Название: Sensors for Next-Generation Electronic Systems and Technologies
Автор: P. Uma Sathyakam, K. Venkata Lakshmi Narayana
Издательство: CRC Press
Год: 2023
Страниц: 295
Язык: английский
Формат: pdf (true)
Размер: 67.8 MB

The text covers fiber optic sensors for biosensing and photo-detection, graphene and CNT-based sensors for glucose, cholesterol, and dopamine detection, and implantable sensors for detecting physiological, bio-electrical, biochemical, and metabolic changes in a comprehensive manner. It further presents a chapter on sensors for military and aerospace applications. It will be useful for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communication engineering.

The main aspect of this book is to introduce new technologies in the field of sensors leveraging on the latest advancements in electronic materials and devices. This book definitely will be interesting to the readers and researchers who are fascinated to explore the future of sensors in various domains spanning from healthcare to space applications. In this modern world, sensors have impacted many areas of our daily life in the form of smart technology implementations. Even though there have been sensor applications explored in different domains, there is a need for a single platform, where the basic elements of modern day sensors with current technological advancement integrated with sensor development in different fields is covered. This markedly benefits beginners as well as domain experts in acquiring an overview of the advancement in sensor development and applications.

The book covers the various sensor technologies related to niche areas, like wearable technologies, healthcare monitoring, military and aerospace applications, nanomaterials like CNTs and Graphene, intelligent sensors, sensor arrays, sensors for flexible electronics, on-chip sensors for SoC, SoP, sensors for Lab-on-a-chip (LoC), magnetic sensors, smart sensors and, thermal sensors Hence, this book provides an interdisciplinary platform for researchers and promotes the research development in the above mentioned areas. Most of the reported findings in the areas of sensors are the motivation behind the IoT and telecommunication industry and special emphasis on signal processing and control automation that are helping to change the nature of human life. We are sure that the novel findings in the research chapters contained in this book will be found exciting and may inspire the research fraternity to work in the field of Sensors and Electronics. We foresee that this book is an initiative to integrate different domains of sensors into a single platform that can bring a great contribution to academic as well as industrial research.

Neural networks have been extensively used to add intelligence to sensors. Linearization, self- calibration or extension of the range of the sensor is also performed using ANNs in various studies. The universal approximation properties of feed forward neural networks allow us to create virtual sensors where output through the neural network model would supply the output as if it were the physical sensor without the parametrical losses and investment of the said sensor. A neural network model is preferred over statistical methods on account of outperforming, including capacity to learn from exemplars, plasticity of architecture, parallel computation, fault tolerant, robustness to noise, and ease of implementation on hardware environments such as the FPGA.

The book:

Discusses implantable sensors for detecting physiological, bio-electrical, biochemical, and metabolic changes
Covers applications of sensors in diverse fields including healthcare, industrial flow, consumer electronics, and military
Includes experimental studies such as the detection of biomolecules using SPR sensors and electrochemical sensors for biomolecule detection
Presents artificial neural networks (ANN) based industrial flow sensor modeling
Highlights case studies on surface plasmon resonance sensors, MEMS-based fluidic sensors, and MEMS-based electrochemical gas sensors

The text presents case studies on surface plasmon resonance sensors, MEMS-based fluidic sensors, and MEMS-based electrochemical gas sensors in a single volume. The text will be useful for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communication engineering.