Distributed Sensor Systems E-Book

Habib F. Rashvand

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 614

Veröffentlichungsjahr: 2012

Beschreibung

This book focuses on the distinct but tightly inter-related areas of development for distributed sensing systems In this book, the authors discuss the technological developments lead by sensor technology, addressing viable new applications to inspire a technological evolution. Under the advanced and visionary approach of distributed intelligence, the authors focus on three distinct but tightly inter-related areas of developments for distributed sensing systems (DSS): firstly, the sensor technology embracing the conversion of the phenomena of interest into desirable form of signal such as electric, secondly, the interaction process between sensing points which requires immense intelligence loosely called networking, and finally, the adoption of useful maturing systems through potential applications for right impacts for a better life and a brighter economy. Furthermore, the book contains a number of case studies and typical applications illustrating the technical details, features and functions of the systems, as well as demonstrating their benefits and limitations. Key Features: * Discusses the technological developments lead by sensor technology * Addresses viable new applications * Contains a number of case studies and typical applications illustrating the technical details, features and functions of the systems * Demonstrates the benefits and limitations of distributed sensing * Written by experts with vast experience in the field (both in academia and industry) This book will be an invaluable reference for postgraduates studying related courses (communication engineering, engineering management, computer systems, industrial process, automation, design, environmental, urban, surveillance), R&D engineers, system and application designers, researchers, industrial project managers and engineers, and technical and strategic managers planning new products.

Leseprobe

Table of Contents

Title Page

Copyright

Dedication

List of Figures

List of Tables

Preface

Acknowledgements

List of Abbreviations

Chapter 1: Distributed Sensors

1.1 Primary Objectives

1.2 Historical Development

1.3 Trends and Technology

1.4 Distributed Intelligence

1.5 Classifying Application Areas

Chapter 2: Smart Sensing Devices

2.1 Specification and Classification

2.2 Elementary Sensing Circuits and Devices

2.3 Actuator Interface Structures

2.4 Physical Phenomena Sensing Devices

2.5 Biological and Chemical Phenomena Sensing Devices

2.6 Other Sensors and Actuators

Chapter 3: Smart Sensing Architectures

3.1 Smart Sensor Nodes

3.2 Embedded Operating Systems

3.3 Network Formation

3.4 Networking Protocols

3.5 Cross-Layer Optimisation

3.6 Inference and Aggregation

3.7 Case Study: Smart Camera Networks

3.8 Case Study: Collaborative Beamforming

Chapter 4: Monitoring Well Being

4.1 Measuring Health

4.2 Managing Chronic Diseases

4.3 Case Study: Smart Shirts

4.4 Case Study: Geriatric Care

4.5 Case Study: Outpatient Care

Chapter 5: Clinical Applications

5.1 Surgical Applications

5.2 Dental Applications

5.3 Scalp Applications

5.4 Post-Operative Applications

5.5 Emergency Case Studies

Chapter 6: Smart Home, Smart Office

6.1 Application Requirements

6.2 Energy and Resource Optimisation

6.3 Smart Home Case Studies

6.4 Smart Office Case Studies

Chapter 7: Public Safety Applications

7.1 Monitoring Airborne Toxins

7.2 Monitoring Forest Fires

7.3 Monitoring Structural Health

7.4 Monitoring Traffic

7.5 Case Study: Sink Location

7.6 Case Study: Congestion Avoidance

7.7 Case Study: Target Tracking and Surveillance

Chapter 8: Geographical Applications

8.1 Farming Industry

8.2 Mining Industry

8.3 Transportation

8.4 Remote Sensing and Imaging

8.5 Earth Resources Observation

8.6 Underwater Sensing

Appendix A: Further Details on Potential Devices and Systems

A.1 Accelerometers

A.2 Equipment

A.3 Smart Sensors Devices

A.4 Networks and Protocols

A.5 Systems

References

Index

Distributed Sensor Systems: Practice and Applications

This edition first published 2012

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Library of Congress Cataloging-in-Publication Data

Rashvand, Habib F.

