From simple thermistors to intelligent silicon microdevices with powerful capabilities to communicate information across networks, sensors play an important role in such diverse fields as biomedical and chemical engineering to wireless communications. Introducing a new dependent count method for frequency signal processing, this book presents a practical approach to the design of signal processing sensors. Modern advanced microsensors technologies require new and equally advanced methods of frequency signal processing in order to function at inreasingly high speeds. The authors provide a comprehensive overview of data acquisition and signal processing methods for the new generation of smart and quasi-smart sensors. The practical approach of the text includes coverage of the design of signal processing methods for digital, frequency, period, duty-cycle and time interval sensors. * Contains numerous practical examples illustrating the design of unique signal processing sensors and transducers * Details traditional, novel, and state of the art methods for frequency signal processing * Coverage of the physical characteristics of smart sensors, development methods and applications potential * Outlines the concept, principles and nature of the method of dependent count (MDC) ; a unique method for frequency signal processing, developed by the authors This text is a leading edge resource for measurement engineers, researchers and developers working in microsensors, MEMS and microsystems, as well as advanced undergraduates and graduates in electrical and mechanical engineering.

DAQ and data processing is a basic part of all automated production systems, diagnostic systems, watching over quality of production, energy distribution, transport control or in various other areas. Demands on the speed, accuracy and reliability increase in general. It is possible to achieve not only using superior (but also more expensive) hardware, but also applying advanced data acquisition and intelligent data processing. It deals e.g. optimal data fusion of a number of sensors, new stochastic methods for accuracy increasing, new algorithms for acceleration of data processing, etc. These are the grounds for publishing this book. Advanced Data Acquisition and Intelligent Data Processing offers 10 up-to-date examples of different applications of advanced data acquisition and intelligent data processing used in monitoring, measuring and diagnostics systems. The book arose based on the most interesting papers from this area published at IDAACS?2013 conference. However, the indivudual chapters include not only designed solution in wider context but also relevant theoretical parts, achieved results and possible future ways.Technical topics discussed in this book include: • advanced methods of data acquisition in application that are not routine;• measured data fusion using up-to-date advanced data processing;• nonlinear dynamical systems identification;• multidimensional image processing.Advanced Data Acquisition and Intelligent Data Processing is ideal for personnel of firms deals with advanced instrumentation, energy consumption monitoring, environment monitoring, non-descructive diagnostics robotics, etc., as well as academic staff and postgraduate students in electrical, control and computer engineering.Content: 1. Introduction; 2. Waveform acquisition with resolutions exceeding those of the ADC employed; 3. Different Disaggregation Algorithms in Non-Intrusive Home Energy Monitoring Systems; 4. Design and testing of an electronic nose system sensitive to the aroma of truffles; 5. DAQ System for Ultrasonic Transducer Evaluation under Spread Spectrum Excitation; 6. Optimal Data Fusion in Decentralized Stochastic Unknown Input Observers; 7. Odor Classification by Neural Networks; 8. ANFIS Based Approach for Improved Multisensors Signal Processing; 9. Neuro-Fuzzy Sensor's Linearization Based FPGA; 10. Interpolation Method of Nonlinear Dynamical Systems Identification Based on Volterra Model in Frequency Domain ; 11. Training Cellular Automata for Hyperspectral Image Segmentation

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts.

With contributions from an internationally-renowned group of experts, this book uses a multidisciplinary approach to review recent developments in the field of smart sensor systems, covering important system and design aspects. It examines topics over the whole range of sensor technology from the theory and constraints of basic elements, physics and electronics, up to the level of application-orientated issues. Developed as a complementary volume to ‘Smart Sensor Systems’ (Wiley 2008), which introduces the basics of smart sensor systems, this volume focuses on emerging sensing technologies and applications, including: State-of-the-art techniques for designing smart sensors and smart sensor systems, including measurement techniques at system level, such as dynamic error correction, calibration, self-calibration and trimming. Circuit design for sensor systems, such as the design of precision instrumentation amplifiers. Impedance sensors, and the associated measurement techniques and electronics, that measure electrical characteristics to derive physical and biomedical parameters, such as blood viscosity or growth of micro-organisms. Complete sensor systems-on-a-chip, such as CMOS optical imagers and microarrays for DNA detection, and the associated circuit and micro-fabrication techniques. Vibratory gyroscopes and the associated electronics, employing mechanical and electrical signal amplification to enable low-power angular-rate sensing. Implantable smart sensors for neural interfacing in bio-medical applications. Smart combinations of energy harvesters and energy-storage devices for autonomous wireless sensors. Smart Sensor Systems: Emerging Technologies and Applications will greatly benefit final-year undergraduate and postgraduate students in the areas of electrical, mechanical and chemical engineering, and physics. Professional engineers and researchers in the microelectronics industry, including microsystem developers, will also find this a thorough and useful volume.

This book describes the fundamentals of data acquisition systems, how they enable users to sample signals that measure real physical conditions and convert the resulting samples into digital, numeric values that can be analyzed by a computer. The author takes a problem-solving approach to data acquisition, providing the tools engineers need to use the concepts introduced. Coverage includes sensors that convert physical parameters to electrical signals, signal conditioning circuitry to convert sensor signals into a form that can be converted to digital values and analog-to-digital converters, which convert conditioned sensor signals to digital values. Readers will benefit from the hands-on approach, culminating with data acquisition projects, including hardware and software needed to build data acquisition systems.

Discusses state-of-the-art and the realization of the integrated device to test the amplification proposal of a synthetic nucleic acid template. It covers the control algorithm for designing the Maximum Power Point Tracker (MPPT) enabled electrical interface system. Discusses designing and generating new metasurface antenna for future applications. Covers integration of optical structures with MEMS devices for implementation in Photonic Integrated Circuits. Presents state-of-art in-exact multiplier architectures and their efficient implementation.

The Signal Conditioning Handbook is a 144-page guide to making sensor-based measurements using PC-based data acquisition equipment. The latest revision has expanded coverage to include new sensor types that have emerged since the last publication, as well as expanded coverage of additional topics including:?Analog to Digital Conversion?Multiplexing?Electrical Measurements?Fundamental Signal Conditioning?Temperature Measurement?Strain Measurements?Vibration and Sound?Displacement and Position Sensing?Noise Reduction and Isolation?Digital and Pulse Train Signal Conditioning?Transducer Electronic Data Sheets