x
Preface
that record large amounts of data by measuring signals around the body. Wearables come
in several forms, such as wristbands, armbands, watches, and headbands. Chapter 2
explores the use of supervised and unsupervised learning techniques to identify individuals and activities using a commercially available wearable headband. It also deals with
applying machine learning techniques for identifying individuals and their activities that
are recorded through various wearable devices available in the market. A deep review on
various algorithms applied for sensor data generated by wearable devices is carried out.
Supervised and unsupervised learning algorithms are applied on EEG brain signal data
for classification. This chapter also discusses challenges involved in handling sensor data
and its mining.
IoT is a prototypical example of big data. In order to have viable solutions to that effect,
artificial intelligence (AI) techniques are considered to be the right choice. Hence, the IOT
system with AI techniques makes us to have smart applications like smart e-health, smart
metering, and smart city to name a few. Although IoT is gaining everybody’s attention
today, security aspects need to be effectively addressed to prevent an intruder from causing disastrous consequences. In Chapter 3, the problem of prediction of energy consumption data generated through the smart grid step to connect all power grids for efficient
energy management is discussed. The system applies convolution neural network and
addresses the challenges posed by the IoT datasets and is considered to have widespread
applications in the future digital world. The system is checked against publicly available
smart city, smart metering, and smart health.
Due to enormous growth in the various applications of IoT, it has the potential to replace
people as the largest producer and consumer of the Internet. The integration of wireless
communication, microelectromechanical devices, and Internet has led to the development
of things in the Internet. It is a network of network objects that can be accessed through
the Internet, and every object connected will have a unique identifier. The increasing
number of smart nodes and constant transfer of data are expected to create concerns
about data standardization, interoperability, security, protection and privacy, and other
issues. Chapter 4 elaborates on the technical, societal challenges and the impact of IoT
applications. With the increasing number of smart nodes and constant transfer of data,
it is expected to create concerns about data standardization, interoperability, security,
protection, and privacy. This chapter gives a detailed outlook at the issues related to software engineering and security in IoT, from which one can provide solutions based on its
understandings.
The social Internet of things (SIoT) is an emerging topic of the digital era with social,
economic, and technical significance. The IoT has already proved its dominance in a wide
range of sectors such as consumer products, durable goods, transportation, industrial
and utility components, and sensors. It is now extended to social media. The evolution
of powerful social network data analytic capabilities transforms the social livelihood into
a new era of link prediction, community grouping, recommendation systems, sentiment
analysis, and more. Chapter 5 covers the evolution of powerful social networking using
IoT. The present society is digitally progressing toward an ever connected paradigm. It
explains the basics of IoT and its technological evolution. The popularity of social networking describes the emergence of social network analytics in IoT. This chapter further discusses various security issues and research challenges pertaining to IoT analytics. It also
provides information and references for further research and developments in applications for those in pro-business and pro-people social IoT services.
It has been established that a habitual typing pattern is a behavioral biometric trait in
biometric science that relates to the issues in user identification/authentication systems.
Preface
that record large amounts of data by measuring signals around the body. Wearables come
in several forms, such as wristbands, armbands, watches, and headbands. Chapter 2
explores the use of supervised and unsupervised learning techniques to identify individuals and activities using a commercially available wearable headband. It also deals with
applying machine learning techniques for identifying individuals and their activities that
are recorded through various wearable devices available in the market. A deep review on
various algorithms applied for sensor data generated by wearable devices is carried out.
Supervised and unsupervised learning algorithms are applied on EEG brain signal data
for classification. This chapter also discusses challenges involved in handling sensor data
and its mining.
IoT is a prototypical example of big data. In order to have viable solutions to that effect,
artificial intelligence (AI) techniques are considered to be the right choice. Hence, the IOT
system with AI techniques makes us to have smart applications like smart e-health, smart
metering, and smart city to name a few. Although IoT is gaining everybody’s attention
today, security aspects need to be effectively addressed to prevent an intruder from causing disastrous consequences. In Chapter 3, the problem of prediction of energy consumption data generated through the smart grid step to connect all power grids for efficient
energy management is discussed. The system applies convolution neural network and
addresses the challenges posed by the IoT datasets and is considered to have widespread
applications in the future digital world. The system is checked against publicly available
smart city, smart metering, and smart health.
Due to enormous growth in the various applications of IoT, it has the potential to replace
people as the largest producer and consumer of the Internet. The integration of wireless
communication, microelectromechanical devices, and Internet has led to the development
of things in the Internet. It is a network of network objects that can be accessed through
the Internet, and every object connected will have a unique identifier. The increasing
number of smart nodes and constant transfer of data are expected to create concerns
about data standardization, interoperability, security, protection and privacy, and other
issues. Chapter 4 elaborates on the technical, societal challenges and the impact of IoT
applications. With the increasing number of smart nodes and constant transfer of data,
it is expected to create concerns about data standardization, interoperability, security,
protection, and privacy. This chapter gives a detailed outlook at the issues related to software engineering and security in IoT, from which one can provide solutions based on its
understandings.
The social Internet of things (SIoT) is an emerging topic of the digital era with social,
economic, and technical significance. The IoT has already proved its dominance in a wide
range of sectors such as consumer products, durable goods, transportation, industrial
and utility components, and sensors. It is now extended to social media. The evolution
of powerful social network data analytic capabilities transforms the social livelihood into
a new era of link prediction, community grouping, recommendation systems, sentiment
analysis, and more. Chapter 5 covers the evolution of powerful social networking using
IoT. The present society is digitally progressing toward an ever connected paradigm. It
explains the basics of IoT and its technological evolution. The popularity of social networking describes the emergence of social network analytics in IoT. This chapter further discusses various security issues and research challenges pertaining to IoT analytics. It also
provides information and references for further research and developments in applications for those in pro-business and pro-people social IoT services.
It has been established that a habitual typing pattern is a behavioral biometric trait in
biometric science that relates to the issues in user identification/authentication systems.