Ph D Kumar Safe (PDF)

Deliberation and Exertion of Wireless Body
Area Networks for Exclusive Health Care
Supervision over IoT

Thesis
Submitted To The
VEER BAHADUR SINGH PURVANCHAL
UNIVERSITY, JAUNPUR (U.P.) India

For the award of

Doctor of Philosophy
Degree in ECE
SUBMITTED BY:

Kumar Keshamoni
Enrolment NO. PU 2014/6225

Under the supervision of

Dr. G Manoj Someswar (Ph.D., D.Litt.)
Professor, Dept. Of ECE
JAUNPUR, UP, India

2017

V.B.S PURVANCHAL UNIVERSITY, JAUNPUR
(DEPARTMENT OF ENGINEERING & RESEARCH)

CERTIFICATE

This is to certify that Kumar Keshamoni has worked under my
supervision for the Degree of Doctor of Philosophy in ECE (Department of Engineering
& Research) of Veer Bahadur Singh Purvanchal University, Jaunpur (U. P.), India, on
the topic “Deliberation and Exertion of Wireless Body Area Networks for
Exclusive Health Care Supervision over IoT”. The findings contained in this thesis
are original and have not been used elsewhere in India or abroad for the award of Ph. D.
Degree.

Supervisor
Dr. G Manoj Someswar (Ph.D., D.Litt.)
Professor, Dept. of ECE

UNDERTAKING FORM OF THE CANDIDATE

I hereby declare that the work incorporated in the present thesis entitled
“Deliberation and Exertion of Wireless Body Area Networks for Exclusive Health
Care Supervision over IoT” is my own work and is original. This work (in part or in
full) has not been submitted to any university for the award of a degree or diploma.

Signature of the Candidate
(Kumar Keshamoni)

CANDIDATE’S DECLARATION

I, Kumar Keshamoni, certify that the work embodied in this Ph.D. thesis is my
own bonafide work carried out by me under the supervision of Dr. G Manoj Someswar
at Department of Electronics & Communication Engineering, Veer Bahadur Singh
Purvanchal University, Jaunpur. The matter embodies in the Ph.D. thesis has not been
submitted for the award of any degree/diploma.

I declare that I have faithfully acknowledged, given credit to end referred to the
research workers wherever their works have been cited in the text and the body of the
thesis. I further certified that I have not willfully lifted up some other’s work, Para, text,
data, results etc. reported in the journal, books, magazines, reports, dissertations and
thesis etc. or available at web-sited and included them in this Ph.D. thesis and cited as my
own work.

Signature of the Candidate
(Kumar Keshamoni)

ACKNOWLEDGEMENT

At the outset, it is my privilege to express my sincere gratitude and feel indebted
to my thesis supervisor Dr. G Manoj Someswar (Ph.D., D.Litt.), Professor, Department
of Electronics & Communication Engineering, for suggesting me the problem and his
keen interest, invaluable help and continuous encouragement during my entire research
work. His untiring patience, constructive criticism and constant motivation, enabled me
to do this work so as to reach a stage of completeness. Whenever I fumbled in darkness
of confusion and dilemma, enlightenment came from his suggestions, criticism and
guidance and clearing the horizons for me. Apart from thesis matters his interests in
leading a healthy and disciplined life also influenced me.

I am grateful to Dr. Mayank Tripathi (Ph.D., D.Litt.), Professor & Head, Department
of Electronics & Communication Engineering, for his perpetual inspiration and
inimitable teaching as a source of infinite acumen. He has always been a source of
encouragement for me during my entire work.

I gratefully acknowledge the encouragement, the unceasing care given by Dr. Harish
Chandra Tripathi, Dr. Eswar Rai Upadhayay of Associate Professor, Department of
Electronics & Communication Engineering, U N S Institute of Engineering &
Technology, Jaunpur. I am highly obliged to all of the above mentioned teachers for their
unending help, support and love towards me and my work.

I extend my sincere thanks to all the subjects of different Colleges and Universities for
extending all the help during the collection of data. Their enthusiastic cooperation and
support is priceless, without their support I’ll not be able to complete my work.

Kumar Keshamoni

ABSTRACT
The net of Things (IoT) makes sensible objects the last word building blocks
within the development of cyber physical sensible pervasive frameworks. The IoT
incorporates a type of application domains, as well as health care. The IoT revolution
is redesigning fashionable health care with promising technological, economic, and
social prospects. This thesis advances in IoT-based health care technologies and
Body-area networks (BANs) are wireless detector networks (WSNs). This thesis
analyzes distinct IoT security and privacy options, as well as security necessities,
threat models, and attack taxonomies from the health care perspective. Body-area
networks (BANs) are wireless detector networks (WSNs) that operate in shut
proximity to the human body, getting used for instance for distributed wireless
medical body sensors. Current implementations of BANs use standardized
frequencies (RF) technologies like IEEE 802.15.4, and don't account the
characteristics of the body channel, e.g. sturdy attenuation of high frequency radio
waves. In order to supply high responsible additionally as energy potency whereas
communicating near the flesh, a replacement technology known as body-coupled
communication (BCC) was developed. As it uses the flesh as channel, it doesn't suffer
from shadowing and allows economical and reliable digital communication between
nodes in shut contact with the flesh. As many applications still need transmission
some knowledge few meters from the flesh, it's essential to even have RF capabilities
during a BCC-BSN. During this thesis we have a tendency to propose replacement
BAN node architecture wherever all nodes have each a BCC and RF transceiver.
Tendency to propose a protocol that allows the cooperation between the 2
technologies. A Tendency to gift the hardware and software system implementation
and illustrate our conception with measurement results.

