.. 485 Swapna B., Dr. M. G. R. Educational and Research Institute, India S. Manivannan, Dr. M. G. R. Educational and Research Institute, India M. Kamalahasan, Dr. M. G. R. Educational and Research Institute, India The multivariate data analysis technique is used to determine the highly impacted data in soil and crop growth. The importance and relationship between soil variables were factored by using the regression analysistechnique.Thecorrelationmatrixtechniquewasusedforcomparingseveralvariablestocorrelate positive and negative signs. From the soil testing procedure and understanding of results, it shows that soil nutrients and pH level have a powerful effect on variation in the usage of fertilizers, crop selection, and high crop yield. pH determination can be used to indicate whether the soil is suitable for the plant’s growth or in need of adjustment to produce optimum plant growth. Based upon the predictive analysis results, nitrogen and potassium content are naturally high compared to other soil nutrients of this region and suggested fertilizers required for crop growth. To produce healthy crop yield, farmers should select the crops as per soil types, nutrients level, and pH level. Compilation of References................................................................................................................ 499 About the Contributors..................................................................................................................... 552 Index.................................................................................................................................................... 567
- 35. Preface Recently,artificialintelligence(AI),InternetofThings(IoT)andcognitivetechnologieshavesuccessfully been applied to various research domains, including computer vision, natural language processing, voice recognition, etc. In addition, AI with IoT has made a significant breakthrough and technical direction in achieving high efficiency and adaptability in a variety of new applications, such as smart wearable devices in healthcare, smart automotive industry, recommender systems, and financial analysis. On the otherhand,networkdesignandoptimizationforAIapplicationsaddressesacomplementingtopic,namely the support of AI-based systems through novel networking techniques, including new architectures as well as performance models for IoT systems. IoT has paved the way to a plethora of new application domains, at the same time posing several challenges as a multitude of devices, protocols, communication channels, architectures and middleware exist. In particular, we are witnessing an incremental develop- ment of interconnections between devices (e.g., smartphones, tablets, smart watches, fitness trackers, and wearable devices in general, smart TVs, home appliances and much more like this), people, processes, and data. Big data generated by these devices calls for advanced learning and data mining techniques to effectively understand, learn, and reason with this volume of information, such as cognitive technologies. Cognitive technologies play a major role in developing successful cognitive systems which mimic “cognitive” functions associated with human intelligence, such as “learning” and “problem solving”. Thus,thereisacontinuing demandforrecentresearchin thesetwolinkedfields.Nowadays,this cognitive technologieslikeNeuralNetworks,Deeplearning,Reinforcementlearning,FuzzySystems,Evolutionary Computation,Bio-inspiredcomputingparadigms,Quantum-inspiredEvolutionaryAlgorithm,Cognitive- inspired computing systems, Brain analysis for cognitive computing, Internet cognitive of things, Cogni- tive agents are combined with AI and IoT for many innovative applications and system developments. This Handbook of Research of Innovations and Applications of AI, IoT, and Cognitive Technologies discusses the latest innovations and applications of AI, IoT, and cognitive-based smart systems. The chapters cover the intersection of these three fields in emerging and developed economies in terms of their respective development situation, public policies, technologies and intellectual capital, innovation systems, competition and strategies, marketing and growth capability, and governance and relegation models. These applications span areas such as healthcare, security and privacy, industrial systems, multidisciplinary sciences, and more. This book is ideal for technologists, IT specialists, policymakers, government officials, academics, students, and practitioners interested in the experiences of innovations and applications of AI, IoT, and cognitive technologies. xxx
- 36. Preface ORGANIZATION OF THE BOOK This book has been divided into two sections: Section 1, “AI and IoT: A Blend in Future Technologies and Systems,” introduces emerging AI and IoT technologies and systems, as well as their innovations and applications that are responsible for the digitization of all the sectors through automation and together rules the technological aspects of our lives. Section 1 is organized into 18 chapters. A synopsis of each chapter is given below. Chapter1(AlgorithmsOptimizationforIntelligentIoVApplications)introducesdifferentoptimization algorithms i.e. clustering algorithms, Ant colony optimization, Best Interface Selection (BIS) Algorithm, Mobility adaptive density connected clustering algorithm, Meta-Heuristics Algorithms and Quality of Service (QoS) based optimization. These algorithms provide an important intelligent role to optimize the operation of IoV networks and promise to develop new intelligent IoV applications. Chapter2(CooperativeRelayingCommunicationinIoTApplicationsfor5GRadioNetworks)presents cooperative relaying networks that are helpful in Internet of Thing (IoT) applications for fifth generation (5G) radio networks. The design of advanced protocols plays an important role to combat the effect of channel fading, data packet scheduling at the buffered relay, average delay, and traffic intensity. Chapter 3 (The Rise of IoT and Big Data Analytics for Disaster Management System) explains the reason why IoT and Big Data are needed to cope with disasters, as well as how these technologies work to solve the problem. The developments in Big Data and the Internet of Things (IoT) have made a greater contribution to accuracy and timely decision-making in the Disaster Management System (DMS). Chapter 4 (IoT-Based Smart Agriculture) explores the current state of advanced farm management systems by revisiting each critical phase, from data collection in crop fields to variable rate applications, in order for growers to make informed decisions save money while also protecting the environment and transforming how food is grown to meet potential population growth. Chapter 5 (Mobile Geo-Fencing Triggers for Alerting Entries Into COVID-19 Containment Zones Using IoT) discusses a Containment Zone alert system by means of Geo-fencing technology to identify the movement of public, deliver info about the danger to the public in travel and also send an alert to the police when there is an entry or exit detected in the containment zone by the use of Location-Based Services (LBS). Chapter 6 (Fine Tuning Smart Manufacturing Enterprise System: A Perspective of Internet of Things- Based Service-Oriented Architecture) proposes the integration of standard workflow model between business system level and manufacturing production level with IoT-enabled SOA framework. Chapter 7 (A Quantum Technology-Based LiFi Security Using Quantum Key Distribution) discusses Wireless Fidelity (Wi-Fi) and focuses on some drawbacks that include speed and bandwidth limit, security issues, and attacks by malicious users, which yield Wi-Fi as less reliable as compared to LiFi. Chapter 8 (Role of Artificial Intelligence of Things [AIoT] to Combat Pandemic COVID-19) studies on AIoT entails AI through machine learning and decision making to IoT; and renovates IoT to add data exchange and analytics to AI. Through this chapter, AIoT will serve as potential analytical tool to fight against the pandemic. Chapter 9 (Recent Trends in Wearable Device Technology for Health State Monitoring) proposes that the main function of wearable devices is said to be collecting the user personal health data. Eg: such devices include measurement on fitness of body, heart beat measurement, ECG Measurement, blood pressure monitoring etc. xxxi
- 37. Preface Chapter 10 (IoT-Based Delineate and Evolution of Kid’s Safety Portable Device) presents those numerous portables in the retail which assist track the day by day action of kids and furthermore help discover the kid utilizing Wi-Fi and Bluetooth directions available on the gadget. Chapter 11 (Blockchain-Enabled Internet of Things for Unsupervised Structural Health Monitoring in Potential Building Structures) proposes a solution that contemplates the architecture of smart sen- sors, customized for individual structures, to regulate the monitoring of structural health through stress, strain and bolted joints looseness. Chapter 12 (An Advanced Wireless Sensor Networks Design for Energy Efficient Applications Us- ing Condition Based Access Protocol) states that, in this investigation WSN networks maintenance is balanced through Condition Based Access (CBA) protocol. The CBA most useful for real time 4G and 5G communication to handle internet assistance devices. Chapter 13 (Effective Image Fusion of PET-MRI Brain Images Using Wavelet Transforms and Neural Networks) proposed approach is segment and identify brain tumor in automatic manner using image fusion with neural network concepts. Segmentation of brain images is needed to segment properly from other brain tissues. Chapter 14 (IoT-Enabled Non-Contact-Based Infrared Thermometer for Temperature Recording of a Person) states that the LET data collection must be stored to influence the quality of the results and to ensure the stability of the laboratory environment. Hence an IoT solution is presented to supervise real time temperature and is known as iRT. Chapter 15 (Predictive Modeling for Classification of Breast Cancer Dataset Using Feature Selection Techniques) conducts to classify the breast cancer patients into either the recurrence or non recurrence category. It is identified that the Mutual Information technique proved to be more efficient and produced higher accuracy in the predictions. Chapter 16 (Credit Card Fraud Detection Using K-Means and Fuzzy C-Means) states that the CFD system is developed using Fuzzy C-Means (FCM) clustering instead of K-means clustering. Performance of CFD using both clustering techniques is compared using precision, recall and F-measure. The FCM gives better results in comparison to K-means clustering. Chapter 17 (A Hybrid Method to Reduce PAPR of OFDM to Support 5G Technology) discusses Well- known systems like ADSL (asymmetric digital subscriber line) internet, wireless local area networks (LANs), Long term Evolution (LTE), and 5G technologies use OFDM. Chapter 18 (Restricted Boltzmann Machine-Driven Matchmaking Algorithm With Interactive Esti- mation of Distribution for Websites) presents that an interactive evolutionary algorithm with powerful evolutionary strategies is a good choice for matchmaking, in which the RBM model is combined with social group knowledge. Some benchmarks from the matrimonial internet site are pragmatic to empiri- cally reveal the pre-eminence of the anticipated method. Section 2, “Big Data and Cognitive Technologies: Current Applications and Future Challenges” provides insights on learning based on big data and cognitive computing technologies, including cutting edge topics (e.g., machine learning for industrial IoT systems, deep learning, reinforced learning and decision trees for IoT systems, computational intelligence and cognitive systems, cognitive learning for IoT systems, cognitive-inspired computing systems). Section 2 is organized into 17 chapters. A synopsis of each chapter is given below. Chapter19(IdentificationandRecognitionofSpeakerVoiceUsingNeuralNetwork-BasedAlgorithm: Deep Learning) explains about the speech signal in moving objects depending on the recognition field by retrieving the name of individual voice speech and speaker personality. xxxii
