ix
Preface
Internet of Things (IoT) is the third wave of Internet and is supposed to have a potential
to connect about 28 billion items by 2020, ranging from bracelets to cars. The term “IoT,”
which was first proposed by Kevin Ashton, a British technologist, in 1999, has the potential
to impact everything from new product opportunities to shop floor optimization to factory worker efficiency gains that will power top-line and bottom-line gains. It is believed
that IoT will improve energy efficiency, remote monitoring, and control of physical assets
and productivity through applications as diverse as home security to condition monitoring on the factory floor. Now IoT has been used in markets in the field of health care, home
appliances and buildings, retail markets, energy and manufacturing companies, mobility
and transportation, logistics companies, and by media.
Equipments are becoming more digitized and more connected, establishing networks
between machines, humans, and the Internet, leading to the creation of new ecosystems
that enable higher productivity, better energy efficiency, and higher profitability. Sensors
help to recognize the state of things, by which they gain the advantage of anticipating
human needs based on the information collected per context. These intelligent devices
not only gather information from their environment but are also capable of taking decisions without human intervention. IoT technology is being used in our day-to-day life for
unlocking the door without a key; in card recognizers, automatic locks, vehicle detecting
systems, toll payment system; and for tracking animals, access control, payment systems,
contactless smart cards, anti-theft devices, steering column reader, etc. The IoT building
blocks will come from those that are web-enabled devices, providing common platforms
on which they can communicate, and develop new applications to capture new users.
In this background, this book is an attempt to present updated information on the
recent trends on the issues involved, highlighting the challenges involved, and source the
solutions for some of these challenges. The book comprises 14 chapters. The chapterwise
description of contents in the volume is as follows.
For seamless visual tracking of passengers traveling in a vehicle, the visual light transmission (VLT) and visual light reflectance (VRT) values of the glass windows used in the
vehicle should be at a particular value. All vehicle manufacturers follow certain standards.
But the vehicle owner/user generally buys window-tinting films from the gray market
and pastes the same on the glass windows, which in turn hamper the visibility, thereby
preventing the law enforcement authorities from having a clear view of those traveling
in the vehicle. In Chapter 1, a proposal for the automatic detection of tint level for vehicles is presented. The system has been designed using ordinary cameras that work in
the visible region of the electromagnetic spectrum. The system is capable of identifying a
vehicle’s registered number using algorithms developed for this purpose. Various filtering
techniques are applied to find the level of tint from the captured camera images. Using
three different techniques, namely, color segmentation, contour detection, and histogram
analysis, the tint level of windshield/window region is estimated. Thus, the IoT system
recognizes the numbers on the number plate and can fetch the contact details of the owner
from the database. It also communicates the same information to the owner with details
on and extent of tint level violation along with documentary evidence.
Supervised and unsupervised learning techniques are reliable tools for the classification
and categorization of data. Wearable devices are a relatively recent consumer technology
Preface
Internet of Things (IoT) is the third wave of Internet and is supposed to have a potential
to connect about 28 billion items by 2020, ranging from bracelets to cars. The term “IoT,”
which was first proposed by Kevin Ashton, a British technologist, in 1999, has the potential
to impact everything from new product opportunities to shop floor optimization to factory worker efficiency gains that will power top-line and bottom-line gains. It is believed
that IoT will improve energy efficiency, remote monitoring, and control of physical assets
and productivity through applications as diverse as home security to condition monitoring on the factory floor. Now IoT has been used in markets in the field of health care, home
appliances and buildings, retail markets, energy and manufacturing companies, mobility
and transportation, logistics companies, and by media.
Equipments are becoming more digitized and more connected, establishing networks
between machines, humans, and the Internet, leading to the creation of new ecosystems
that enable higher productivity, better energy efficiency, and higher profitability. Sensors
help to recognize the state of things, by which they gain the advantage of anticipating
human needs based on the information collected per context. These intelligent devices
not only gather information from their environment but are also capable of taking decisions without human intervention. IoT technology is being used in our day-to-day life for
unlocking the door without a key; in card recognizers, automatic locks, vehicle detecting
systems, toll payment system; and for tracking animals, access control, payment systems,
contactless smart cards, anti-theft devices, steering column reader, etc. The IoT building
blocks will come from those that are web-enabled devices, providing common platforms
on which they can communicate, and develop new applications to capture new users.
In this background, this book is an attempt to present updated information on the
recent trends on the issues involved, highlighting the challenges involved, and source the
solutions for some of these challenges. The book comprises 14 chapters. The chapterwise
description of contents in the volume is as follows.
For seamless visual tracking of passengers traveling in a vehicle, the visual light transmission (VLT) and visual light reflectance (VRT) values of the glass windows used in the
vehicle should be at a particular value. All vehicle manufacturers follow certain standards.
But the vehicle owner/user generally buys window-tinting films from the gray market
and pastes the same on the glass windows, which in turn hamper the visibility, thereby
preventing the law enforcement authorities from having a clear view of those traveling
in the vehicle. In Chapter 1, a proposal for the automatic detection of tint level for vehicles is presented. The system has been designed using ordinary cameras that work in
the visible region of the electromagnetic spectrum. The system is capable of identifying a
vehicle’s registered number using algorithms developed for this purpose. Various filtering
techniques are applied to find the level of tint from the captured camera images. Using
three different techniques, namely, color segmentation, contour detection, and histogram
analysis, the tint level of windshield/window region is estimated. Thus, the IoT system
recognizes the numbers on the number plate and can fetch the contact details of the owner
from the database. It also communicates the same information to the owner with details
on and extent of tint level violation along with documentary evidence.
Supervised and unsupervised learning techniques are reliable tools for the classification
and categorization of data. Wearable devices are a relatively recent consumer technology