This thesis proposes AN intelligent cooperative security model to attenuate security
risk. We show that our dual technology solution is more efficient and reliable than
classical RF solutions for BANs. This paper provides energetic security algorithm for
sensing devices and multiple applications. Industries such as relevant to medicine and
sport can get benefits means in plenty from the wireless body area network projects.
By means of these sensor devices any one can successfully know the heartbeat, level
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of the glucose, and blood pressure of the patient. We can predict heart attack,
diabetes, cancer and many other diseases without much of a difficulty using Wireless
body area network concepts. The Internet of Things (IoT) makes sensible objects the
last word building blocks within the development of cyber-physical sensible pervasive
frameworks. The IoT incorporates a type of application domains, including health
care. The IoT revolution is redesigning fashionable health care with promising
technological, economic, and social prospects.

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LIST OF FIGURES
Figure 1.1 -The proposed typical structure of the health IoT system

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Figure 2.1 - Block diagram of a BN powered by energy harvesting

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Figure 2.2 - Energy harvesters in the human environment

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Figure 2.3 - Examples of predictable energy harvesting sources

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Figure 2.4 - Examples of unpredictable energy harvesting sources

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Figure 2.5 - Examples artificial energy harvesting sources

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Figure 2.6 - Architectures of systems powered by energy harvesting: a) HarvestUse Architecture, and b) Harvest-Store-Use Architecture
Figure 2.7 - Main characteristics of energy storage units
Figure 2.8 - Relation between IEEE 802.15.6 and the others types of wireless
networks
Figure 2.9 - Illustration of the heterogeneity of the BNs in the BANs
Figure 2.10 - Medical WBANs: data transmission rates and average power
consumption, compared to other wireless technologies.
Figure 2.11 - Distribution of power consumption when a sampled signal is
transmitted by an ECG
Figure 2.12 - Power consumption of some operation modes in a wireless sensor

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Figure 2.13 - BNs connected to various energy harvesters in the human body:
(a) heartbeats (predictable source), (b) environmental light and temperature
difference (unpredictable sources) and (c) transcutaneous energy transfer

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(artificial source)
Figure 2.14 - System performance and energy consumption correlation in ENO
and ENO-MAX states
Figure 2.15 - Classification of MAC protocols

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Figure 2.16 - Contention-free multiple-access methods: (a) TDMA, (b) FDMA,
and (c) CDMA. Each BN in the network is represented by a different color and
number

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Figure 2.17 - Timing diagram of Aloha pure and slotted

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Figure 2.18 – Slotted CSMA, state transition diagram

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Figure 2.19 - Slotted CSMA, transmission timings

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Figure 2.20 – Unslotted CSMA, state transition diagram

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Figure 2.21 - Unslotted CSMA, flowchart of the backoff mechanism

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Figure 2.22 - ID-polling, state transition diagram

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Figure 2.23 - ID-polling, transmission timings

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Figure 2.24 - Probabilistic polling, pc updating algorithm

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Figure 2.25 - Mathematical representation AIMD, MIMD, AIAD, and MIAD
techniques for probabilistic polling protocol
Figure 2.26 - Comparison of AIMD, MIMD, AIAD, and MIAD techniques for
probabilistic polling (pUn = 0.01 ,pmi = 2, nd pmd = 0.5)
Figure 3.1- Health monitoring system network architecture
Figure 3.2 - Prototype WBAN sensors.

From left to right: eActiS with

electrodes, ActiS

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Figure 3.3 - Functional block diagram of Tmote Sky platform

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Figure 3.4 - Tmote Sky wireless platforms

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Figure 3.5 - Functional block diagram of the MSP430F1611

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Figure 3.6 - ISPM block diagram

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Figure 3.7 - ActiS sensor node – Tmote Sky with ISPM motion sensing
daughter card

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Figure 3.8 - ADXL202 PWM descriptions [ADXL202]

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Figure 3.9 - TinyOS timer interfaces

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Figure 3.10 - TinyOS TimerC configuration diagram

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Figure 4.1 - Healthcare trends

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Figure 4.2 - IoT health care network (IoThNet) issues

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Figure 4.3 - A conceptual diagram of IoT-based ubiquitous healthcare solutions.

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Figure 4.4 - Remote monitoring in wearables and personalized health care.

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