- 38. Preface Chapter 20 (Traditional and Innovative Approaches for Detecting Hazardous Liquids) presents tradi- tional and innovative approaches used in hazardous liquid detection are reviewed and a novel approach for the detection of hazardous liquids. The proposed innovative system is based on electromagnetic response measurements of liquids in the microwave frequency band. Chapter21(COVID-19AnalysisofSentimentTweetsonPandemicUsingMachineLearningTechniques) gathers the tweets identified with the hash tags of crown infection and lock down, pre-framework them and was examined. The tweets had been marked fabulous, negative or fair and a posting of classifiers had been utilized to investigate the precision and execution. The classifiers utilized had been under the four models which incorporates decision Tree, Regression, helpful asset Vector framework and Naïve Bayes form. Chapter 22 (Intelligence Medical Data Analytics Using Classifiers and Clusters in Machine Learn- ing) proposes a secure and PPCD, which allows the service providers to diagnose a patient’s disease without leaking any patient’s medical data. Patients can retrieve the diagnosed results according to their own preference privately without compromising the service provider’s privacy. Chapter 23 (Machine Learning for Industrial IoT Systems) states that the new model of industrial IoT (IIoT), sensors and other intelligence are added to new or existing plants to monitor exterior parameters such like energy consumption and other industrial parameters levels. In addition, smart devices designed as factory robots, specialized decision-making systems, and other online auxiliary systems are used in the industries IoT. Chapter 24 (A Research on Software Engineering Research in Machine Learning: Machine Learn- ing) proposes that the researchers in the field of software engineering (SE) root for concepts of machine learning (ML), a sub field in which utilizing the deep learning (DL)for the development of such SE tasks. Chapter 25 (Intelligent Speech Processing Technique for Suspicious Voice Call Identification Using Adaptive Machine Learning Approach) develops the application for suspicious call identification using intelligent speech processing. When an incoming call is answered, the application will dynamically analyze the contents of the call in order to identify frauds. Chapter 26 (Image Captioning Using Deep Learning) designs a model that is able to generate ac- curate captions that nearly describe the activities carried in the image when an input image is given to it. Further, the BLEU scores can be used to validate the model. Chapter 27 (Leveraging Big Data Analytics and Hadoop in Developing India’s Healthcare Services) discusses the role of Big Data Analytics and Hadoop, as well as their effect on providing healthcare services to all at the lowest possible cost. Chapter 28 (A Sequential Data Mining Technique for Identification of Fault Zone Using Facts-Based Transmission) investigates the issue of flaw zone identification of separation transferring in “FACTS- based transmission lines”. Chapter 29 (K-Means Clustering Machine Learning Concept to Enable Social Distancing in Public Places)studies onutilizing artificialintelligence totrackthelivinglocationby themobilecamerawithout the internet facilities and it helps users to follow the social distancing. Chapter 30 (An Efficient Selfishness Control Mechanism for Mobile Ad Hoc Networks) introduces a novel replica model, motivated by the social relationship. Using this technique, it detects the malicious nodes and prevent the hacking issues in routing protocol in future routes. Chapter 31 (Estimation of Secured Wireless Sensor Networks and Its Significant Observation for Improving Energy Efficiency Using Cross-Learning Algorithm) presents Wireless Sensor Networks (WSNs) are helpless against assaults, refined security administrations that are required for verifying xxxiii
- 39. Preface the information correspondence between hubs. Grouping is a successful way to deal with accomplishes vitality productivity in the system. In bunching, information accumulation is utilized to diminish the measure of information that streams in the system. Chapter 32 (Executing CNN-LSTM Algorithm for Recognizable Proof of Cervical Spondylosis Infec- tion on Spinal Cord MRI Image: Machine Learning Image) proposes that machine learning methods such as Long Short-Term Memory (LSTM) in fusion with Convolution Neural Networks (CNNs), a kind of neural network (NN) are applied to this strategy to evaluate for making the systematization in various applications. Chapter 33 (Soil Nutrients and Ph Level Testing Using Multivariate Statistical Techniques for Crop Selection) explains that the importance and relationship between soil variables are factorized by using the Regression analysis technique. Jingyuan Zhao University of Toronto, Canada V. Vinoth Kumar MVJ College of Engineering, India 2021 June xxxiv
- 40. Section 1 Section 1 introduces emerging AI and IoT technologies and systems, as well as their innovations and applications that are responsible for the digitization of all the sectors through automation and together rules the technological aspects of our lives. Section 1 is organized into 18 chapters. AI and IoT: A Blend in Future Technologies and Systems
- 41. 1 Copyright © 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 1 DOI: 10.4018/978-1-7998-6870-5.ch001 ABSTRACT Internet of vehicles (IoV) has recently become an emerging promising field of research due to the in- creasing number of vehicles each day. It is a part of the internet of things (IoT) which deals with vehicle communications. As vehicular nodes are considered always in motion, they cause frequent changes in the network topology. These changes cause issues in IoV such as scalability, dynamic topology changes, and shortest path for routing. In this chapter, the authors will discuss different optimization algorithms (i.e., clustering algorithms, ant colony optimization, best interface selection [BIS] algorithm, mobility adaptive density connected clustering algorithm, meta-heuristics algorithms, and quality of service [QoS]-based optimization). These algorithms provide an important intelligent role to optimize the op- eration of IoV networks and promise to develop new intelligent IoV applications. Algorithms Optimization for Intelligent IoV Applications Elmustafa Sayed Ali Ahmed https://orcid.org/0000-0003-4738-3216 Sudan University of Science and Technology, Sudan Red Sea University, Sudan Zahraa Tagelsir Mohammed Red Sea University, Sudan Mona Bakri Hassan Sudan University of Science and Technology, Sudan Rashid A. Saeed https://orcid.org/0000-0002-9872-081X Sudan University of Science and Technology, Sudan Taif University, Saudi Arabia
- 42. 2 Algorithms Optimization for Intelligent IoV Applications INTRODUCTION Recently, Internet of vehicles (IoV) has become an emerging promising field of research due to the increasing number of vehicles each day. It is a branch of the internet of things (IoT) which deal with communication among vehicles (Mahmoud et al, 2012). IoV enables vehicles to send information among vehicles,roadinfrastructures,passengers,drivers,sensorsandelectricactuatorsthroughdifferentcommu- nicationmediaincludingIEEE802.11p,vehicularcooperativemediaaccesscontrol(VC-MAC),dynamic source routing (DSR), Ad hoc on demand distance vector (AODV), directional medium access control (DMAC) and general packet radio services (GPRS) (Amal et al, 2016). As know, that vehicular nodes are always in motion that causes the frequent changes in the network topology (Mahmoud et al,2014). These changes cause issues in IoV as scalability, dynamic topology changes and shortest path for routing. The design of an effective application is a major challenge that should not be neglected in IoV, considering their special features and characteristics, such as high vehicle mobility and quick topology changes, which make the design and implementation of effective solutions for such networks a difficult task (Mayada et al,2018) (Nahla et al,2021). First, high mobility is the main factor distinguishing IoV from other networks. Vehicle speed varies according to road conditions and may be low or medium in urban areas and large on highways (Amal et al,2018). This speed variation has a direct impact on network stability and results in a dynamic network topology. Secondly, node density is not uniform but exhibits spatiotemporal variation. Typically, the density in urban areas is higher than in rural areas and depends on the time of day. Finally, network fragmentation generally occurs when vehicle density is low and irregular. Then, the vehicles move in disconnected isolated clusters, and therefore, end-to-end communication becomes difficult. Generally, the focus on optimization in IoV applications is related to the importance of traffic ac- curacy and protection of information and entertainment network, as well as ensuring road safety when deploying the IoVs applications. According to what has been mentioned, IoV applications face a number of problems related to the reliability and consistency in the exchange of information between the vehicles and the appropriate decision-making to improve safety on the road (Mayada et al,2017). Artificial intel- ligence (AI) techniques provide appropriate and effective solutions to a number of the aforementioned problems, especially those related to decision-making in IoV systems. Recently, many studies have been presented that rely on the capabilities of AI and the use of its algorithms in various processes related to improving quality in IoV applications and services. Table 1 shows the summary of different optimiza- tion studies in IoV applications. (Farhan et al, 2018), presented a method for using the metaheuristic dragonfly-based clustering al- gorithm (CAVDO) to optimize cluster-based packet route to create a stable IoV topology in a dynamic environment. The study is presented on the basis that the mobility aware dynamic transmission range algorithm (MA-DTR) algorithm is used with CAVDO to adapt the transmission range based on traffic density. A comparison of the proposed algorithm was also made with other algorithm such as the Ant Colony Improvement (ACO) and learning particle swarm optimization (LPSO). Through the analysis, it was found that the proposed algorithm has much better performance than ACO and LPSO as it provides the minimum number of clusters according to the current channel conditions, as it improves network availability and integrates the functions of the network infrastructure. The study presented by (Ali et al, 2019), reviews two algorithms known as Energy Perceived QoE Optimization (PQO) and Store Perceived QoE Improvement (BQO) as their performance was compared, in addition to proposing a multimedia communication mechanism based on the two algorithms. Also,
