Advances in Wireless Sensors and Sensor Networks (eBook)

Guest Editorial 5
Table of Contents 7
Security for Wireless Sensor Networks – Configuration Aid 9
Introduction 9
Motivation 10
Threats to Wireless Sensor Networks 10
Security Primitives 14
Security Protocols 17
Configuring Security 20
Protocols Supported 22
Application Based Parameters 23
Configuration Scenario 27
Tool Design 28
Conclusion 29
References 30
Low Power Wireless Buoy Platform for Environmental Monitoring 33
Introduction 33
WSN for Habitat Monitoring 36
Buoys for Environmental Monitoring 37
System Design 39
Networking 40
Time and Network Synchronization 41
Power Supply 42
Temperature Profiling 43
Transmission Range Tests 44
Buoy Deployment 46
Results and Conclusion 46
Ongoing and Future Work 47
References 50
A Detail Performance Evaluation of the Novel Mechanisms Ensuring Maximum Connectivity and Data Transmission between Nodes, Based on the Heuristics Under 5-Color Clustered Response Approach 51
Introduction 52
Related Work on All Layers of Protocol Stack 53
Literature Review of Topology Discovery Mechanisms 54
5-Color Clustered Response Mechanism 54
Heuristics Behind 5-Color Clustered Response Mechanism 57
A Novel Duty Cycle Assignment Mechanism 58
Phase 1 (Determining Recommended Number of Gray Nodes) 58
Phase 2 (Node Selection Mechanism for a Parent Node) 60
Phase 3 (Node Selection Mechanism for a Child Black Node) 61
Transmission Mechanisms of Information Packets between a Pair of Clusters 62
Overview of the Scenarios When a Node Fails 62
Fault Tolerance Mechanism 63
Discussion of Fault Tolerance Mechanism at Faulty State of a Node 63
Discussion of Fault Tolerance Mechanism at the Operational State of a Node 68
Method of Resetting the States of the Nodes 68
Fault Tolerance Mechanism When a Node Fails Multiple Times 69
Mechanism of Caching Packets Transmitted to a Faulty Node 69
Performance Evaluation 69
Experiment 1 69
Experiment 2 70
Experiment 3 71
Experiment 4 72
Experiment 5 72
Experiment 6 72
Experiment 7 73
Experiment 8 74
Experiment 9 75
Experiment 10 75
Experiment 11 76
Experiment 12 77
Experiment 13 77
Conclusion and Future Work 78
References 79
Inventory Management in the Packaged Gas Industry Using Wireless Sensor Networks 82
Asset Tracking and the Packaged Gas Industry 82
Using Wireless Sensor Networks for Gas Cylinder Tracking 87
Prototype System Implementation 89
System Overview 89
System Operation 90
Key Features 92
Sensors for Asset Tracking 97
Experimental Results 98
Battery Life 98
Using the Hand Held Unit for Asset Discovery 100
Industrial Demonstration 101
Conclusions and Future Work 103
References 105
An EM-IMM Method for Simultaneous Registration and Fusion of Multiple Radars and ESM Sensors 108
Introduction 108
Sensor Network Model for Radars and ESM Sensors 110
Simultaneous Registration and Fusion Using EM-IMM 113
E-STEP 114
Expectation Evaluation by IMM Filter 115
M-STEP 117
Bias Analysis of the EM Method 119
Performance Evaluation by PCRB 122
Simulation Results 126
Conclusions 129
References 129
Locatable, Sensor-Enabled Multistandard RFID Tags 132
Introduction 132
System Architecture 133
Technology Aims 134
Analog Multistandard Frontend 135
Ultra Low-Power Rectification 135
Tag-to-Reader Communication 138
Reader-to-Tag Communication 139
Digital Baseband Processing 140
Energy Efficiency of Digital Circuits 141
Localization of UHF Labels 142
Distance Measurement with FMCW Radar 143
Common Requirements for the Oscillator 145
Distance Calculation with Digital Signal Processing 147
Integrated Sensors and Their Interface 149
Analog to Digital Converter 150
Input Multiplexer 152
Temperature Sensor 152
Measurements 153
Summary 154
References 155
Optimal Sensor Network Configuration Based on Control Theory 158
Optimal Sensor Network Configuration Considering Estimation Error Variance and Communication Energy 158
Introduction 158
Problem Formulation 159
Estimation Algorithm 162
Sensor Scheduling Algorithm 166
Experimental Evaluation 168
Conclusions 170
Optimal Sensor Network Configuration via Multi-hop Communication 170
Introduction 170
Problem Formulation 172
Proposed Method 174
Network Configuration Algorithm 177
Experimental Evaluation 178
Conclusion 180
References 182
Optimal Local Map Registration for Wireless Sensor Network Localization Problems 184
Introduction 184
Related Work 187
Optimal Local Map Registration 189
The Optimal Rotation Matrix 192
Global Map Construction 195
Performance Analysis 195
Conclusions 201
Appendix 204
Wireless Sensor Network: Application to Vehicular Traffic 206
Introduction 206
Background 207
Vehicle Sensor Review 208
Wireless Sensor Network 209
System and Network Architecture 210
System Architecture 210
Network Topology 211
Antenna 212
Protocols 213
Mac Protocol 213
Frame Format 214
Frame Format between Server Node and PC (Data Server) 216
Data Analysis 217
Preprocess the Data 217
Vehicle Detection 218
Estimation of Vehicle's Speed and Length 218
Averaged Magnetic Energy 219
Hill Pattern Peaks 220
Experiments and Results 220
Detectability, Length and Speed Estimation Experiment 220
RF Communications Experiment 221
Classification Experiment 222
Conclusion 226
References 227
Thermal Energy Harvesting for Wireless Sensor Nodes with Case Studies 228
Introduction 228
Conversion Methods and Technologies 230
Thermoelectric 230
Thermionic and Thermo-tunnelling 232
Power Management Systems 233
Heat Sources and Applications 233
Solar 233
Ground to Ambient Air 234
Water to Ambient Air 236
Transport 236
Industrial Waste Heat 237
The Human Body 238
Case Study: The Use of Environmental Heat 238
Experimental Details 240
Experimental Variations 240
Experimental Results 241
Conclusion 247
References 247
IEEE 1451.5 Standard-Based Wireless Sensor Networks 250
Introduction 250
Related Work 253
IEEE 1451.5 Standard-Based Wireless Sensor Networks 257
Architecture of IEEE 1451.5 Standard-Based Wireless Sensor Networks 257
IEEE 1451.5 Standard-Based Wireless Sensor Networks 267
Service-Oriented and IEEE 1451.5-802.11 Standard-Based Wireless Sensor Network 270
Service-Oriented and IEEE 1451.5-802.11 Standard-Based Wireless Sensor Network 270
Case Studies 272
Summary 276
References 276
Fuzzy Based Optimized Routing Protocol for Wireless Sensor Networks 279
Introduction 279
Related Work 280
Proposed Routing Protocol 281
Protocol Operation 281
Performance Analysis and Simulation Results 285
Conclusions 287
References 287
Energy Aware Sensor Group Scheduling to Minimise Estimated Error from Noisy Sensor Measurements 289
Introduction 289
Chapter Overview 290
Problem Description and Formulation 291
System Models 292
State Estimation 293
Error Cost Function 295
Scheduling Methodologies 296
Dynamic Programming 296
Particle Swarm Optimisation 298
One-Step-Look-Ahead Method 301
Experiment and Simulation Results 301
Conclusion 309
References 309
Smart Home for Elderly Using Optimized Number of Wireless Sensors 312
Introduction 312
Motivation – Need for Early Detection of Aging Changes 314
Literature Survey 314
Wireless Sensors Based In-home Monitoring Using Optimized Number of Sensors 316
System Description 317
Electrical Appliance Monitoring Unit 319
Water-Use Monitoring Unit 319
Bed Monitring Unit 321
Emergency Button 326
The Cellular Modem 326
Radio Frequency Communication Protocol 327
Interface and Control Software 328
Experimental Results 329
Conclusions and Future Work 332
References 332
Estimation of Packet Error Rate at Wireless Link of VANET 334
Introduction 334
Related Works 335
Our Works 337
Measurement of Packet Error Rate in Vanet 338
Analysis of Packet Error in VANET 340
Burst Length and Gas Length 340
Statistical Properties of Packet Error Rate 342
Estimation of Packet Error Rate in VANET 347
Estimate Per Using Plm 348
Packet Error Rate Estimation Using Rpee 353
Conclusions 362
References 362
Author Index 365

