Table Of ContentCognitive Computing for
Internet of Medical Things
Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assess-
ment of the present scenarios, roles, challenges, technologies, and impacts of IoMT-enabled
smart healthcare systems. It contains chapters discussing various biomedical applications
under the umbrella of the IoMT.
Key Features
• Exploits the different prospects of cognitive computing techniques for the IoMT
and smart healthcare applications
• Addresses the significance of IoMT and cognitive computing in the evolution of
intelligent medical systems for biomedical applications
• Describes the different computing techniques of cognitive intelligent systems
from a practical point of view: solving common life problems
• Explores the technologies and tools to utilize IoMT for the transformation and
growth of healthcare systems
• Focuses on the economic, social, and environmental impacts of IoMT-enabled
smart healthcare systems.
This book is primarily aimed at graduates, researchers, and academicians working in the
area of development of the applications of IoT in smart healthcare. Industry professionals
will also find this book helpful.
Cognitive Computing for
Internet of Medical Things
Edited by
A Prasanth
Lakshmi D
Rajesh Kumar Dhanaraj
Balamurugan Balusamy
Sherimon P C
First edition published 2023
by CRC Press
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CRC Press is an imprint of Taylor & Francis Group, LLC
© 2023 selection and editorial matter, A Prasanth, Lakshmi D, Rajesh Kumar Dhanaraj, Balamurugan Balusamy and
Sherimon P C; individual chapters, the contributors
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ISBN: 978-103-218-7884 (hbk)
ISBN: 978-103-218-7891 (pbk)
ISBN: 978-100-325-6243 (ebk)
DOI: 10.1201/9781003256243
Typeset in Palatino
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Contents
Preface ............................................................................................................................................vii
Editors ..............................................................................................................................................ix
List of Contributors ........................................................................................................................xi
1. Toward the Internet of Things and Its Applications: A Review on Recent
Innovations and Challenges ................................................................................................1
Arunkumar Gopu, Neelanarayanan Venkataraman, and M. Nalini
2. Introduction to Cognitive Computing .............................................................................23
M. Nalini, A. Prasanth, Arunkumar Gopu, and D. Lakshmi
3. IoT with 5G in Healthcare Systems ..................................................................................45
S. Vijayanand
4. Communication Protocols for IoMT-Based Healthcare Systems ...............................59
N. Pushpalatha, P. Anbarasu, and A. Venkatesh
5. Security and Privacy of Biomedical Data in IoMT ........................................................77
Ashish Kumbhare and Piyush Kumar Thakur
6. Cyber-Security Threats to IoMT-Enabled Healthcare Systems ................................105
S. Roobini, M. Kavitha, M. Sujaritha, and D. Rajesh Kumar
7. Using Self-Organizing Map to Find Cardiac Risk Based on Body Mass Index....131
Pon Bharathi A, Allan J. Wilson, S. Veluchamy, and S. Swathi
8. Embedded Medical IoT Devices for Monitoring and Diagnosing Patient
Health in Rural Areas Peoples Using IoMT Technology ...........................................153
V. Karuppuchamy, S. Palanivel Rajan, and C. Manikandan
9. Case Studies: Cancer Prediction and Diagnosis in the IoMT Environment ..........173
C. Soundaryaveni, A. Prasanth, S. Lavanya, and K.K. Devi Sowndarya
10. A Deep Exploration of Imaging Diagnosis Approaches for IoMT-Based
Coronavirus Disease of 2019 Diagnosis System – A Case Study .............................199
Preethi Sambandam Raju, Revathi Arumugam Rajendran, and Murugan Mahalingam
Index .............................................................................................................................................217
v
Preface
Technology can help us in our personal and professional life in the quest to stay healthy.
Our digital devices can help us to improve our diets, measure our workout activities, and
keep track of our prescription compliance.
Sensor-based devices such as physiological monitors, ventilators, infusion pumps, and
bedside computer terminals are utilized in modern medical treatment for the reading of
biomarkers and other clinical activities.
Reducing human errors, increasing clinical outcomes, facilitating care coordination,
enhancing practice efficiencies, and collecting data over time are all examples of how
health informatics may help improve and revolutionize healthcare. Machine learning, the
Internet of things (IoT), deep learning, embedded systems, augmented reality, and cogni-
tive computing are among the technologies used.
The usage of medical technological instruments ensures the safety of patients. First,
there are medication warnings, flags and reminders, consultation and diagnosis reports,
and improved patient data accessibility. Alerts, in particular, might assist someone in
sticking to specified medications and treatment schedules.
Digital technology in medicine and healthcare could help transform unsustainable
healthcare systems into sustainable ones, ensure the equal relationships between med-
ical professionals and patients, and provide cheaper, faster, and more effective disease
solutions – technologies could help us win the cancer battle.
Doctors and nurses now use mobile gadgets to record real-time data and update patients’
medical histories. Diagnoses and treatments become more accurate and efficient as a
result. The centralization of key patient data and lab findings has significantly improved
healthcare quality.
The use of artificial intelligence-based analytical models to imitate the human thought
process in complex settings where the solutions may be ambiguous and uncertain is
known as cognitive computing. The goal of cognitive computing is to create a compu-
tational model that mimics human thought processes. The computer may simulate the
way the human brain works by using self-learning algorithms that leverage data min-
ing, pattern recognition, and natural language processing. Cognitive computing systems
are thinking, reasoning, and remembering systems that collaborate with humans to help
them make better decisions. Its findings are meant to be consumed by humans. AI aims to
produce the most accurate result or action by employing the best algorithm.