- 43. 3 Algorithms Optimization for Intelligent IoV Applications the researchers demonstrated a framework that improves QoE during IoV multimedia communication throughmobiledevices.Throughtheanalysis,itwasfoundthattheproposedalgorithmsgiveasignificant improvement in QoE, as they greatly assist in enabling applications during multimedia communication. In the study presented by (Hongjing et al,2020) the potential of both MEC and AI in IoV applications and the possibility of combining them in a specific structure and topology are reviewed. The researchers analysed the application of MEC and AI in IoV and compared it with current approaches. The analysis shows that the MEC with AI will gives higher location awareness in addition to higher scalability. (Xi- antao et al, 2020) studied the analysis of video applications on the IoV using multiple access computing (MEC) technology and integrating it with the blockchain i to improve transaction throughput as well as reduce MEC system latency. Researchers relied on the Markov decision process (MDP) and asynchro- nous critic-critic (A3C) algorithm to model the improvement problem. Through the analysis, the results showed that the proposed approach could rapidly converge and significantly improve the performance of the blockchain-powered IoV. (Quoc et al, 2020), presented an overview of swarm intelligence(SI) technologies and their impact in the optimization process. The researchers covered the use of SI in spectrum management, resource allocation, wireless buffering, advanced computing and network security. in addition, they review the future challenges facing the optimization in many IoV aspects such as plectrum management and re- source allocation for IoV based on 5G. In the study presented by (Ghassan et al,2020) a mechanism known as Whale Optimization Algorithm is used to improve the select optimum cluster head for vehicle communication according to two criteria: intelligence and capacity. Through the analysis, it was found that the proposed algorithm gave better results in finding optimum cluster compared to other traditional algorithms, as it gave an improvement in cluster optimization by 46%. (Kayarga et al,2021), review the challenges facing the IoV deployment in addition to the reliability and consistently of messages between vehicles that enables drivers to make appropriate decisions to improve road safety. Where the authors presented a review of the methods proposed from a number of previous studies that present a new approach to determine the mechanism used to identify and route the vehicular node for the IoV environment. (elmustafa et al,2021), presented theories and general founda- tions for the use of machine learning and models of some algorithms in IoV applications, where they conducted a critical review with an analytical model of mobile edge computing decisions based on machine learning and a deep augmented learning (DRL) approaches. The study adopted the IoV secure edge computing unloading model with different data processing and traffic flow by taking an analytical model of Markov decision process (MDP) and ML in unpacking the decision process of the different task streams of the IoV network control cycle. The researchers also analysed the mechanisms of buffer and perceived energy in improving the quality of the experiment (QoE) enabled by ML. Considering all issues disused in the previous studies, as new techniques and mechanisms have been studied to ensure a stable network topology structure as well as effective data routing and dissemination. This chapter provides a brief concept about algorithms optimization in mentioned issues related to the IoV applications. The chapter describes the background of Internet of Vehicles, in addition to the use of Artificial Intelligence in IoV. The clustering algorithms in IoV are reviewed in this chapter by explain- ing the concept of clustering and how it is used to optimize IoV networks, it also describes some of the most important clustering algorithms used for IoV; Dragonfly-based clustering algorithm for IoV, Moth Flame Clustering Algorithm and Mobility adaptive density connected clustering algorithm. The chapter also focuses in three types of Swarm-Intelligence (SI) Algorithms which is inspired from the life of some swarms such as ants, bees and Cookoo Bird. In addition, the concept of Meta-Heuristics
- 44. 4 Algorithms Optimization for Intelligent IoV Applications algorithms and the Best Interface Selection (BIS) algorithm with their classifications in IoV are also discussed. Moreover, the chapter explains the Distributed Multichannel and Mobility-Aware Cluster- Based MAC Protocol. Chapter also describes the importance of considering Quality of Service with the Optimization Algorithms in IoV System, and the optimization problem in IoV clustering. Finally, the chapter presented the future research directions that should be followed to enhance the process of optimizing IoV networks, and summarizes the optimization and IoV. IOV APPLICATIONS BACKRGOUND The new era of the IoT is driving the development of Vehicle Ad-hoc Networks into the IoV. VANET is recognized from mobile ad hoc network (MANET). VANET technology is interfaced in vehicle-to- vehicle (V2V) and vehicle to roadside (V2R) communications technology to send data among vehicles. IoV is a new version of IoT used to enable communication among vehicles, things and environments to send information among IoV networks (yang et al, 2014) (Amal et al,2013). In other words, IoV is a combination of inter-vehicle network, an intra-vehicle network and vehicular mobile internet in urban environment. It improves VANET features and reduces traffic issues in urban traffic environment. IoV is technology that concerned on travel plan and network access for passengers, drivers and indi- viduals who are working in the traffic management department. The major applications of vehicles and road network (IoV) including smart traffic monitoring, self-drive cars and smart parking system (Mayada et al,2020). IoV allows managing traffic, developing intelligent dynamic information communication Table 1. Summary of Algorithms Optimization Studies on IoV Applications Approach Feature Advantages Citations Metaheuristic dragonfly-based clustering algorithm Optimize cluster based packet route in IoV dynamic environment Minimum number of clusters and improving in network availability Farhan et al, 2018 Energy perceived QoE optimization Store perceived QoE improvement algorithms QoS for multimedia communication mechanism in IoV Improved QoS multimedia communication through IoV mobile devices Ali et al, 2019 MEC based AI algorithm Combination of MEC and AI in IoV applications Higher location awareness in addition to higher scalability Hongjing et al,2020 Markov decision process (MDP) and asynchronous critic-critic (A3C) algorithm Video services on IoV using multiple access computing (MEC) with blockchain Reduce MEC system latency and improve the performance of the blockchain-powered IoV Xiantao et al, 2020 Swarm intelligence (SI) technology Impact of SI in IoV spectrum management, resource allocation, and network security Possible improvements in management and resource allocation for IoV based on 5G Quoc et al, 2020 Whale Optimization Algorithm Optimal Cluster head selection in IoVs communication Improvement in cluster optimization by 46%. Compared with traditional algorithms Ghassan et al,2020 Intelligent decision making for IoV application Road safety and route optimization in IoV Improved methods to identify and route the vehicular node for the IoV environment Kayarga et al,2021 Mobile edge computing decisions based on machine learning Secure edge computing unloading model with different data processing and traffic flow in IoV improving the quality of the experiment (QoE) enabled by ML elmustafa et al,2021
- 45. 5 Algorithms Optimization for Intelligent IoV Applications among vehicles, pollution and environmental protection, road safety management and energy manage- ment as well as road accident prevention (yang et al, 2014) (Priyan et al, 2019). As shown in figure 1, IoV connects humans within and around vehicles, intelligent systems on board vehicles and various cyber-physical systems in urban environments, by integrating sensors, actuator, vehicles and smart phones into a wide area network (WAN) which allows varied services to vehicles and humansonboardandaroundvehicles.Severalresearchersdefinedvehicleasamannedcomputerwithfour wheels or a manned large phone in IoV (yang et al, 2014). Thus, in contrast to other networks, existing multi-user, multi-vehicle, multi-thing and multi-network systems need multi-level collaboration in IoV. Figure 1. Internet-of-Vehicles (IoV)
- 46. 6 Algorithms Optimization for Intelligent IoV Applications RESEARCH METHODOLOGY The general aim of AI that has an ability machines integrate with human intelligence. ML is a method that using algorithms of AI techniques to analyse data, learn from data, and make a decisions and predic- tions for real-world events. In the next section research methodologies are discussed. Artificial Intelligence in IoV For realizing ML, it enables many applications and expands the scope of AI. Reinforcement learning (RL), also known as evaluation learning. It is a technique of ML. Deep reinforcement learning (DRL) is the combination of DL and RL techniques. It uses the benefits of deep neural networks (DNNs) to train the learning process, therefore the learning speed and performance of the RL algorithm and overcoming the unsuitability of RL for large-scale networks. Figure 2 shows relationship between ML, DL, RL and AI (Hongjing et al, 2020). AI integrated with IoT in automated vehicles (AV) to provide high-performance of embedded systems that used to allow more dynamic and robust control systems. While the main software components of AVs are traditionally host by cloud computing systems, new edge computing paradigm has addressed some technical challenges includes bandwidth, latency and security of networks (Mona et al,2021). Figure 2. The relationship between AI, ML, RL, DL and DRL
