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1 online resource (553 pages) |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
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Intro -- CONTENTS -- Preface -- Chapter 1 - Markets and Applications -- 1.1 Technology at Crossroads -- 1.2 The Present - MEMS in the News -- 1.3 The Past - Great Expectations -- 1.4 The Future - Maturity and Pervasive Applications -- 1.5 Drivers for Progress -- 1.6 Progress - Device Improvement -- 1.7 Progress - Device Integration -- 1.8 Smart MEMS - The Research Agenda -- 1.9 Structure of the Book -- Chapter 2 - Microfabrication Technologies -- 2.1 Introduction -- 2.2 Passive Components -- 2.3 Sensing Components -- 2.4 Actuating Components -- 2.5 Materials and Growth -- 2.6 Fabrication Techniques -- 2.7 Conclusions -- Chapter 3 - Sensor Electronics -- 3.1 Introduction -- 3.2 Functions of a Sensor System -- 3.3 Analogue and Digital Design Options -- 3.4 Digital Signal Processing -- 3.5 Interface Configurations for Different Transducer Types -- 3.6 Integration -- 3.7 Design for Power Awareness -- 3.8 Conclusion -- Chapter 4 - Sensor Signal Enhancement -- 4.1 Errors in Sensor Systems and Measurement Quality (Non-linearity Cross-sensitivity Offset Parameter Drift) -- 4.2 Sensor Calibration and Compensation - Techniques and Examples -- 4.3 System Design Choices for Compensation - Closed Loop Configurations and other Designs -- 4.4 Summing up on Sensor Calibration and Compensation -- Chapter 5 - Case Study: Control Systems for Capacitive Inertial Sensors -- 5.1 Introduction -- 5.2 Open Loop Accelerometer -- 5.3 Closed Loop Accelerometer -- 5.4 Conclusions -- Chapter 6 - Case Study: Adaptive Optics and Smart VLSI/MEMS Systems -- 6.1 Introduction -- 6.2 Adaptive Optics and MEMS Systems -- 6.3 Operational Principles -- 6.4 Device Implementation -- 6.5 Closed-loop Adaptive Optical System -- 6.6 Conclusions and Future Trends -- Chapter 7 - Artificial Intelligence Techniques for Microsensors Identification and Compensation |
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7.1 Artificial Neural Networks: What They are and How They are Used for Microsensor Control and Identification -- 7.2 Open Loop Neural Transducer Prototype for Static/Low Frequency Applications -- 7.3 Closed-loop Neural Network Controlled Accelerometer -- 7.4 The Neural Network Non-linear Gain Controller -- 7.5 Micromachined Sensor Identification Using Neural Networks -- 7.6 Concluding Remarks -- Chapter 8 - Smart Intelligent and Cogent MEMS Based Sensors -- 8.1 Introduction -- 8.2 Smart Intelligent and Cogent Sensors - What do the Terms Mean -- 8.3 What and Where is the Added Value Brought by Intelligence? -- 8.4 ANNs and MEMS -- 8.5 AI for MEMS Intelligence -- 8.6 'Cogent' Sensors - Fault Detection Case Study -- 8.7 Conclusion -- Chapter 9 - Sensor Arrays and Networks -- 9.1 Potential of Sensor Arrays -- 9.2 Node Design -- 9.3 An Architectural History of Sensor Arrays and Networks -- 9.4 Systems Design Issues -- 9.5 Network Technology and Topology -- 9.6 Conclusion -- Chapter 10 - Wireless and Ad Hoc Sensor Networks -- 10.1 Sensor Network Applications -- 10.2 System Designers' Role -- 10.3 Design Assumptions for Ad hoc Networks -- 10.4 Distributed System Design Philosophy -- 10.5 Network Design Considerations -- 10.6 Layered Model -- 10.7 Sensor Network Operating Environments -- 10.8 Application Services -- 10.9 Proposed Sensor Support System Architecture -- 10.10 Conclusions -- Chapter 11 - Realising the Dream - A Case Study -- 11.1 Introduction -- 11.2 The Mission -- 11.3 Initial Rough Design -- 11.4 Sensor Technology -- 11.5 Deployment -- 11.6 Operation Control and Communication -- 11.7 Querying the Array -- 11.8 A Cogent Sensor -- 11.9 A World of Applications -- Index |
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In recent years, MEMS have revolutionized the semiconductor industry, with sensors being a particularly buoyant sector. Smart MEMS and Sensor Systems presents readers with the means to understand, evaluate, appreciate and participate in the development of the field, from a unique systems perspective. The combination of MEMS and integrated intelligence has been put forward as a disruptive technology. The full potential of this technology is only evident when it is used to construct very large pervasive sensing systems. The book explores the many different technologies needed to build such systems and integrates knowledge from three different domains: MEMS technology, sensor system electronics and pervasive computing science. Throughout the book a top-down design perspective is taken, be it for the development of a single smart sensor or that of adaptive ad-hoc networks of millions of sensors. For experts in any of the domains named above the book provides the context for their MEMS based design work and an understanding of the role the other domains play. For the generalist (either in engineering or computing) or the technology manager the underpinning knowledge is provided, which can inform specialist decision making. Sample Chapter(s). Chapter 1: Markets and Applications (1,731 KB). Contents: Markets and Applications; Microfabrication Technologies; Sensor Electronics; Sensor Signal Enhancement; Case Study: Control Systems for Capacitive Inertial Sensors; Case Study: Adaptive Optics and Smart VLSI/MEMS Systems; Artificial Intelligence Techniques for Microsensors Identification and Compensation; Smart, Intelligent and Cogent MEMS Based Sensors; Sensor Arrays and Networks; Wireless and Ad Hoc Sensor Networks; Realising the Dream - A Case Study. Readership: Graduate students on courses in sensing, instrumentation, VLSI, and MEMS technology; |
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researchers and academics dealing with smart sensor systems; practitioners who need to understand and apply the technology effectively |
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Description based on publisher supplied metadata and other sources |
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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2020. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries |
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Print version: Gaura, Elena Smart Mems And Sensor Systems
Singapore : World Scientific Publishing Company,c2006 9781860944932
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| Subject |
Microelectromechanical systems.;Smart structures
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Electronic books
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| Alt Author |
Newman, Robert
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Kraft, Michael
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Flewitt, Andrew
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Lima Monteiro, Davies
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