Distributed sensor systems : practice and applications / Habib F. Rashvand, Jose M. Alcaraz Calero.

p. cm.

Includes bibliographical references and index.

ISBN 978-0-470-66124-6 (cloth)

1. Sensor networks--Design and construction. 2. Sensor networks--Industrial applications. I. Alcaraz Calero, Jose M. II. Title.

TK7872.D48R37 2012

681′.2–dc23

2011051663

A catalogue record for this book is available from the British Library.

Print ISBN: 9780470661246

To Liz, Leila, Cyrus and Joan

List of Figures

Figure 1.1Historical developments of three generations of sensor: TST, SSD and DSS. The graphs are their estimated market viabilityFigure 1.2The telemedicine cross-road opportunityFigure 1.3Smart home environment application, an example of adopting intelligence at homeFigure 1.4Kondratiev's long waves are accompanied by three technological revolutions. The symbols indicate inventions, innovations and bundling new technologiesFigure 1.5The operational flowchart showing the main process involved in Convergence, Divergence Ubiquitous Access (CDUA) algorithmFigure 2.1Three-level device structure design associated with three sensor generations of Chapter 1Figure 2.2Basic application-based classification of sensor devicesFigure 2.3Using a capacitor as a sensing device, where the formula shows the relationship between surface, distance and capacityFigure 2.4A typical switched capacitor and implementation of the capacitance sensingFigure 2.5Diagram of the different modules provided by a power gating processor (Seok et al., 2010)Figure 2.6The 2T (on the left) and 4T (on the right) voltage referencesFigure 2.7Power efficiency of the SCN DC-DC converterFigure 2.8Typical ubiquitous core functional block diagramFigure 2.9Service viewer and controller using a smart-phoneFigure 2.10Actuation principle of elastomeric material. (a) Without actuation; (b) With actuation © 2006 IEEE. Reprinted, with permission, from Koo et al (2006) Wearable Tactile Display based on Soft ActuatorFigure 2.11Wearable Tactile: (a) Various applications on the finger, (b) FabricationFigure 2.12Integrated optical nanowire as an optical sensor-on-a-chip solution. © 2011 IEEE. Reprinted, with permission, from Daoxin and Sailing (2011) Ultracompact Silicon Nanowire Circuits for Optical Communication and Optical SensingFigure 2.13Typical CCD image sensor circuit boardFigure 2.14Circuit configuration of an operational amplifier using the common-drain VI-CMOS technologyFigure 2.15Diagrams of CMOS sensor basic operations: (a) Multiplication of two inputs by the photocurrent, (b) Logarithmic intensity compensationFigure 2.16Capacitance sensors used to detect the presence of variety of biological materials from protein or antibodies to cellsFigure 2.17Family of wearable chest belt sensor systemsFigure 2.18Data signals gathered from a person in two cases of (a) Running and (b) Resting on the treadmillFigure 2.19A prototype for chemical micro fluidics sensing applications: (a) The prototype, (b) Finite element design filter and (c) The laser machined micro fluidic channelsFigure 2.20Diagram of various wireless standards of RFID and associated technologiesFigure 2.21Barcode used as a sweat pH reader: (a) Whole system using four indicator dyes and their pH activity range; (b) Barcode fabrication processFigure 2.22Schematic diagram showing the optically enhanced acoustic sensor where a built in phase-sensitive diffraction detector transfers the displacement caused by the acoustic pressure onto the photodiodes. (Qureshi et al., 2010)Figure 2.23For a hearing aid application scenario the transceiver circuit consists of an optical pulse generator and the process of combining a pair of two sensors, an optical and a mechanical (MEMS) coupled togetherFigure 2.24Components of optical MEMS application: (a) VCSEL pulse source; (b) The band-pass filter and the low-pass filter; and (c) The coherent and envelope detectors, repeatedlyFigure 3.1Block diagram of a typical chest belt sensor device (Huang