- 47. 7 Algorithms Optimization for Intelligent IoV Applications The amount of data is increase in AV which is used for advanced driver assistance dystems (ADAS) and entertainment (Hongjing et al, 2020). Hence, software and hardware have been required. Sensors, actuators devices and software are used to complete the purpose similar to the superhuman brain as aimed through AI. The AV brings new approach to industrial manufacturers and dealerships, enabling companies to implement AI to increase value for their customers. The most efficient approach for AI to process this data is to use ML algorithms. The ML algorithms help a specific driver profiles and vehicle owners exactly what they require in vehicle and through their mobile phones via a corresponding application. They accomplish this by remembering their behaviour and analysing their driving history and the situ- ation on the road (Hongjing et al, 2020). Even though AI can handle large data from vehicles with some of the extra data conditions including traffic, pedestrians, and experiences, will need to be collected via IoT networks as LAN, PAN, WSN and wide area network (WAN). This large amount data required some equipment such as sensors, vehicles, embedded electronics devices, software and network connectivity for allowing to gathering and sharing data among vehicles. These IoT-allowed AVs to integrate equipment to provide more safety reduce the fuel consumption and security. Figure 3. Architecture for AI based on IoV
- 48. 8 Algorithms Optimization for Intelligent IoV Applications AI has ability to enhance the cognition and IoV networks and thus assist in optimally allocating re- sources for problems with diverse, time-variant and complex features (Hongjing et al, 2020). As shown in figure3, the architecture of AI in IoV, where the agent observed its current environmental state, takes action and receives its immediate reward with the new state. The observed information includes imme- diate rewards and the new status which used to adjust the agent’s strategy and this process is repeated until the agent’s strategy approaches the optimal strategy. Clustering Algorithms in IoV As mentioned before, IoV is a new version of IoT which focus on communication among vehicles. Vehicular nodes are usually in motion with time it will lead frequent changes in the topology. These changes cause issues in IoV network include dynamic topology changes, shortest path for routing and scalability (Rashid et al,2010). Clustering is among one of the popular topologies to solve issues in IoV network. Logical grouping of nodes like in UAV’s, sensors, automobiles, ships, and etc. have a common topographical zone termed as clustering. Nodes can vary according to the applied problem; participating nodes are cluster members (CM). Node has two fundamental topology types they are Centralized topology is known as a central govern- ing node cluster head (CH) which responsible for intra-cluster and inter-cluster activities. And second type is De-centralized topology is considered as each group of the population consists of similar nodes having distributed control (Farhan et al, 2018). If control is centralized, then a cluster contains central governing node CH. Nodes can be connected with other by wireless networks (3G, 4G, and 5G). Nodes Figure 4. 5G-enabled VANET architecture
- 49. 9 Algorithms Optimization for Intelligent IoV Applications that connected with 5G network are more desirable CHs but not compulsory for enhanced management. Better CH selection/election is difficult in IoVs. V2Xcommunicationinheterogeneousnetworksisconsideredthearchitecturethatclarifies5Gallows using IoVs as well as it supports more benefits in term of bandwidth and availability of network resource (see figure 4). Also, 5G will enable new application scenarios such as parked cars and pedestrians. IoV issues including mobility, information broadcast and shortest path routing can be addressed more ef- ficiently in 5G-based scenarios (Farhan et al, 2018). The future scenario that CAVDO can be interfaced with other future networks technologies such as Li-Fi and beyond network technologies. Dragonfly-Based Clustering Algorithm for IoV Clustering is one of the solution issues for IoV due to motivation such as scalability, dynamic topology changes and shortest path for routing. The Meta heuristic dragonfly-based clustering algorithm CAVDO is used for cluster-based packet route optimization for stability of IoV topology in a dynamic environ- ment and mobility aware dynamic transmission range algorithm (MA-DTR) is used with CAVDO for transmission range adaptation on the basis of traffic density. Minimum number of clusters represents the shortest path in cluster-based routing (Farhan et al, 2018). To avoid broadcast overhead, CHs only are responsible to forward and exchange information between CMs and to other clusters. For efficient CHs selection/election, the unique swarming technique of dragonflies enable CAVDO and MA-DTR used to construct ideal clustering solution for IoV routing. In swarm-based techniques, a swarm is a set of solutions and each node defined as a single solution. A dragonfly algorithm represents a complete route containing CH IDs through which packet is travelled. Swarm-based approaches proved their working efficiency on both problemdomains: in discrete value problems and in continuous problems as well. Although in comparison, the implementation complexity is high, mostly applied to exhaustive search situations to collect best possible solution, this nature of algorithm makes it best suited for cluster-based routing in IoV. CAVDO with dynamic weights is first attempt to construct efficient clustering solution in IoVs. The algorithm is initialized by finding CHs, and then finds neighbouring nodes of CHs (Rofida et al,2017). For the application of swarm-based techniques in IoV, following are the requirements of problem encoding. First, a complete solution set formation by combination of multiple different subsets. Second, the evaluation methodology can be applied to solution fitness measures. And third, an associated heuristic measure for solution subsets which is not compulsory, but desirable. Moth Flame Clustering Algorithm This technique is inspired from Moths, Moths have a mechanism called transverse orientation, it is based on tracking path at night by following moon light by making use of the same angle towards the moon, this procedure assures that the moth will fly in a straight line as the moon is immensely distant from the moth, this is an efficient procedure for drifting in lengthy expanses in a strait trail (Muhammad et al, 2019). It is observed that moth fly spirally near artificial lights, moths try to retain an analogous angle with artificial light and try to move in a straight track; but as these light sources are near, preserving a same angle triggers a lethal spiral trail for moths. This is shown in figure 5. Moths can fly in 1- Dimensional, 2- Dimensional, 3- Dimensional or hyper dimensional area with altering their positions. The sets of moths can be shown in the following matrix form.
- 50. 10 Algorithms Optimization for Intelligent IoV Applications M= M M M d M M M d Mn Mn Mn d 1 1 1 2 1 2 1 2 2 2 1 2 , , , , , , : : : : , , , . (1) Where, n: represents the number of moths. d: represents the number of dimensions. The network of autonomous vehicles is created by randomly initializing their position within a certain region called as grid size. Next, the speed and direction of vehicles are also allocated arbitrary. The vehicle ID’s are assigned for the identification so in the mesh topology of the network (Yasir et al, 2018). Afterward, Euclidian distance is measured between all the nodes to form a complete distance matrix of whole network. An ideal number of clusters in IoV network mark the network more stable as the resources of network are effectively employed. Moth flame clustering algorithm optimizes the sum of clusters in the network. This is due to the evolutionary proficiency of MFO which empowers it to select the optimum number of solutions as it is efficient and appropriate for discrete and continuous variable problems (Yasir et al, 2018). Though the implementation of such algorithms is relatively challenging, these procedures are Figure 5. Spiral flying path
- 51. 11 Algorithms Optimization for Intelligent IoV Applications computationally inexpensive, specifically when competed with an extensive search to recognize the finest solution. As a result, these characteristics signify that MFO based procedures are successful for clustering in IoV networks. Mobility Adaptive Density Connected Clustering Algorithm Clustering is one of the popular approaches for topology management that can positively influence in the performance of networks. It plays important role in VANETs. VANET having highly mobile nodes that causes change in topology with a time and it is very difficult to construct stable clusters. More homogeneous environment creates more stable clusters. Homogeneous neighbourhood for a vehicle is strongly driven by density and standard deviation of average relative velocity of vehicles in its commu- nication range. Mobility adaptive density connected clustering algorithm (MADCCA) is a density-based clustering algorithm. This approach used standard deviation of relative velocity and density matrices in their neighbour- hood for selecting the cluster head for a cluster as well as direction and location of movement in the clustering process (Anant Ram et al, 2017). The CHs will select with respect to standard deviation of average relative velocity and density matrices in their neighbourhood. Vehicle that has a more homog- enous environment will be selected as CHs. The standard deviation of the average relative velocity will become low only when all the neighbour vehicles of a vehicle are homogeneous with respect to the av- erage relative velocity. While the standard deviation of the average relative velocity of a vehicle will be very high, when average relative velocity difference of a vehicle is high with each of its neighbourhood. Standard deviation of average relative velocity parameter enhanced the intra-cluster homogeneity; the target of density variation parameter is to improve inter-cluster homogeneity (Anant Ram et al, 2017). Swarm Intelligence (SI) Algorithms Swarm Intelligence (SI) is a new branch of AI based on analysis the action of individuals in various decentralized system. SI provides the possibility of SI behavior through collaboration in individuals that have limited or no intelligence. Its potential parallelism and distribution characteristics used to enable the possibility of solving complex nonlinear problems with advanced capabilities in term of robustness, self-adaptability and search ability (Hazem et al, 2012). Since there are many SI optimization algorithms including classical particle swarm optimization (PSO) and ant colony optimization (ACO). Recently, many improvement algorithms appear such as artificial bee colony (ABC), bacterial foraging algorithm (BFO) and butterfly optimization algorithm (BOA). SI algorithms explore optimized solution based on heuristic information. SI implemented in some area as routing, scheduling, medical, military, telecommunication networks and for process optimization problems (Hazem et al, 2012) (Priyan et al.2017). SI algorithm can be used on robots which is one of the most rapid developments today. There are many developments of SI that was utilized on Unmanned Aerial Vehicle (UAV) for industries because this algorithm has a several benefits such as flexibility, easy marketing and implementation, robustness and derivative free optimization (Priyan et al.2017). Moreover, SI has been developed and installed on autonomous surface vehicle (ASV). ASV implements the global positioning system (GPS) to determine the location, relative orientation to other ASV and ability to arrive the desire direction.
