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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
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.
This book offers a timely yet comprehensive snapshot of innovative research and developments at the interface between manufacturing, materials and mechanical engineering, and quality assurance. It covers a wide range of manufacturing processes, such as cutting, grinding, assembly, and coatings, including ultrasonic treatment, molding, radial-isostatic compression, ionic-plasma deposition, volumetric vibration treatment, and wear resistance. It also highlights the advantages of augmented reality, RFID technology, reverse engineering, optimization, heat and mass transfer, energy management, quality inspection, and environmental impact. Based on selected papers presented at the Grabchenko’s International Conference on Advanced Manufacturing Processes (InterPartner-2020), held in Odessa, Ukraine, on September 8–11, 2020, this book offers a timely overview and extensive information on trends and technologies in production planning, design engineering, advanced materials, machining processes, process engineering, and quality assurance. It is also intended to facilitate communication and collaboration between different groups working on similar topics and offer a bridge between academic and industrial researchers.
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.
This book highlights original research and recent advances in various fields related to smart cities and their applications. Bringing together new contributions by prominent researchers from around the globe, the book is a rich pedagogical tool and an inspiring research support for courses on computer science, electrical engineering, and urban sciences. The book gathers papers presented at the 7th International Conference on Smart City Applications (SCA 2022), held on October 19–21, 2022, in Castelo Branco, Portugal. The technical program of SCA 2022 consisted of 80 papers. The keynote speakers were Eng. Loide Monteiro (Foundation Smart City Cape Verde), Prof. Teodora Vuckovic (University of Novi Sad), Prof. Susana Sargento (University of Aveiro), Prof. Andy Van Den Dobblesteen (TU Delft), and Prof. Juan Corchado (University of Salamanca). SCA 2022 provided a good forum for all researchers to discuss all aspects of science and technology that are relevant to smart city applications.
This Special Issue presents the recent advances in sensor technologies for smart homes, including fiber Bragg grating (FBG) sensors for detecting the presence and number of occupants, the Internet of things for monitoring CO2 concentration, and designing a novel eye-tracking system for monitoring and controlling a smart home, and infrared thermal sensors for fall detection. Such new explorations are pushing the boundary of sensing technologies and, thus, will have more profound implications for the future smart home. Advanced machine learning and data mining algorithms have been proposed to address sensor failure, appliance identification, and human activity recognition in a home environment. These results will enable a promising, sustainable deployment of sensing technologies. A novel multi-agent gamification system is proposed for managing tasks between household members and between families, which demonstrate another dimension of future smart home application. This Special Issue concludes with a review on sensors for human activity recognition. This work paves the roadmap for deploying smart home systems in different socioeconomic contexts. The whole Special Issue has significantly helped to shape our understanding of the strength, implications, and barriers of deploying long-term, sustainable, sensor technologies for smart homes.
This book brings new smart farming methodologies to the forefront, sparked by pervasive applications with automated farming technology. New indigenous expertise on smart agricultural technologies is presented along with conceptual prototypes showing how the Internet of Things, cloud computing, machine learning, deep learning, precision farming, crop management systems, etc., will be used in large-scale production in the future. The necessity of available welfare systems for farmers’ well-being is also discussed in the book. It draws the conclusion that there is a greater need and demand today for smart farming methodologies driven by technology than ever before.
Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services. It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality. In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS - Contains contributions from noted scholars in computer science and electrical engineering from around the globe - Provides a broad overview of recent developments in sensor collected intelligence - Edited by a team comprised of leading thinkers in big data analytics
The objective of the conference is to bring to focus the recent technological advancements across all the stages of data analysis including acquisition, processing, and communication. Advancements in acquisition sensors along with improved storage and computational capabilities, have stimulated the progress in theoretical studies and state-of-the-art real-time applications involving large volumes of data. This compels researchers to investigate the new challenges encountered, where traditional approaches are incapable of dealing with large, complicated new forms of data.