et al., 2009)Figure 3.2Sensor placement in a prototype of a fabric belt with sensing capabilities (Huang et al., 2009)Figure 3.3Block diagram structure of Cicada 3.0 devices (Pei et al., 2008)Figure 3.4Some hardware parts integrated in Cicada 1.0 WSN nodes (Pei et al., 2008)Figure 3.5Infrastructure to help the deployment of sensing devicesFigure 3.6Example of a two-tier network topologyFigure 3.7Protocol stack for ZigBee protocol (Pei et al., 2008)Figure 3.8Wibree protocol stack with Bluetooth (Pei et al., 2008)Figure 3.9Hierarchical network architecture for monitoring health using a wearable sensing system (Huang et al., 2009)Figure 3.10Common node placement classes (Younis and Akkaya, 2008)Figure 3.11Relay Region defined in the routing protocol MECN for delimiting a power efficient area for packet transmission (Rodoplu and Ming, 1999)Figure 3.12Steps involved in the SPIN routing protocol and the associated type of propagation (Kulik et al., 2002)Figure 3.13Phases of the Directed Fusion protocol (Intanagonwiwat et al., 2003). (a) Interest propagation; (b) Initial gradients setup; (c) Data delivery along reinforcedFigure 3.14Layout of a basic cluster, where there are two level of cluster headsFigure 3.15Example scenario where a Virtual Grid is built with both local and master aggregatorsFigure 3.16Example Scenario for Data Mule routing protocolFigure 3.17Common Congestion Control mechanism using two queues between MAC and Network layers (Wang et al., 2007)Figure 3.18Scheme, in which a two level routing aggregation process is shown for improving energy and interferenceFigure 3.19Waterfall sensor fusion processFigure 3.20Basic loop of observe, orient, decide and act in which it can be seen how data is interconnected along the different steps of the loopFigure 3.21Comparison of delay time behaviours of three common signal processing methods for reconstructing samples sensor fusion: (a) Smoothing; (b) Filtering; (c) PredictionFigure 3.22Sample scenario where a distributed sensor system for video surveillance is deployedFigure 3.23A typical antenna gain pattern showing various beam lobesFigure 3.24Core adaptive filtering of the acoustic/audio beam formerFigure 3.25Graph in which a core beam former pattern can be seenFigure 4.1Firefly motion tracking system architecture for tracking human movementFigure 4.2Optotrak tracking system integrated into cars and road-side devicesFigure 4.3Combination of ultrasound and RF technologies in an example scenarioFigure 4.4Smart-shirt developed in the magic system for health monitoringFigure 4.5Pattern of shirt where placement of the fabric electrodes for the ECG acquisition are shownFigure 4.6Deployment of 4 load-cell sensors used to measure ballisto-cardiogramsFigure 4.7Diagram of the different elements integrated in typical health monitoring smart shirt (Pandian et al., 2008)Figure 4.8Diagram of the different hardware elements available in the smart medical box proposed by (Pang et al., 2009)Figure 4.9Generic architecture for elderly monitoring system (Wu and Huang, 2011)Figure 4.10Typical sequence diagram for the patient interaction with the monitoring system for chronic diseasesFigure 4.11Different types of devices deployed by (Ko et al., 2010) at John Hopkins hospital for health monitoringFigure 4.12Main encryption and decryption steps in a typical security architecture (Sain et al., 2010)Figure 4.13Design of an anti-bomb dressFigure 4.14Screenshot of the software to control the status of the policeman in real-timeFigure 4.15Implemented prototype anti-bomb dressFigure 4.16Code blue graphical interface screenshotFigure 4.17Agent-based wearable service architecture (Fraile et al., 2010)Figure 4.18Sensor architecture showing the protocols involved (Junnila et al., 2010)Figure 4.19Example of the remote monitoring system provided by (Tapia et al., 2010) in a scenario where a sensor can detect the smoke at homeFigure 4.20Protocol stack available in each smart sensor device (Corchado et al., 2010)Figure 