- 52. 12 Algorithms Optimization for Intelligent IoV Applications Ant Colony Optimization (ACO) in IoV In ACO, each ant releases pheromones on the path. The whole ant colony can perceive pheromones. The ants in the ant colony will choose the path with higher pheromones and ants passing through the path will release pheromones so that after a while, the whole ant colony can follow the shortest path to reach the food. The advantages of ACO include strong global optimal ability and flexibility in implementation. It is suitable for integrating with other algorithms. Moreover, this algorithm uses forward and backward ant procedures to know the optimal route to reach the destination. The number of vehicles currently moving on a road and the road length are collected simultaneously with the help of IoV technology (Priyan et al.2017). The calculation of maximum number of vehicles MaxNVij .can be on the road as follows: Max LL L L NL NV ij v ij ij . (2) where, LLij . Represents road length. NLij . represents the number of roads in a street between two nodes (i and j). ∆L .: represents the average distance between two vehicles. Lv . represents the average length of vehicles. Density of vehicles ( Dij . is calculate by D NV Max ij ij NVij = . (3) In ant colony optimization, forward ants used to find the optimal and shortest path to reach the desired destination. The forward ants could calculate the movement of new position as in the following equation. p t a b · a b · N ij k ij ij h tabu ij ij j k 1 1 1 1 1 ,if j tabuk 0otherwise . (4) Where: ∂ij . describe the pheromone value of an ant in node i to move to node j. · ij . describe instan- taneous state of the fuzzy value on the link from i to j and calculated by vehicle as ant. a: describe the weight for the importance of ∂ij .b: describe the weight for the importance of · ij . tabuk . describe a
- 53. 13 Algorithms Optimization for Intelligent IoV Applications group of nodes connected to node i that an ant k has not visited until now. Nj . describe a number of neighbours for node j. If a forward ant reaches desired destination, then the forward ant changes as a backward ant. The memory of forward ant is known from the backward ant to find optimal route. Ant Colony Optimization algorithm is deployed for efficiency in the CH selection/election to create desirable solutions of clustering for IoV. In methods, which are swarm-based, each node is considered to be a single solution, and the swarm is a group of solutions. An ant, in a given instance, depicts all CH IDs of the entire route. The initial attempt is to create optimum solutions in IoV clustering. The Ant Colony Optimization algorithm by using intelligent first-node selection and dynamic evaporation strat- egy makes this aim possible. The initialization of the algorithm is made by finding the CHs regarding node speed, distance, direction, and local traffic density and then locating the neighbouring nodes of the CHs (Mohd Nadhir et al,2015). Every vehicle is considered to have interfaces of 5G and 802.11p. The way the vehicular networks are organized is made up of clusters that are managed by the eNodeBs. The cluster sizes are of varying ranges at 802.11p based on the vehicular local traffic density. Bee Colony Optimization in IoV This algorithm is inspired by the intelligent behaviour of real honey bees in finding food sources, known as nectar, and the sharing of information about that food source among other bees in the nest. The bee colony divides the bee swarm into three types, the employed bee, the onlooker bee, and the scout bee. Each of these bees has different tasks assigned to them in order to complete the algorithm’s process. The employed bees focus on a food source and retain the locality of that food source in their memories. The number of employed bees is equal to the number of food sources since each employed bee is associated with one and only one food source (Anuja et al, 2017). The onlooker bee receives the information of the food source from the employed bee in the hive. After that, one of the food sources is selected to gather the nectar. The scout bee is in charge of finding new food sources and the new nectar. Figure 6 shows the flow chart of Bee colony algorithm. Within bee colony optimization met-heuristic (BCO), the agents that call artificial bees collaborate in order to solve difficult combinatorial optimization problem. All artificial bees are located in the hive at the beginning of the search process. During the search process, artificial bees communicate directly. Each artificial bee makes a series of local moves, and in this way incrementally constructs a solution of the problem. Bees are adding solution components to the current partial solution until they create one or more feasible solutions. The search process is composed of iterations. The first iteration is finished when bees create for the first time one or more feasible solutions. The best discovered solution during the first iteration is saved, and then the second iteration begins. Within the second iteration, bees again incrementally con- struct solutions of the problem, etc. There are one or more partial solutions at the end of iterations. The analyst-decision maker prescribes the total number of iterations (Anuja et al, 2017) (José et al,2018). In the application of vehicle routing problem, the bees construct paths in different ways depending on their roles. Leaders only retrace the last path of the iterative procedure without changing the situation. The scouts and followers choose the next nectar source as follows:
- 54. 14 Algorithms Optimization for Intelligent IoV Applications p t S t f t S t f t j ij k ij y Allowed kto i ij y ( )= ( ) ( ) ( ) ( ) ∉ ∑ [ ] [ ] [ ] [ ] , , β β A A Otherwise i k 0, . (5) Where, p t ij k ( ) representstheprobabilitythatbeektravelsfromnodeitojiniterationt. A Tabu i k k = − Φ denotes the available nodes for bee k, i.e., the points that satisfy all constraints but have not been previ- ously visited by the bee). Tabu k is the tabu list of bee k, which prevents the nodes already visited by bee k from being repeatedly visited. In some applications (i.e., router optimization), it is also convenient that the bee can return through the original path. sij(t) and fij(t) represent the bee colony and heuristic information, respectively, while α and β are the weight coefficients (Ajay et al,2019). Figure 6. The Bee Colony algorithm
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- 56. bear to the form of a miller’s thumb, the peculiar conformation of which is produced by his mode of testing samples of meal. THE STICKLEBACK, (Gastuostius aculiatus,) Is one of our smallest fishes, and appears to live indifferently in fresh and salt water. It is exceedingly common in every pond, and may be caught easily, either with a hand-net, or by fishing for it with a small worm tied to the end of a piece of cotton; he bites at this so boldly that he may be drawn out of the water without the aid of a hook. His name of Stickleback is given to him from his having thin spines on the back instead of a fin; the sides of his body are covered with thin bony plates, and his ventral fins consist of single, strong, and sharp spines, which constitute formidable offensive weapons. The Stickleback, although so common, is one of the most interesting of fishes, on account of the singularity of its habits in the breeding season. Instead of depositing its eggs in the sand or mud, and leaving them to take care of themselves, the Stickleback builds a curious nest of fragments of vegetable matter, and defends this most valiantly against all intruders until the hatching of the young; the parental solicitude does not cease until the young Sticklebacks have grown too big to be any longer controlled. One curious feature in the business is, that it is the male that takes all this trouble; he builds the nest, exposes himself to every danger in its defence, and watches anxiously over the vagaries of his young progeny, the female having nothing to do but to deposit her eggs in the already prepared nest. The Stickleback is an extremely pugnacious fish. The males fight together furiously, and the colours of their bodies become much more brilliant while they are so occupied than at any other time.
- 57. THE ELECTRICAL EEL. (Gymnotus Electricus.) This very remarkable fish is about five or six feet in length, and twelve inches in circumference, in the thickest part of the body. The head is broad, flat, and large; the mouth wide and destitute of teeth; the rostrum obtuse and rounded; the eyes small and of a bluish colour; the back of a darkish brown, the sides grey, and the abdomen of a dingy white. Across the body there are several annular divisions, or rather ridges of the skin, which give the fish the power of contracting or dilating itself at pleasure. There is no dorsal fin, and the ventral fins are also wanting, as in all the Eels. It is able to swim backwards as well as forwards. Mr. Bryant mentions an instance of the shock from one of these fish being felt through a considerable thickness of wood. One morning, while he was standing by, as a servant was emptying a tub, in which an Electrical Eel was contained, he had lifted it entirely from the ground, and was pouring off the water to renew it, when he received a shock so violent as occasioned him to let the tub fall. He then called another person to his assistance, and they lifted up the tub together, each laying hold only on the outside. When they were pouring off the remainder of the water, they received a shock so smart that they were compelled to desist. Persons have been knocked down with a stroke. One of these fish having been taken from a net and laid upon the grass, an English sailor, notwithstanding all the persuasions that were used to prevent him, would insist on taking it up; but the moment he grasped it he dropped down in a fit; his eyes were fixed, his face became livid, and it was not without difficulty that his senses were restored. He said that the instant he touched it “the cold ran swiftly up his arm into his body, and pierced him to the heart.”
