Wireless Sensing: Principles, Techniques and Applications (Wireless Networks)

✍ Scribed by Jiannong Cao, Yanni Yang

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 175
• Category: Library

✦ Synopsis

This book systematically presents the wireless sensing technology, which has become a promising sensing paradigm in recent years. It includes the introduction of underlying sensing principles, wireless signals, sensing methodologies and enabled applications. Meanwhile, it provides case studies to demonstrate how wireless sensing is applied for representative human and object sensing applications.

This book also provides a wireless sensing framework as a guidance to understand and design a wireless sensing system or prototype based on their needs. It also presents a critical investigation of the challenges in achieving wireless sensing in both signal-level and application-level contexts. Accordingly, it summarizes the typical solutions to tackle the related challenges.

Researchers and advanced-level students in computer science or electrical engineering working on the design of a wireless system will find this book useful as a reference. Professionals working in the wireless sensing industry will also find this book valuable as a reference tool.

✦ Table of Contents

Preface
Acknowledgments
Contents
List of Symbols and Abbreviations
1 Introduction
1.1 Wireless Sensing and Applications
1.1.1 Applications in Healthcare and Assisted Living
1.1.2 Applications in Security and Surveillance
1.1.3 Human-Computer Interaction
1.1.4 Indoor Navigation
1.1.5 Industrial Automation
1.2 Wireless Sensing Framework
1.3 Organization of the Book
References
2 Wireless Signals and Signal Processing
2.1 Preliminaries of Wireless Signals
2.2 Common Types of Wireless Signals
2.2.1 Acoustic Signal
2.2.2 RFID Signal
2.2.3 WiFi Signal
2.2.4 LoRa Signal
2.2.5 Radar Signal
2.2.6 Light Signal
2.3 Wireless Signal Processing Solutions
2.3.1 Signal Processing to Remove Signal Noises
2.3.2 Signal Processing to Release Signal Constraints
2.3.2.1 Limited Number of Transmitters and Receivers
2.3.2.2 Effects of Signal Frequency and Power
2.3.2.3 Limited Bandwidth
2.3.2.4 Effect of Frequency Selective Fading on Sensing
References
3 Wireless Sensing System Configurations
3.1 Single-Transceiver vs. Multi-Transceiver Configurations
3.2 Device-Based vs. Device-Free Configurations
References
4 Wireless Sensing Methodologies
4.1 Sensed Information from Wireless Signals
4.2 Model-Based Methodologies
4.2.1 Wireless Signal Propagation Models for Sensing
4.2.1.1 Signal Propagation Distance
4.2.1.2 Angle of Arrival
4.2.1.3 Moving Frequency and Speed
4.2.1.4 Multipath Effect on Sensing the Target
4.2.1.5 Position Effect on Sensing the Target
4.2.1.6 Sensing Multiple Targets Simultaneously
4.2.2 Pros and Cons of Model-Based Methodologies
4.3 Data-Driven Methodologies
4.3.1 Data Analytics and Machine Learning Algorithms for Wireless Sensing
4.3.2 Pros and Cons of Data-Driven Methodologies
References
5 Case Studies
5.1 Human Respiration Monitoring
5.1.1 WiFi-Based Respiration Monitoring During Sleep
5.1.1.1 CSI for Tracking Respiration
5.1.1.2 CFR Data Pre-processing
5.1.1.3 Breathing Rate Estimation on Individual CFR Sequence
5.1.1.4 Tracking Respiration at Different Sleeping Positions
5.1.1.5 Experiments and Evaluation
5.1.2 RFID-Based Respiration Monitoring in Dynamic Environments
5.1.2.1 Understanding RFID-Based Respiration Monitoring and the Multipath Effect
5.1.2.2 Respiration Signal Mixed with Multipath Signals
5.1.2.3 Apnea Detection
5.1.2.4 Matched Filter
5.1.2.5 Respiration Rate Estimation
5.1.2.6 Evaluation
5.1.3 RFID-Based Concurrent Exercise and Respiration Monitoring
5.1.3.1 Understanding the Exercise and Respiration Rhythm
5.1.3.2 The RFID Signal of Exercise or Respiration Movements
5.1.3.3 Modeling the Respiration Activity During Exercise
5.1.3.4 Limb Movement Rate Estimation
5.1.3.5 Respiration Pattern Extraction
5.1.3.6 LRC Estimation
5.1.3.7 Evaluation
5.1.4 UWB Radar-Based Multi-Person Respiration Monitoring
5.1.4.1 Preliminary of UWB Radar
5.1.4.2 Respiration Pattern in the UWB Radar Signal
5.1.4.3 Presence Detection
5.1.4.4 Respiration State Estimation
5.1.4.5 Evaluation
5.2 Human and Object Indoor Localization
5.2.1 Bluetooth-Based Human Indoor Localization
5.2.1.1 LSTM-Based Self-Adaptive Localization
5.2.1.2 Experiments
5.2.2 RFID-Based Object Indoor Localization
5.2.2.1 Understanding and Preprocessing Phase
5.2.2.2 Detailed Design for 2D Localization
5.2.2.3 Extending to 3D Localization
5.2.2.4 Evaluation
5.3 Liquid Sensing
5.3.1 Acoustic-Based Liquid Fraud Detection
5.3.1.1 Understanding the Acoustic Absorption and Transmission in Liquids
5.3.1.2 Acoustic Signal Generation
5.3.1.3 Signal Pre-processing and Acoustic Feature Extraction
5.3.1.4 Tackling the Effect of Different Acoustic Devices
5.3.1.5 Tackling the Effect of Different Relative Device-Container Positions
5.3.1.6 Liquid Detection
5.3.1.7 Evaluation
References
6 Conclusion
6.1 Research Summary
6.2 The Future