Thanks to 5G’s 100 times more bandwidth than 4G for connecting with IoT devices,
healthcare service providers can rely on remote patient monitoring or wearable devices
to continuously gather, report, and transfer crucial information to a remote monitoring
station.
IoT has the potential to make healthcare more affordable and efficient in future. It can
aid in the development of more personalized and patient-centered devices. Furthermore,
IoT will enable patients to have better access to data and individualized care, resulting in
fewer hospital visits.
The Internet of Medical Things (IoMT) is a collection of medical equipment and apps
that use online computer networks to link to healthcare IT systems. Machine-to-machine
communication, which is the foundation of IoMT, is enabled by medical devices equipped
with Wi-Fi.
vii
viii Preface
A communication protocol is a set of rules that allows two or more entities in a commu-
nications system to send data using any physical quantity variation. The protocol specifies
the communication rules, syntax, semantics, and synchronization, as well as error recov-
ery techniques.
IoT protocols are classified according to the role that each of them plays in the net-
work. Protocols for network infrastructure (e.g., 6LowPAN), communications (Wi-Fi and
Bluetooth), data transmission (MQTT, CoAP, and XMPP), security (DTLS), device manage-
ment, and telemetry (LwM2M) are just a few examples.
The Internet of Medical Things (IoMT) is a network of sensors, wearable devices, medi-
cal devices, and clinical systems that are all connected.
The embedded medical device takes the user’s inputs and compares them to a pre-loaded
symptom dossier and then attempts to match the symptoms with the appropriate ailment.
If the disease is not detected by evaluating the symptoms, it undertakes tests suggested by
the pre-loaded symptom file to find a precise match for the condition.
Embedded systems are also used in glucose monitors, pacemakers, CPAP machines, and
a range of biomedical sensors. Embedded systems in biomedical applications allow clini-
cians to use telemedicine and other remote systems to remotely monitor patients’ health
and make diagnostic and treatment decisions.
The security of data and devices has become a serious problem in the field of healthcare
automation. This book covers a variety of tools and approaches for dealing with the safety
and security systems of medical equipment.
This book is a collection of chapters written for health professionals, academicians,
undergraduates, graduates, and researchers who want to learn more about the cutting-
edge technologies employed in modern drugs.
Editors
Dr. A Prasanth is an Assistant Professor at Sri Venkateswara College of Engineering,
Sriperumpudur, India. He earned a B.E. degree in Electronics and Communication
Engineering from Anna University, Chennai, and an M.E degree in Computer Science and
Engineering (with specialization in networks) from Anna University, Chennai, and also
earned a Ph.D. in Information and Communication Engineering from Anna University,
Chennai, India. Recently, he has received the Young Scientist Award from International
Scientist Awards 2020 for his excellent research performance. He also received the
Researcher of the Year Award 2020 from “2nd International Business and Academic
Excellence Awards (IBAE)”, in Delhi, held on December 26, 2020. Moreover, he received
the Young Researcher Award from “Institute of Scholars Awards” 2020. He has published
more than 25 research articles in reputed international journals, among which 7 articles
are indexed in SCI and 15 articles are indexed in Scopus. He has published and granted
two patents. Further, he has published more than eight books under reputed publishers.
He has served as a resource person in 20 AICTE-Sponsored STTP programs. Moreover, he
has served as an Editorial Board Member in various reputed SCI journals. He has 8 years
of teaching experience, and his research interests include Internet of things, edge comput-
ing, cloud computing, and 5G network.
Dr. Lakshmi D i s a Senior Associate Professor (Grade 2) in the School of Computer Science
and Engineering at VIT Bhopal University, Madhya Pradesh, India. Since February 2021, she
was designated as an Educational Research Officer at Vishnu Educational Development and
Innovation Centre (VEDIC) and an Associate Professor at B V Raju Institute of Technology
run by Shri Vishnu Educational Society, Hyderabad, from 2016 to Feb 2021. She has been
working in the educational sector since 1998. Her key focus is on exploring the dynamics
of learning, dynamics of learner, and classroom dynamics, suitable to accelerate the learn-
ing efficacy of higher education students. With her expertise, she has delivered more than
150 sessions on various titles. Her research areas include machine learning, deep learn-
ing, Internet of things, educational technology, educational data mining, virtual education,
and educational psychology. She holds a Ph.D. degree in Information and Communication
Engineering from Anna University, Chennai, India. She has published 28 articles in vari-
ous journals and conference proceedings and contributed chapters to books. She has won
two best paper awards: one in IEEE and one in Springer conference. One book publica-
tion titled, “Theory of Computation”, seven Indian patents provisionally published and wait-
ing for examinations and filed one copyright waiting for grant. One copyright has been
granted, two Australian patents have been granted, and one is filed and waiting for a grant.
Dr. Rajesh Kumar Dhanaraj is an Associate Professor in the School of Computing Science
and Engineering at Galgotias University, Greater Noida, Uttar Pradesh, India. He holds
a Ph.D. degree in Information and Communication Engineering from Anna University,
India. He has presented papers at conferences, published articles and papers in vari-
ous journals, and contributed a chapter to a book. His research and publication interests
include wireless sensor networks and cloud computing. He is an Expert Advisory Panel
Member of Texas Instruments Inc., the USA.
ix