- 58. Humboldt tells us that when the Indians wish to catch these Eels they drive some wild horses through the pools which the fish inhabit; and that when the Eels have exhausted their electrical power upon the horses, the Indians take them without difficulty. He relates an instance in which he says that the horses, stunned with the shocks they received, sank under water, but most of them rose again, and gained the shore, where they lay stretched out on the ground, apparently quite exhausted and without the power of moving, so much were they stupefied and benumbed. In about a quarter of an hour, however, the Eels appeared to have exhausted themselves, and, instead of attacking fresh horses that were driven into the pond, fled before them. The Indians then entered the water and caught as many fish as they liked.[B]
- 59. [B] See a very animated account of the capture of this fish, in Humboldt’s “Views of Nature,” page 16 (Bohn’s Edition). This most singular fish is peculiar to South America, where it is found only in stagnant pools, at a great distance from the sea. THE EEL. (Anguilla vulgaris.) The Eel resembles a serpent in its form, though no two animals can be more different in every other respect. Eels are fresh-water fish; but as they are very susceptible of cold, those which inhabit rivers go down every autumn towards the sea, which is always warmer than a river, and return in spring. They are said also to spawn in the sea, and great numbers of young Eels are seen in spring ascending tidal rivers. Mr. Edward Jesse, in his edition of “Walton’s Angler,” says: “A column of them has been traced in the Thames from Somerset House to Oxford, about the middle of May, and I have watched their progress with much interest. No impediment stops them. They keep as much as possible close alongshore, and as they pass watercourses, open ditches, and brooks, c., some of them leave the column and enter these places, along which they eventually make their way to ponds, smaller rivers, c. So strong is the migratory instinct in these little eels, that when I have taken some in a bucket and returned them to the river at some distance from the column, they have immediately rejoined it without any deviation to the right or left. On the banks of the Thames the passage is called Eel-fare. Two observers, watching their progress at Kingston, calculated that from sixteen to eighteen hundred passed a given line per minute. Rennie saw (on the 13th of May) a column of young eels of
- 60. uniform size, about as thick as a crow-quill, and three inches long, returning to the river Clyde, in almost military order, keeping within parallel lines of about six inches. He traced it for several hours without perceiving any diminution.” Those that live in ponds seek the deep water for their winter quarters, and sometimes bury themselves in the mud at the bottom. They are very tenacious of life, and will live for a long time out of water; they are even sometimes found on the grass, passing from one pond to another, in search, it is said, of food. They are voracious feeders, eating frogs, snails, and other molluscous animals, worms, the fry of fishes, and the larvæ of various insects, as well as grass and aquatic weeds. Mr. Jesse states that he has known them to eat young ducks, and even water-rats. The Eel is caught in many different ways. As it seldom stirs during the day, the best method is found to be by setting night-lines. The baits most commonly used are lob-worms, loach, minnows, small perch, with the fins cut off, or small pieces of any fish; but such is the voracity of this animal that it will take almost any bait. Spearing for Eels is a method very commonly resorted to during the winter, when Eels imbed themselves in a state of torpidity in the muddy banks of streams and ponds. Eel-spears have usually six or seven prongs, with long handles. The process consists merely in plunging them into the mud in likely places, and pulling them out again. There seems to be no reason for supposing, as is commonly done, that Eels are viviparous; parasitic worms have sometimes been mistaken for the young animals. The common Eel often weighs upwards of twenty pounds. The flesh is tender, soft, and nourishing, but does not agree with all stomachs. THE CONGER, OR SEA EEL, (Conger vulgaris,) Is very large and thick. Its body is dusky above, and silvery below; the dorsal and anal fins are edged with black; and the lateral line is dotted with white. Its flesh is firm, and was much esteemed by the ancients. It is still eaten by the poorer classes, especially in seaside towns, but would be considered coarse and tasteless by most people in the present day. The voracity of the Conger Eel is very great, and it is one of the most powerful enemies with which the fishermen of the British islands have to
- 61. contend. Being usually caught by a hook and line, it requires some care to land and kill the large ones without danger. We are informed that, on such occasions, they have been known to entwine themselves round the legs of a fisherman, and fight with the utmost fury. They are almost incredibly strong and tenacious of life. When pulled up by the line and landed in a boat, they make a loud, hoarse, grating sound, almost resembling the angry snarling of a dog, which often terrifies the amateur fisherman. Unless seized with great care, they bite most severely. It is even said that men have occasionally been permanently maimed by them. A Conger, six feet in length, was caught in the Wash, at Yarmouth, in April, 1808: but not without a severe contest with the man who had seized it. The animal is stated to have risen half erect, and to have actually knocked the fisherman down before he could secure it. This Conger weighed only about sixty pounds: but some of the largest exceed even a hundredweight.
- 62. Book IV. REPTILES. § 1. Serpents, or Ophidian Reptiles. SERPENTS. SERPENTS. Serpents are characterised by an elongated body, clothed in scales and destitute of limbs, but furnished with a tail. They move by lateral undulations of the body; and in this manner they glide with equal ease along the bare ground, through entangled thickets or water, and up the trunks of trees. They possess the power of fasting a great length of time, and when they feed always swallow their prey whole, which they are enabled to accomplish by their faculty of dilating their bodies to an enormous size. This power is carried to such an extent that a Boa Constrictor can swallow a bullock whole, suffering no other inconvenience than that of lying in a state of torpor while digestion is proceeding. Serpents generally roll themselves up when in a state of repose, with the head in the centre; and when disturbed raise the head before they uncoil the body. The Serpent is often made a subject of poetry; and as it was the form adopted by the arch fiend to seduce Eve, it is generally considered the emblem of insinuation and flattery:
- 63. “—— —— —— —— on his rear, Circular base of rising folds that tower’d Fold above fold, surprising maze, his head Crested aloft, and carbuncle his eyes. With burnish’d neck of verdant gold, erect Amidst his circling spires that on the grass Floated redundant; pleasing was his shape And lovely.... Oft he bow’d His turret crest and sleek enamell’d neck, Fawning, and lick’d the ground whereon she trod.” Paradise Lost. The ancients paid great honours to Serpents, and sometimes called them good genii: they frequented sepulchres and burying-places, and were addressed like the tutelary divinities of these places. We read, in the fifth book of the Æneid, that when the Trojan hero sacrificed to his father’s ghost, a Serpent of this kind made his appearance: “—— —— and from the tomb begun to glide His hugy bulk on seven high volumes roll’d; Blue was his breadth of back, and streak’d with scaly gold. Thus riding on his curls he seemed to pass A rolling fire along, and singe the grass; More various colours through his body run, Than Iris when her bow imbibes the sun. Between the rising altars and around, The sacred monster shot along the ground; With harmless play among the bowls he pass’d, And with his lolling tongue assay’d the taste: Thus fed with holy food, the wondrous guest Within the hollow tomb retired to rest.” Dryden. This animal was exalted to the honour of being an emblem of prudence, and even of eternity; and is often represented as the latter in Egyptian hieroglyphics, biting his tail, so as to form a circle. Serpents are very numerous in Africa; and Lucan, in his “Pharsalia,” gives us a very extraordinary account of the different species, which he seems to have drawn partly from ancient Greek authors, partly from actual traditions. He says:
- 64. “Why plagues like these infect the Libyan air; Why deaths unknown in various shapes appear; Why, fruitful to destroy, the cursed land Is temper’d thus by Nature’s secret hand; Dark and obscure the hidden cause remains, And still deludes the vain inquirer’s pains.” Rowe’s “Lucan. Serpents differ very much in size. We are told of Serpents in the Isle of Java measuring fifty feet in length; and in the British Museum there is a skin of one thirty-two feet long. THE VIPER, OR ADDER, (Vipera berus,) Is a venomous species of serpent that seldom exceeds the length of two or three feet, and is of a dull yellowish brown colour with black spots, the abdomen being entirely black; the head is nearly in the shape of a lozenge, and much thicker than the body. The Viper is viviparous; yet it is ascertained that the eggs are formed, though they are hatched in the body of the mother. The Reverend Mr. White, of Selborne, in company with a friend, surprised a large female Viper, as she lay on the grass, basking in the sun, which seemed very heavy and bloated. As Vipers are so venomous that they
- 65. should be destroyed, they killed her; and afterwards, being curious to know what made her so large, they opened her, and found in her abdomen fifteen young ones, about the size of full-grown earth-worms. This little fry issued into the world with the true Viper spirit about them, showing great alertness as soon as they were disengaged from the body of their parent. They twisted and wriggled about, set themselves up, and gaped very wide when touched with a stick; exhibiting manifest tokens of menace and defiance, though as yet no fangs could be discovered, even by the help of glasses. Vipers attain their full growth in seven years; they feed on frogs, toads, lizards, and other animals of that kind, and it is even asserted that they catch mice and small birds, of which they seem very fond. They cast their skin every year. The two front teeth in the upper jaw of the Viper are furnished with a small bladder containing poison. There is no doubt but this poison, which appears to have been infused into the jaws of the Viper and other serpents by Providence, as a means of revenge upon their enemies, is so harmless to the animal itself, that when swallowed by it it only serves to accelerate its digestion. These venomous teeth or fangs stand, each by itself, upon a small movable bone; this arrangement enables the creature to fold down its fearful weapons in the mouth, and to erect them instantly when it has occasion to make use of them. The Viper is very patient of hunger, and may be kept more than six months without food. When in confinement, it refuses all sustenance, and the sharpness of its poison decreases in proportion: when at liberty, it remains torpid throughout the winter; yet, when confined, it has never been observed to take its annual repose. The Viper is a native of many parts of this island, chiefly the dry and chalky counties. Its flesh was formerly used for broth, and much esteemed in medicine, particularly to restore debilitated constitutions. It was also used as a cosmetic, being supposed to render the complexion fair. It was probably from the use made by the ancients of this animal in medicine that Esculapius is represented with a serpent. The best remedy against the bite of the Viper is to suck the wound, which may be done without danger, and after this to rub it with sweet oil, and poultice it with bread and milk.
