Front Cover

Geographical and Fingerprinting Data for Positioning and Navigation Systems: Challenges, Experiences and Technology Roadmap

Copyright

Dedicatories

Contents

Contributors

Preface

Acknowledgments

Chapter 1: Challenges of Fingerprinting in Indoor Positioning and Navigation

1 Motivation

2 Indoor Positioning Systems

2.1 Position, Location, and Navigation

2.2 Classification

2.3 Localization Mechanisms

3 Fingerprinting Indoor Positioning Techniques

3.1 Wi-Fi Fingerprinting

3.2 Problems of Wi-Fi Fingerprinting

3.2.1 Solutions to Radiomap Creation

3.3 Magnetic Field Fingerprint

3.4 Examples of Solutions

3.4.1 How to Compare Solutions

4 Indoor Maps

5 Privacy and Security Issues

6 Conclusions and Future Challenges of Indoor Positioning

Acknowledgments

References

Further Reading

Chapter 2: Wi-Fi Tracking Threatens Users' Privacy in Fingerprinting Techniques

1 Introduction

2 Related Work

3 Technical Background

4 Potentials and Limitations of Wi-Fi Tracking

5 Security Mechanisms Against Wi-Fi Tracking

5.1 Protocol Extensions

5.2 MAC Address Randomization

6 Privacy-Preserving Wi-Fi Fingerprinting

6.1 Basic Concept

6.1.1 Deterministic Approach

6.1.2 Probabilistic Approach

6.2 Evaluation

6.2.1 Implementation and Setup

6.2.2 Deterministic Location Estimation

6.2.3 Probabilistic Location Estimation

6.2.4 Considering User Movement

7 Conclusion and Future Work

References

Chapter 3: Lessons Learned in Generating Ground Truth for Indoor Positioning Systems Based on Wi-Fi Fingerprinting

1 Introduction

2 Lessons Learned at In-Home Scenarios

2.1 Calibration and Experimental Setup

2.1.1 Smartphone-Based Patient Monitoring

2.1.2 Smartwatch-Based Patient Monitoring

2.2 Experiences and Lessons Learned

2.2.1 Smartphone-Based Patient Monitoring

2.2.2 Smartwatch-Based Patient Monitoring

3 Lessons Learned at Very Large Scenarios

3.1 Calibration and Experimental Setup

3.2 Experiences and Lessons Learned

3.2.1 First Stage

3.2.2 Second Stage

3.2.3 Third Stage

3.2.4 Fourth Stage

3.2.5 Fifth Stage

3.2.6 Sixth Stage

4 General Experiences

Acknowledgments

References

Chapter 4: Radio Maps for Fingerprinting in Indoor Positioning

1 Introduction

2 Radio Maps for Different Radio Technologies

2.1 Deterministic Radio Maps

2.2 Bluetooth Low Energy Radio Maps

2.3 Other Technologies: FM and AM Radio Maps

3 Building and Updating Radio Maps

3.1 Build a Radio Map

3.2 Crowdsourcing

3.3 A Crowdsourcing Solution to Build a Radio Map

4 Wi-Fi Radio Map Density

4.1 Radio Map Construction Using Interpolation

4.1.1 Inverse Distance Weighting Interpolation

4.1.2 Radial Basis Function Interpolation

4.1.3 Kriging Interpolation

4.1.4 Other Interpolation Methods

4.2 Radio Map Construction Using Propagation Models

5 Radio Maps Filtering

5.1 Radio Map Density and Positioning Performance

5.2 AP Selection

5.2.1 Offline AP Selection

5.2.2 Online AP Selection

5.3 Samples Filtering

6 Standards

6.1 Fundamental Building Blocks of an Indoor Positioning and Tracking System

6.2 The Need for Standards

6.3 Automatic Discovery Protocols

6.4 Radio Maps: Formats and Protocols

6.5 Floor Maps and Other Space Models

6.6 Remote Positioning Engines

6.7 Standardization Initiatives

7 Conclusion

References

Further Reading

Chapter 5: Crowdsourced Indoor Mapping

1 Introduction

2 Some Existing Crowdsourced Outdoor Map Systems

2.1 Google Maps

2.2 OpenStreetMap

2.3 MapQuest

2.4 Waze

2.5 Others

2.6 Discussions

3 Indoor Map Systems' Research

3.1 Simultaneous Localization and Mapping

3.2 Calibration-Free Indoor Positioning System

TIX

SDM

EZ

UnLoc

Walkie-Markie

CrowdInside

MapGenie

Jigsaw

iMoon

3.3 Discussions

4 Research Challenges of Crowdsourced Indoor Floor Plan Construction

4.1 Quality of Crowdsourced Data

4.2 Implications of Internet of Things (IoT) Devices' Equipped Sensors

4.3 Dimension of the Floor Plan Layout

4.4 Type of Architecture

4.5 Privacy and Security

5 Conclusion

References

Chapter 6: Radio Fingerprinting-Based Indoor Localization: Overcoming Practical Challenges

