Название: Cognitive Sensors: Intelligent sensing, sensor data analysis and applications (Volume 1)
Автор: G.R. Sinha, Varun Bajaj
Издательство: IOP Publishing
Серия: IOP Series in Sensors and Sensor Systems
Год: 2023
Страниц: 278
Язык: английский
Формат: pdf (true), epub
Размер: 44.0 MB

Cognitive sensors and associated Artificial Intelligence (AI) and algorithms are most important components of cognitive science research and studies. This book provides a critical review of the emerging themes of cognitive sensors, how it functions and its applications in a range of disciplines. Volume I includes Sensor Physics, Imaging, Modalities, Pre-processing of images, Problems and Issues in Cognitive Sensing techniques, Cognitive Sensors and IoTs, Psychological, Philosophical and Linguistic Studies of Cognitive Science; Humanoid robots, Industrial Robots and intelligence, Cognitive Sensor Network and applications. This book presents a brilliant introduction to Cognitive Sensors for industrial and academic researchers in sensor science and technology, smart systems, Internet of Things, and biomedical engineering. Part of IOP Series in Sensors and Sensor Systems.

Cognitive sensors have become essential parts of a number of Internet of Things (IoT) devices and modern gadgets. In fact, the sensors which behave and act smartly in all modern applications are cognitive sensors. Sensors that have the ability to understand and interpret the data they sense, with the help of signal processing and machine learning techniques, are known as cognitive sensors. Cognitive sensors are heavily used in healthcare applications, smart city smart transport, smart manufacturing, smart automobiles, and a number of other such applications in which automation is achieved using sensor-based data and the analysis of sensor-based data using Artificial Intelligence (AI)-based approaches.

In the modern world, computer vision is dominating all advances and their applications in science, engineering, and technology; for example, computer-aided diagnosis, industrial robotics, driverless cars, the brain–computer interface (BCI), human-computer interaction (HCI), telemedicine, etc. are emerging areas in which computer vision plays a significant role in implementing, simulating, and improving their performance. Cognitive Science is actually a multidisciplinary area of research that mainly covers artificial intelligence, neuroscience, mathematics, philosophy, psychology, linguistics, which are the building blocks of humanoid robots, automated diagnosis, self-driving cars, etc. Cognitive sensors are most important components of cognitive science research and studies. For example, brain images such as those produced using electroencephalography (EEG) dominate among a number of other brain signal modalities; they are used in the analysis and study of various types of brain disorder and disability. In the computing part of cognitive science related to physics and images, a number of signal processing and soft computing techniques are used to make images for suitable applications. Cognitive sensors are basically smart and intelligent sensors that have the ability to exploit cognitive aspects of science and engineering, namely understanding, decision-making, improving, adapting to requirements, computing, etc.

In this volume of the book, we focus on smart sensors, the data captured by these sensors and its analysis, an overview of the different types of cognitive sensor, their characteristics, uses, and their potential applications. The readers of this book will gain an understanding of cognitive sensors, their fundamentals, their scope, and the possible applications in which cognitive sensors can play a significant role in smart sensing and decision-making. This volume takes 11 chapters to cover the complete scope of the book; a chapter-by-chapter description of this book as follows:
Chapter 1 presents and insight into various types of application areas in which cognitive IoT devices provide enhanced user experiences and smart features that are critical and essential to making human life safe and secure. Chapter 2 presents various applications and advantages of various sensors used in today’s scenarios; for example, cognitive wireless sensor networks (CWSNs) are widely used for various military purposes, public security, healthcare, home appliances, real-time surveillance, transportation networks, etc. Chapter 3 discusses the role of sensors in cases of moderate COVID-19 infection that may be linked to cognitive impairments; such prediction systems are promising for smart healthcare design. Chapter 4 presents various facets of cognitive IoT devices used in smart sensing, including their architectures and applications in different fields such as healthcare, the military, intelligent home applications, and cognitive radio. Chapter 5 provides an overview of wireless sensor network (WSN) design challenges and additional design issues that need to be addressed in making them cognitive WSNs. Chapter 6 highlights CWSNs and discusses enhancing the communication flow range, diminishing the sensor node as required to cover a definite neighborhood, and working toward reduced power utilization. Chapter 7 presents the use of cognitive IoT devices for healthcare that can take intelligent decisions based on the physical state of the patient. Chapter 8 discusses various types of redundancy and presents a survey of the most recent studies which have aimed to minimize the effect of redundancy on WSN performance. Chapter 9 discusses the roles and capabilities of sensors, communication networks, and cloud storage in healthcare systems. Chapter 10 focuses on the important issue of interference and elucidates the different EMF radiation limit guidelines applicable worldwide. It also describes an experimental study that has been conducted in order to discover the effects of EMF in a college premises. Chapter 11 analyses the advances in the field of cognitive sensing using the BCI and provides the reader with a very insightful take on the topic to foster more research in this direction.

The structure of the book is arranged in such a way that the reader will easily understand the different topics covered in different chapters. Thus, the basic understanding of the fundamentals is discussed in the early chapters, which provide an overview, a necessary discussion, and a description of the possible applications. This is followed by the major challenges facing the implementation strategies used for WSNs; finally, cognitive sensing and its utilization in smart applications are discussed. We believe that the reader will enjoy learning about cognitive sensors using a different, case-study-based approach.