- 66. THE HORNED VIPER. (Cerastes Hasselquistii.) This species of Viper is nearly allied to the asp, and has a pointed and solid horny substance on each eyelid, formed of two projecting scales: its body is of a pale yellowish or greyish colour, with distant sub-ovate transverse brown spots; and in length it is from one to two feet. This species is often mentioned by the ancients. Pliny tells us that “the serpent Cerastes hath many times four small horns, standing out double; with moving whereof she amuseth the birds, and traineth them unto her for to catch them, hiding all the rest of her body.” It is found in the sandy deserts of Egypt and the neighbouring countries, and is believed to be the Asp with which Cleopatra eluded the disgrace of becoming a prisoner to her Roman conqueror. THE RATTLE-SNAKE, (Crotalus horridus,) Is a native of the New World, and grows to five or six, and sometimes to eight feet in length, and is nearly as thick as a man’s leg. It is not unlike the
- 67. viper, having a large head and small neck, and inflicting a very dangerous wound. Over each eye is a large pendulous scale, the use of which has not yet been ascertained; the body is scaly and hard, variegated with several different colours. The principal characteristic of this justly dreaded serpent is the rattle, a kind of instrument resembling the curb-chain of a bridle, at the extremity of the tail; it is formed of thin, hard, hollow bones, linked together, and rattling on the least motion. When disturbed, the creature shakes this rattle with considerable noise and rapidity, striking terror into all the smaller animals, which are afraid of the destructive venom that this serpent communicates to the wounded limb with his bite. The wound the Rattle-snake inflicts, through the uncommon sharpness and rapid fluency of the poison, generally terminates the torment and life of the unhappy victim in the course of six or seven hours. A snake of this kind exhibited in London at a menagerie of foreign animals, in the year 1810, wounded a carpenter’s hand, who was repairing its cage, and seeking for his rule. The man suffered the most excruciating pain, and his life could not be saved, although medical assistance was immediately applied, and every effort made to prevent the dire effect of the poison. The proprietor was condemned to pay a deodand for the injury done by the serpent. THE HAJE, OR EGYPTIAN ASP. (Naja Haje.)
- 68. The Haje, or Egyptian Asp, is from three to six feet in length; it has two teeth longer than the rest, through which the venom flows. The body is covered with small round scales, and is of a greenish colour, bordered with brown; its neck is capable of inflation. The jugglers of Egypt, by pressing this Asp on the nape of the neck with the finger, throw the animal into a kind of catalepsy, which renders it stiff and immovable; when they say that they have changed it into a rod. The habit which this species has of raising itself up when approached, induced the ancient Egyptians to believe that it guarded the fields where it was found; and it is sculptured on the gates of their temples as an emblem of the protecting divinity of the world. THE HOODED SERPENT, OR COBRA DI CAPELLO, (Naja tripudians,) Called by the Indians the Nagao, is from three to eight feet long, with two long fangs in the upper jaw. It has a broad neck, and a mark of dark brown on the forehead; which, when viewed frontwise, looks like a pair of spectacles; but behind, like the head of a cat. The eyes are fierce and full of fire; the head is small, and the nose flat, though covered with very large scales, of a yellowish ash-colour: the skin is white, and the large tumour on
- 69. the neck is flat and covered with oblong smooth scales. This serpent is extremely dreaded by the British residents in India, as its bite has hitherto been found to be incurable, and the sufferer generally dies in half an hour. Of this kind are the dancing-snakes, which are carried in baskets throughout Hindoostan, and procure a maintenance for a set of people, who play a few simple notes on the flute, with which the snakes seem much delighted, and keep time by a graceful motion of the head; erecting about half their length from the ground, and following the music with gentle curves, like the undulating lines of a swan’s neck. It is a well-attested fact, that, when a house is infested with these snakes, and some other of the coluber genus, which destroy poultry and small domestic animals, as also by the larger serpents of the boa tribe, the musicians are sent for; who, by playing on a flageolet, find out their hiding places, and charm them to destruction: for no sooner do the snakes hear the music, than they come softly from their retreat, and are easily taken. I imagine these musical snakes were known in Palestine, from the Psalmist comparing the ungodly to the deaf adder, which stoppeth her ears, and refuseth to hear the voice of the charmer, charm he never so wisely. THE SNAKE, (Coluber natrix,) Is the largest of all English serpents, sometimes exceeding four feet in length. The colour of the body is variegated with yellow, green, white, and regular spots of brown and black. They seem to enjoy themselves when basking in the sun, at the foot of an old wall. This animal is perfectly innoxious, although many reports have been circulated and believed to the contrary; it feeds on frogs, worms, mice, and various kinds of insects, and passes the greater part of the winter in a state of torpidity. In the spring they
- 70. re-appear, and at this season uniformly cast their skins. This is a process that they also seem to undergo in autumn. Mr. White says: “About the middle of September we found in a field, near a hedge, the slough of a large snake, which seemed to have been newly cast. It appeared as if turned wrong side outward, and as if it had been drawn off backward, like a stocking or a woman’s glove. Not only the whole skin, but even the scales from the eyes were peeled off, and appeared in the slough like a pair of spectacles. The reptile, at the time of changing his coat, had entangled himself intricately in the grass and weeds, in order that the friction of the stalks and blades might promote this curious shifting of his exuvia.” THE BOA CONSTRICTOR. This immense animal is often twenty feet in length, and sometimes even thirty-five; the ground colour of its skin is yellowish grey, on which is distributed, along the back, a series of large chain-like, reddish brown, and sometimes perfectly red, variegations, with other smaller and more irregular marks and spots. It is a native of South America, where it chiefly resides in the most retired situations in woods and marshes. The bite of this snake is not venomous, nor is the animal believed to bite at all, except to seize its prey. It kills its prey by twining round it and crushing its bones. The Python and the Anaconda, which are at least as large as the Boa Constrictor, are found chiefly in the Indian Islands: they are very similar both in form and colouring to the Boa, and have exactly the same habits.
- 71. These monsters will attack and devour the largest animals, of which the following is an instance: A Boa had for some time been waiting near the brink of a pool in expectation of its prey, when a buffalo appeared. Having darted upon the affrighted beast, it instantly began to encircle him with its voluminous twistings, and at every twist the bones of the buffalo were heard to crack as loud as the report of a gun. It was in vain that the animal struggled and bellowed; its enormous enemy entwined it so closely that at length all its bones were crushed to pieces, like those of a malefactor on the wheel, and the whole body was reduced to one uniform mass: the serpent then untwined its folds in order to swallow its prey at leisure. To prepare for this, and also to make it slip down the throat more smoothly, it licked the whole body over, covering it with a mucilaginous substance. It then began to swallow it, at the end that afforded the least resistance, and in the act of swallowing, the throat suffered so great a dilation as to take in a substance that was thrice its own ordinary thickness. THE AMPHISBÆNA. (Amphisbæna fuliginosa.) This name is now applied only to a genus of South American reptiles, which are of a harmless nature, being destitute of those fangs which prepare the venom in poisonous serpents. It is indeed doubtful whether the Amphisbænas are really snakes, and by many naturalists they are arranged amongst the lizards, although they have no limbs. The head is so small, and the tail so thick and short, that at first sight it is difficult to distinguish one from the other; and this circumstance, united to the animal’s habit of proceeding either backwards or forwards as occasion may require, gave rise to the supposition throughout the native regions of the Amphisbæna, that it had two heads, one at each extremity, and that it was impossible to destroy
- 72. one by simple cutting, as the two heads would mutually seek one another and reunite! The colour of the commonest species is a deep brown varied with patches of white. The body is ornamented by more than two hundred rings, and the tail by about twenty-five. The eyes are almost concealed by a thick membrane, and this, together with their small size, has given rise to the idea that the Amphisbæna is blind. It grows to the length of eighteen inches or two feet. Its food consists of worms and insects, and especially ants, in the mounds of which it generally conceals itself. The ancients gave the name of Amphisbæna to what they considered a two-headed serpent; but it is not known with certainty which of the serpent tribe they meant, as their Amphisbæna is described by Lucan as venomous, though in his lines elegance of language, beauty of versification, and liveliness of fancy, have perhaps a greater claim than truth to the admiration of the reader:— “With hissings fierce, dire Amphisbænas rear Their double heads, and rouse the soldier’s fear. Eager he flies: more eager they pursue; On every side the onset quick renew! With equal swiftness face or shun the prey, And follow fast when thought to run away. Thus on the looms the busy shuttles glide, Alternate fly, and shoot at either side.” § II. Batrachian Reptiles.