5.1Ischemic damage induced in porcine liver during retractionFigure 5.2Modified standard fan retractor for measuring laparoscopic retraction forces and ischemia. The ischemia is measured between two points with a pair of bi-colour LEDs and one photodiode (PD). The force is measured by the strain gagesFigure 5.3Demonstrating local oxygen sensing results and the ability of a laparoscopic grasper in a controlled experiment restoration of the bowel segment's ischemiaFigure 5.4Five important physiological points in human heart pulse (Gong, 2011)Figure 5.5Schema of a health diagnosis system for both local and remote monitoring (Gong, 2011)Figure 5.6An illustration of different pulse patterns (Gong, 2011)Figure 5.7Left: Endovascular slent-graft repair of AAA. Right: Smart sensor incorporated into AAA sac to monitor the pressure in sac (Allen, 2005)Figure 5.8Basic structure of the dental management packageFigure 5.9Multitier infrastructure that enables an embedded flexibilityFigure 5.10Wireless sensor structure of the dental retainerFigure 5.11RFID-equipped dental retainer in placeFigure 5.12Device placement of MEMS in skull: (a) Sub-dural device implantation and (b) Epidural device in contiguous sections of the meninges. The sensor is exposed to the cerebral spinal fluid in sub-arachnoids space for sub-dural pressure detection. In epidural detection, the sensor maintains a contact with the dura mata and relies on dural deflection. (The sub-arachnoids space is the space between the innermost and the middle protective covering of the brain)Figure 5.13Schematic of the setup based on sphygmomanometer technique for monitoring air pressureFigure 5.14Schematic of hydrostatic pressure measurement using ICP monitoring deviceFigure 5.15Results of the average experimental pressure showing air pressure in terms of pulse frequency displayed by the measuring deviceFigure 5.16Basic concept of tomography image processing [wiki]Figure 5.17Isodose curves for two fields (out of 4) for a radio surgery case. Left: pencil beam dose, right: Monte Carlo energy deposition. The isodose intensity areas are for into six prescription doses of >90%, 90%–80%, 80%–60%, 60%–50%, 50%–30% and 30%–10%Figure 5.18Isodose curves for three fields for a paranasal sinus cancer. Left: pencil beam, right: Monte Carlo. The isodose intensity areas are for into six prescription doses of >90%, 90%–80%, 80%–60%, 60%–50%, 50%–30% and 30%–10%Figure 5.19Clinical application of MagIC heart conditioning wearable systemFigure 5.20Sample MagIC ventricular ectopic beating test signalsFigure 5.21MEM device using gravity to show the positionFigure 5.22Block diagram showing min components of the acceleratorFigure 5.23Data fusion model for situation and threat assessment (Vincen et al., 2009)Figure 5.24Technical structure of EMS in China (Zhang and Anwen, 2010)Figure 5.25The percentage of total travelling time (Benjamin et al., 2009)Figure 5.26The percentage of the trauma period in number of days (Benjamin et al., 2009)Figure 5.27Wearable Tele-Bio watchFigure 5.28Tele-Health emergency, system architectureFigure 5.29Map of Wake County, NC, highlighting census tracts, their centroids, and public elementary school locationsFigure 5.30Comparison of infection spreading dynamics over timeFigure 6.1Common architecture for implementing Smart Homes, proposed by (Kim et al., 2008)Figure 6.2Common architecture for the home server, proposed by (Kim et al., 2008)Figure 6.3Gator Tech Smart House. The project features numerous existing (E), ongoing (O), or future (F) ‘hot spots’ located throughout the premises (Helal et al., 2005)Figure 6.4Sensor platform architecture. The modular design provides a flexible configuration (Helal et al., 2005)Figure 6.5Software architecture of the SOA distributed operating system (Sleman and Moeller, 2011)Figure 6.6Main components of the SOA-DOS system (Sleman and Moeller, 2011)Figure 6.7Diagram of the U-Object finder environment (Kawashima et al., 2008)Figure 6.8Diagram of UOF-Robot