| Preface | 5 |
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| Organization | 7 |
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| Table of Contents | 9 |
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| Wireless Sensor Network Application for Fire Hazard Detection and Monitoring | 11 |
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| Introduction | 11 |
| Sensor Node Design | 13 |
| Sensor Node Hardware | 13 |
| Sensor Node Modes of Operation | 14 |
| Central Node Design and Operations | 17 |
| Central Node GUI Design | 19 |
| Application Field Testing | 21 |
| Conclusions | 24 |
| References | 25 |
| Fire Detection and Localization Using Wireless Sensor Networks | 26 |
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| Introduction | 26 |
| Fire Detection Algorithm | 27 |
| Fire Localization Algorithm | 29 |
| Simulation Results | 32 |
| Conclusion | 35 |
| References | 36 |
| Design and Implementation of a Wireless Sensor Network for Precision Horticulture | 37 |
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| Introduction | 37 |
| General Characteristics of the Network Deployed | 38 |
| The GAIA Soil-Mote | 39 |
| Hardware Overview | 40 |
| Software Organization | 42 |
| Hydra Probe II Sensor | 43 |
| Power Management and Autonomy | 44 |
| Environmental-Mote, Water-Mote and Data-Sink/Gateway | 45 |
| Monitoring Application | 47 |
| Experimental Results | 49 |
| Final Remarks and Conclusions | 50 |
| References | 51 |
| A Nephelometric Turbidity System for Monitoring Residential Drinking Water Quality | 53 |
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| Introduction and Definition | 53 |
| Turbidity Measuring Techniques | 55 |
| Design and Development | 56 |
| Calibration and Testing | 59 |
| Interferences in Turbidity Measurement | 62 |
| Conclusions and Future Work | 62 |
| Conclusions | 62 |
| Future Work | 62 |
| References | 63 |
| Deployment of a Wireless Ultrasonic Sensor Array for Psychological Monitoring | 66 |
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| Introduction | 66 |
| System Architecture | 67 |
| Mote Development Environment | 68 |
| Sensor Array | 68 |
| Tracking Filter | 68 |
| Surmounted Challenges | 72 |
| Power Network | 72 |
| Sensor Access Pattern: Noise vs. Speed Tradeoff | 73 |
| Differential Calibration | 74 |
| Results | 74 |
| Performance of Distance Tracking | 75 |
| System Specifications | 76 |
| Conclusion | 76 |
| Future Work | 76 |
| References | 77 |
| WISEBED: An Open Large-Scale Wireless Sensor Network Testbed | 78 |
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| Introduction – Motivation | 78 |
| Previous Related Work | 80 |
| Overall Architecture and Considerations | 82 |
| Software Aspects of WISEBED | 85 |
| Integration with the Shawn Network Simulator | 86 |
| Federation of Testbeds and Related APIs | 86 |
| Hardware Aspects of WISEBED – Current Deployment | 89 |
| L\ | 89 |
| 90 | 89 |
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| RACTI Testbed Description | 91 |
| Use-Case Scenarios – Research Challenges | 93 |
| Scenarios | 93 |
| Research Challenges | 94 |
| Conclusions – Future Work | 95 |
| References | 96 |
| SmartEN: A Marie Curie Research Framework for Wireless Sensor Networks in Smart Management of the Human Environment | 98 |
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| Introduction | 98 |
| Overview of Previous Work | 100 |
| SmartEN Objectives and Challenges | 102 |
| Work Programme and Methodology | 105 |
| Work Programme 1 – Wireless Sensor Networks | 106 |
| Work Programme 2 – Sensor Signal Processing | 107 |
| Work Programme 3 – Non Destructive Evaluation | 108 |
| Work Programme 4 – Smart Proactive Management | 110 |
| Horizontal Integration through Multi-disciplinary Research Projects | 111 |
| SmartEN Applications | 111 |
| Discussion and Conclusions | 113 |
| References | 114 |
| Software Update Recovery for Wireless Sensor Networks | 117 |
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| Introduction | 117 |
| Related Work | 118 |
| Automated Local Recovery | 118 |
| Identifying Loss of Control | 119 |
| Recovery Action | 120 |
| Two-Phase Approach | 120 |
| State Machine | 120 |
| High-Reliability Polycasting | 121 |
| Minimum Spanning Tree Algorithm | 122 |
| Flooding Algorithm (FDMT) | 122 |
| Analytical Comparison | 122 |
| Experimental Comparison | 123 |
| Protocol Overview | 125 |
| Simulation | 126 |
| Behavioral Results | 126 |
| Estimating Long-Term Reliability | 128 |
| Propagation Delay | 129 |
| Recovery Latency | 129 |
| Energy Use | 130 |
| Energy vs. Latency Tradeoff | 132 |
| Feedback | 134 |
| Conclusions and Future Work |