- 73. THE FROG. (Rana temporaria.) When this reptile issues from the egg it is merely a black, oval mass, with a slender tail. This tadpole, as it is then called, is the embryo of the Frog, and when it has attained a certain size its body gradually acquires the form of that of the Frog, its legs sprout from its sides, and finally its tail is cast off. This metamorphosis is one of the most curious in nature, and deserves our observation. Like other reptiles, it is not necessary for it to breathe in order to put its blood into circulation, as it has a communication between the two ventricles of the heart. It lives during spring in ponds, brooks, muddy ditches, marshy grounds, and other watery places, in summer in corn-fields and pasture land. Its voice proceeds from two bladders, one on each side of the mouth, which it can fill with wind. When it croaks, it puts its head out of the water. The hinder legs of the Frog are much longer than the fore ones, to help it in its repeated and extensive leaps. The whole of the body bears a little resemblance to some of the warm-blooded animals, principally about the thighs and the toes. The Frog is extremely tenacious of life, and often survives the abscission of its head for several hours. It is supposed that Frogs spend the whole winter at the bottom of some stagnant water in a state of torpidity. There are several species of the Frog; they are all oviparous, and the eggs are gelatinous. The Edible Frog is the species used in France and Germany for food; it is considerably larger than the common kind, and though rare in England, is very plentiful in France, Germany, and Italy. Its colour is olive green, marked with black patches on the back, and on its
- 74. limbs with transverse bars of the same. From the tip of the nose three distinct stripes of pale yellow extend to the extremity of the body, the middle one slightly depressed, and the lateral ones considerably elevated. The upper parts are of a pale whitish colour, tinged with green, and marked with irregular brown spots. These creatures are brought from the country, thirty or forty thousand at a time, to Vienna, and sold to the great dealers, who have froggeries for them, which are pits four or five feet deep, dug in the ground, the mouth covered with a board, and in severe weather with straw. In the year 1793, there were but three great dealers in Vienna, by whom those persons who brought them to the markets ready for the cook were supplied. Only the legs and thighs are eaten, and these are always skinned. They are rather dear, being considered a great delicacy. The Edible Frogs are caught in various ways, sometimes in the night, by means of nets, into which they are attracted by the light of torches that are carried out for the purpose, and sometimes by hooks, baited with worms, insects, flesh, or even a bit of red cloth. They are exceedingly voracious, and seize everything that moves before them. THE TOAD, (Bufo vulgaris,) Whose very name seems to carry with it something of an opprobrious meaning, is not unworthy the attention of the observer of nature; for, though prejudice and false associations have affixed a stigma on certain species of animals, none of the works of our Creator are despicable, but all, the more minutely they are examined, the greater claim they are found to have to our admiration. Somewhat like the frog in the body, it also resembles that animal in its habits; but the frog leaps, while the Toad crawls. It is an error to suppose the Toad to be a noxious and venomous animal; it is as harmless as the frog, and, like some of the human kind, only labours under the stigma of undeserved calumny. Several stories have been related of its spitting
- 75. poison, or knowing how to expel the venom it may have received from the spider or any other animals; but these fables have been long exploded. A curious and yet inexplicable phenomenon is that Toads have been said to be found alive in the centre of large blocks of stone, where they must have subsisted without food and respiration for a number of years. The following are recorded examples: In the year 1719, M. Hubert, professor of philosophy at Caen, was witness to a living Toad being taken from the solid trunk of an elm-tree. It was lodged exactly in the centre, and filled the whole of the space that contained it. The tree was in every other respect firm and sound. Dr. Bradley saw a Toad taken from the trunk of a large oak. In the year 1733, a live Toad was discovered by M. Grayburg in a hard and solid block of stone which had been dug up in a quarry in Gothland. On being touched with a stick upon the head, he informs us, it contracted its eyes as if asleep, and when the stick was moved gradually opened them. Its mouth had no aperture, but was closed round with a yellowish skin. On being pressed with the stick on the back, a small quantity of clear water issued from it behind, and it immediately died. A living Toad was found in a block of marble at Chillingham Castle, belonging to Lord Tankerville, near Alnwick, in Northumberland. Some of these cases are related in a manner which renders it difficult to doubt that the observers described what they thought they saw; but the occurrence of the phenomena, as described, seems to be so utterly impossible that we are forced to suppose that those writers have been misled in some way. That there is some foundation for many of the stories in question we can have no doubt, but we must look forward to further observations for their explanation; as Mr. Bell says: “To believe that a Toad, inclosed within a mass of clay, or other similar substance, shall exist wholly without air or food, for hundreds of years, and at length be liberated alive, and capable of crawling, on the breaking up of the matrix, now become a solid rock, is certainly a demand upon our credulity which few would be ready to answer.” With regard to the length of life of these animals, it is impossible to state anything decisive, but several facts prove that some of them have been gifted with astonishing longevity. A correspondent of Mr. Pennant’s supplied him with some curious particulars respecting a domestic Toad, which continued in the same place for thirty-six years. It frequented the steps before the hall-door of a
- 76. gentleman’s house in Devonshire. By being constantly fed, it was rendered so tame as always to come out of its hole in the evening when a candle was brought, and to look up as if expecting to be carried into the house, where it was frequently fed with insects. An animal of this description being so much noticed and befriended excited the curiosity of all who came to the house, and even females so far conquered the horrors instilled into them by their nurses as generally to request to see it fed. It appeared most partial to flesh-maggots, which were kept for it in bran. It would follow them on the table, and, when within a proper distance, would fix its eyes and remain motionless for a little while, apparently to prepare for the stroke which was to follow, and which was instantaneous. It threw out its tongue to a great distance, and the insect, stuck by the glutinous matter to its tip, was swallowed by a motion quicker than the eye could follow. After having been kept more than thirty-six years it was at length destroyed by a tame raven, which one day seeing it at the mouth of its hole pulled it out, and so wounded it that it died. THE SURINAM TOAD, (Pipa Americana,) Which is one of the ugliest of all Toads, is remarkable for the mode in which the young are developed. The female, like that of the common Toad, deposits her eggs at the edge of the water, but instead of leaving them there, the male takes the mass of eggs and places them on the back of his partner, pressing them down into a number of curious pits, which are produced in that part at the breeding season. When each of the pits has received its egg, the orifice becomes closed by a sort of lid, and the young animal goes
- 77. through all its changes from the tadpole to the perfect Toad in this rather confined space. This curious Toad is found in Guiana; it frequents the dark corners of the houses, and, notwithstanding its intense ugliness, is eaten by the natives. THE COMMON NEWT. (Triton aquaticus.) Besides the frogs and toads, which have no tails when arrived at their perfect form, there are several Batrachian Reptiles in which this appendage is permanent. The best known of these are the Newts, of which two kinds are very common in ponds during the spring. The common Newt is three or four inches in length, and is of a pale brown colour above, and orange with black spots below. It has four little webbed feet and a flattened tail. In swimming, the legs are turned backwards to lessen resistance, and the animal is propelled principally by the tail. Their progression at the bottom of the water and on land is performed creepingly with their small and weak feet. These animals live during the autumn and winter under stones and clods of earth, and come down to the water in February or March for the purpose of depositing their eggs there. The eggs are carefully inclosed by the parents in the leaves of aquatic plants. The young, when first hatched, are in the form of tadpoles; the legs afterwards sprout from the sides of the body, but the tail is not cast off, as in the frogs. The old Newts remain in the water until July or August. THE GREAT NEWT. (Triton palustris.)
- 78. This, the largest British species of the Newt, is by no means uncommon in our ponds and ditches. It is about six inches in length; its back is dark, and its under side is orange-coloured, sprinkled with small black spots; altogether it is darker and richer in colour than the common species. During the breeding season the males of both species, but especially those of the larger one, are adorned with membranous crests, and their colours become much more vivid. Their tenacity of life is very great; when mutilated, they will reproduce the lost parts, and they may be frozen into a solid lump of ice without losing their vitality. With regard to its habits, this animal is a most voracious creature, and devours unsparingly aquatic insects, and, in fact, any small animal which happens to come in its way. For tadpoles it seems to have a special predilection, and its greediness is such that it has not escaped the charge of cannibalism. These Newts have more than once been taken in the act of devouring individuals of the smaller species, but of such a size that there seems to have been considerable difficulty in swallowing them. § III. Saurian Reptiles. THE LIZARD. (Lacerta vivipara.)
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