components (Kawashima et al., 2008)Figure 6.9The Robots’ coordination procedure (Kawashima et al., 2008)Figure 6.10Example of home automation system structureFigure 6.11IEEE 802.15.4 Deployment (a) Without interference and (b) With interferenceFigure 6.12Overall system architecture of the system (Byun and Park, 2011)Figure 6.13Middleware architecture. (a) Adaptive light-weight middleware; (b) Middleware reconfiguration flowFigure 6.14Hardware block diagram of the SISFigure 6.15Structure of the proposed multi-agent system (Wang et al., 2010)Figure 6.16Structure of the subsystems for local control of the proposed multi-agent system (Wang et al., 2010)Figure 6.17BeeHouse ArchitectureFigure 6.18Proposed system and the graphical interface associated for BeeHouseFigure 6.19Domestic appliances collaboration in a Smart Home, architecture proposed by (Erol-Kantarci and Mouftah, 2010)Figure 6.20Deployment done at seventh floor of National Engineering Laboratory building in Beijing Jiaotong UniversityFigure 6.21Architecture proposed by (Lee et al., 2009) for in-home localisation service in smart house environmentsFigure 6.22Overview of the Interface based in 3D models proposed by (Lee et al., 2009) for rendering of in-home servicesFigure 6.23Smart wardrobe prototypeFigure 6.24Flowchart for the smart wardrobe systemFigure 6.25Smart office deployment controlling data centre temperature (Baghyalakshmi et al., 2011)Figure 6.26Architecture overview proposed in Kaleidos framework (Genova et al., 2009)Figure 6.27Scenario proposed by (Pan et al., 2008) in which there is smart management of lights in the officeFigure 6.28Decision algorithm proposed by (Pan et al., 2008) for deciding the lights to be activated in the officeFigure 7.1General IT public safety infrastructureFigure 7.2Monitoring scenario with nodes drifting along the sewer flow (Lim et al., 2011a)Figure 7.3Algorithm sequence used for building a Wireless Electronic Nose (Kim et al., 2009)Figure 7.4Chemical states of the fireFigure 7.5Monitoring forest fire architecture (Hartung et al., 2006)Figure 7.6Logical base station structure proposed by (Hartung et al., 2006)Figure 7.7Hop-by-hop recovery protocolFigure 7.8Ceiling structure used for the deployment done in WisdenFigure 7.9Sensor distribution in the Golden Gate Bridge to perform Structure Health MonitoringFigure 7.10Logical stack used for monitoring the Golden Gate BridgeFigure 7.11Deployment diagram of sensors proposed by (Chebrolu et al., 2008) to monitor railway bridgesFigure 7.12High-level overview for the architecture proposed by (Ceriotti et al., 2009) used to monitor the structure health of Torre Aquila, a historical buildingFigure 7.13WSN architecture proposed in SAFESPOT for traffic monitoring (Franceschinis et al., 2009)Figure 7.14Scenario proposed by (Weingärtner and Kargl, 2007) showing how to use the sensing devices to avoid traffic collisionsFigure 7.15Car collision scenario in which a distributed sensing platform is used to avoid collisions (Biswas et al., 2006)Figure 7.16Road intersection configuration proposed by (Tubaishat et al., 2007)Figure 7.17Deployment proposed by WITS system to monitor car traffic in cities (Chen et al., 2006)Figure 7.18Proposed scenario for determining the sink node in a mobile sink node scenarioFigure 7.19Schema used for calculating the timetable associated with VSsFigure 7.20Sample scenario for tracking an object using a cluster-based approachFigure 8.1Real deployment done by (Hu et al., 2010) used for monitoring underground water salinityFigure 8.2Double-chain network topologyFigure 8.3Sensing platform deployed in a poultry farm proposed by (Murad et al., 2009)Figure 8.4Hog farm sensor distribution proposed by (Hwang and Yoe, 2010)Figure 8.5Greenhouse sensor deployment proposed by (Chaudhary et al., 2011)Figure 8.6D. L. Coal Mine structure provided by (Li and Liu, 2009)Figure 8.72D localisation plane of the 3D deployment proposed by (Li and Liu, 2009)Figure 8.8Deployment proposed by (Carullo et al., 