Understand multi-sensor fusion--the most sophisticated way to deliver accurate real-world data to computer systems. Applications include aviation, medicine, military, manufacturing, and transportation. The Sensor Fusion Toolkit on disk contains C programs discussed in the book and supports each section.

Neuromorphic engineering has just reached its 25th year as a discipline. In the first two decades neuromorphic engineers focused on building models of sensors, such as silicon cochleas and retinas, and building blocks such as silicon neurons and synapses. These designs have honed our skills in implementing sensors and neural networks in VLSI using analog and mixed mode circuits. Over the last decade the address event representation has been used to interface devices and computers from different designers and even different groups. This facility has been essential for our ability to combine sensors, neural networks, and actuators into neuromorphic systems. More recently, several big projects have emerged to build very large scale neuromorphic systems. The Telluride Neuromorphic Engineering Workshop (since 1994) and the CapoCaccia Cognitive Neuromorphic Engineering Workshop (since 2009) have been instrumental not only in creating a strongly connected research community, but also in introducing different groups to each other’s hardware. Many neuromorphic systems are first created at one of these workshops. With this special research topic, we showcase the state-of-the-art in neuromorphic systems.

Motor monitoring, incipient fault detection, and diagnosis are important and difficult topics in the engineering field. These topics deal with motors ranging from small DC motors used in intensive care units to the huge motors used in nuclear power plants. With proper machine monitoring and fault detection schemes, improved safety and reliability can be achieved for different engineering system operations. The importance of incipient fault detection can be found in the cost saving which can be obtained by detecting potential machine failures before they occur. Non-invasive, inexpensive, and reliable fault detection techniques are often preferred by many engineers. A large number of techniques, such as expert system approaches and vibration analysis, have been developed for motor fault detection purposes. Those techniques have achieved a certain degree of success. However, due to the complexity and importance of the systems, there is a need to further improve existing fault detection techniques.A major key to the success in fault detection is the ability to use appropriate technology to effectively fuse the relevant information to provide accurate and reliable results. The advance in technology will provide opportunities for improving existing fault detection schemes. With the maturing technology of artificial neural network and fuzzy logic, the motor fault detection problem can be solved using an innovative approach based on measurements that are easily accessible, without the need for rigorous mathematical models. This approach can identify and aggregate the relevant information for accurate and reliable motor fault detection. This book will introduce the neccessary concepts of neural network and fuzzy logic, describe the advantages and challenges of using these technologies to solve motor fault detection problems, and discuss several design considerations and methodologies in applying these techniques to motor incipient fault detection.

This book is written for academic and professional researchers designing communication systems for pervasive and low power applications. There is an introduction to wireless sensor networks, but the main emphasis of the book is on design techniques for low power, highly integrated transceivers. Instead of presenting a single design perspective, this book presents the design philosophies from three diverse research groups, providing three completely different strategies for achieving similar goals. By presenting diverse perspectives, this book prepares the reader for the countless design decisions they will be making in their own designs.

Biological and Medical Sensor Technologies presents contributions from top experts who explore the development and implementation of sensors for various applications used in medicine and biology. Edited by a pioneer in the area of advanced semiconductor materials, the book is divided into two sections. The first part covers sensors for biological applications. Topics include: Advanced sensing and communication in the biological world DNA-derivative architectures for long-wavelength bio-sensing Label-free silicon photonics Quartz crystal microbalance-based biosensors Lab-on-chip technologies for cell-sensing applications Enzyme biosensors Future directions for breath sensors Solid-state gas sensors for clinical diagnosis The second part of the book deals with sensors for medical applications. This section addresses: Bio-sensing and human behavior measurements Sweat rate wearable sensors Various aspects of medical imaging The future of medical imaging Spatial and spectral resolution aspects of semiconductor detectors in medical imaging CMOS SSPM detectors CdTe detectors and their applications to gamma-ray imaging Positron emission tomography (PET) Composed of contributions from some of the world’s foremost experts in their respective fields, this book covers a wide range of subjects. It explores everything from sensors and communication systems found in nature to the latest advances in manmade sensors. The end result is a useful collection of stimulating insights into the many exciting applications of sensor technologies in everyday life.