"Wireless Sensor Network: Application to Vehicular Traffic (p. 199-200)

Abstract.

In this paper we are reporting our current development of wireless sensor network to e?ectively monitor vehicular tra?c. A simple star con?guration that consists of a server node communicating with a number of sensor nodes is proposed because of its low complexity, and easy and quick deployment, maintenance and relocation. Our system consists of the sensor, processor, and RF transceiver. We choose the magneto-resistive sensor to detect vehicles as it yields high accuracy with small size. The sensor yields important vehicle informations such as vehicle count, speed, and classi?cation.

The network topology is a simple star network. Two Medium Access Communication Protocols (MAC) are analyzed and can be automatically switched based on two di?erent tra?c scenarios. An antenna design is shown to ?t with a small sensor node. Experiments show that the proposed system yields good data processing results. The classi?cation of vehicles is very promising for major types of vehicles: motorcycle, small vehicle, and bus. RF communications is employed that cable installation can be avoided. Protocol frame formats are provided for both RF communications and RS232. This protocol is very simple and can be easily extended when new sensors or new data types are available.

1 Introduction

Tra?c congestion is all big city’s major concern. It hinders substantial economic and social growth. Work have been proposed with the common goal of alleviating tra?c congestion. It is widely agreed that e?cient tra?c planning and management often reduce the congestion to a certain degree. Let’s take Bangkok for instance. During rush hours, the city often manages the traf- ?c by resorting to the tra?c police as a conventional and common practice.

Police o?cers are dispatched to major streets and junctions to help direct and control tra?c ?ow. The tra?c police manually switched tra?c lights at these junctions based on real-time tra?c conditions being observed and communicated among them over their trunked-radio. The lack of tra?c data or wrong tra?c information will worsen the tra?c situation. This particular situation clearly shows that tra?c data collection is very important for an e?ective real-time tra?c management. It is thus important that an e?cient management of tra?c requires data collection process in the ?rst step. A number of work have studied on various vehicle sensors, their accuracy in collecting data, and their operation and functionality.

These sensors include inductive loop [1,8,5], optical sensor [13,8], ultrasonic [6,8], and magnetic sensor [7,8]. Applications of these sensors to tra?c data collection and processing have been numerously proposed [11,13,6,12,2,14,5,9]. Most of the tra?c data collecting devices require signal and power cables. Recently, wireless sensor network has been applied to traf- ?c monitoring systems as it yields several advantages including quick deployment and maintenance, less cables involved, and small size [9,4]. Therefore, applications of wireless sensor network to tra?c data collection are numerous."