2009) for cold chain monitoringFigure 8.9Architecture proposed by (Maza et al., 2010) for controlling UAV devicesFigure 8.10Dynamic spatial monitoring scenario proposed by (Duckham et al., 2005)Figure 8.11Sensor Deployment provided by (Martinez and Hart, 2010) to monitor glaciersFigure A.1MMA7260Q acceleration sensor unit with Bluetooth moduleFigure A.2Moving average filter with five samples window size applied to acceleration signalFigure A.3Clustered sensing system using ripple-to-ripple loss recoveryFigure A.4EEG workflow design Drowsiness Warning SystemFigure A.5Architecture of PUIP dual image processor in projected operation (Kim et al., 1997)Figure A.6Two different scans of 3-D-rendered images of the power mode imagesFigure A.7‘THz gap’ relative to the microwave and IRFigure A.8Electro–Thz–Optical architectural conceptFigure A.9(a) Thin-film DNA wave-guiding (b) 2-D DNA-based switching waveguide (c) 3-D DNA PBG with active controlFigure A.10Multifunctional sensing method that uses piezoelectric ceramic transducers (a) Measurement of the ultrasonic properties (b) Electrical measurement of the propertiesFigure A.11Schematic diagram of the measurement systemFigure A.12Microphotograph of the sensor chipFigure A.13Unit electrode area. Al was formed on the top of the pixels in the electrode area. The Al was removed only on the top of the PD. The PD surface was coated with Green filter to selectively transmitted fluorescence lightFigure A.14Fabricated multimodal CMOS sensing deviceFigure A.15Implantable cardioverter defibrillatorFigure A.16Demonstration of the portal vein in placeFigure A.17Sensor structure and driving mechanism: (a) The regions for input and output electrodes as a diaphragm and (b) Illustration of the sensing principleFigure A.18Screenshot of Mica 2 Dot mote developed by Crossbow IncFigure A.19Screenshot of MICA2 Mote developed by Crossbow IncFigure A.20Screenshot of MicaZ mote developed by Crossbow IncFigure A.21Screenshot of TMote Sky mote developed by Moteiv CorpFigure A.22Screenshot of Fleck3 mote developed by CSIROFigure A.23Screenshot of IMote2 mote developed by CrossBow IncFigure A.24Protocol Stack of the ZigBee specificationFigure A.25Network topology associated with ZigBee specificationFigure A.26The CodeBlue infrastructure for tracking of patients and associates for emergency conditionFigure A.27Mote (a) Pulse oximeter and (b) Two-lead ECGFigure A.28PDA-based multiple-patient triage application. The screen shows real-time vital sign (heart rate and blood oxygen saturation) data from three patientsFigure A.29General structure for telemedicine framework

List of Tables

Table 1.1Four mobility based classes of sensor applicationsTable 2.1Specifications of U-Healthcare wearable systemTable 2.2Security applications of RuBee versus barcodes and RFID (wiki)Table 3.1Types of routing protocols and representative contributionsTable 4.1Sensors used in different real scenarios (1° and 2° trial) and data processing done in the device. L = in-sensor, S = stored locally in home PC, P = passed to central serverTable 5.1Sensor and associated sensing normally used for remote monitoring. (Pantelopoulos and Bourbakis, 2010)Table 5.2Wearable systems product specificationsTable 6.1Some heterogeneous contexts used in the pervasive computing framework (Hasswa and Hassanein, 2010)Table 8.1Operational Requirement for glacial monitoring provided by (Martinez and Hart, 2010)Table A.1Results of sensitivity and specificity performing different fall scenariosTable A.2Medical context of the patients monitored using telemedicine system

Preface

No matter how small a superior technology is, it can lead to new application paradigms and through a series of successful large-scale diffusions, transform societies and provide a better global lifestyle.

This book is complementary to many recent theoretical sensor-networking books and aims to give readers a taste of what the new smart sensing systems can do in their promising real world applications.