1 Introduction

1.1 Motivation

1.2 Radio Fingerprint Localization Assumptions

2 Fingerprinting Challenges

2.1 Fingerprint Point Similarity

2.2 Location and Error Estimation

2.3 Device Heterogeneity

2.4 Obtaining and Updating Radio Maps

3 Summary and Conclusions

References

Chapter 7: Low-Complexity Offline and Online Strategies for Wi-Fi Fingerprinting Indoor Positioning Systems

1 Introduction

2 Low-Complexity Strategy for Offline Phase

2.1 RSS Prediction via MWMF Model

2.2 Offline Phase

2.3 Online Phase

2.4 Experimental Setting and Performance Indicators

2.5 Results and Discussions

3 Low-Complexity Strategy for Online Phase

3.1 RP Clustering via Affinity Propagation

3.2 Offline Phase

3.3 Online Phase

3.4 Experimental Setting and Performance Indicators

3.5 Results and Discussion

4 Conclusion and Future Work

References

Chapter 8: Study and Evaluation of Selected RSSI-Based Positioning Algorithms

1 Introduction

2 Indoor Radio Propagation

2.1 The Free Space Model

2.2 Indoor Propagation

2.3 The RSSI Measure

3 Wi-Fi Positioning by Centroid Methods

3.1 The Centroid Method

3.2 Weighted Centroid Method

4 Wi-Fi Fingerprinting

4.1 The Radio Map

4.2 RSSI Vector Similarity Measures

5 Fingerprint Calibrated Weighted Centroid

6 Validation of the Described Fingerprint and FCWC Schemes

6.1 Validation Data

6.2 Algorithm Implementations

6.3 Results SPCF and FCWC

6.4 Validation Against Competing Algorithms

7 Wi-Fi Probability-Based Positioning and BLE

7.1 The Probability Density Function

7.2 A Probability-Based Setup and Algorithm

7.3 Probability-Based Results

7.4 BLE Beacon RSSI Weighted Centroid

8 Summary

References

Chapter 9: Mapping Indoor Environments: Challenges Related to the Cartographic Representation and Routes

1 Introduction

2 Related Work

3 Context and Study Area

4 Database Construction

4.1 Database Conceptual Model

4.2 Database Implementation

4.3 Cartographic Database Construction

5 Indoor Routing

6 Development Environment

7 Results

7.1 Indoor Cartographic Representation

7.2 Indoor Routes

8 Conclusion and Future Developments

Acknowledgments

References

Chapter 10: OGC IndoorGML: A Standard Approach for Indoor Maps

1 Introduction

2 Requirements for Indoor Maps

2.1 Complex Structures of Indoor and Connectivity

2.2 Cell-Based Context Awareness

2.3 Integrating Multiple Data Sets

3 Basic Concepts of OGC IndoorGML

Cell Geometry

Topology Between Cells

Cell Semantics

Multilayered Space Model

4 Modular Structure of IndoorGML

4.1 IndoorGML Core Module

4.2 IndoorGML Navigation Module

5 Implementation Issues

Cell Determination and Decomposition

Thick Door Model vs. Thin Door Model

Path Geometry

Space Closure

Hierarchical Structure

Wall Texture

Vertical Connection

6 Use Cases

7 Conclusion

Acknowledgments

References

Chapter 11: The EvAAL Evaluation Framework and the IPIN Competitions

1 Motivation and Challenges

2 Background

2.1 The IPIN Conference

2.2 The EvAAL Indoor Localization Competition

2.3 The Microsoft Indoor Localization Competition

3 The EvAAL Framework

4 The IPIN Competitions

4.1 Applying the EvAAL Framework to IPIN Competitions

4.2 Discussion on the Error Statistics

5 IPIN Competing Systems

5.1 An Overview on the Internals of Real-Time Systems

5.1.1 Raw-Data Modules

5.1.2 Fusion Strategies

6 Conclusion and Future Directions

References

Chapter 12: IndoorLoc Platform: A Web Tool to Support the Comparison of Indoor Positioning Systems

1 Introduction

2 Related Work

3 Overview of the Platform

3.1 Datasets

3.2 Ranking

3.3 Methods

3.4 Dashboard

3.5 Implementation Details

4 Datasets Included in the Platform

4.1 Wi-Fi-Based Datasets

4.1.1 UJIIndoorLoc

4.1.2 IPIN2016 Tutorial

4.1.3 Tampere University

4.1.4 ALCALA2017 Tutorial

4.2 AmbiLoc Dataset

4.3 magPIE Dataset

5 Methods Included in the Platform

5.1 Deterministic-Based Approach

5.2 Probabilistic-Based Approach

6 Experiments

7 The Platform in Use

8 Conclusions

Acknowledgments

References

Chapter 13: Challenges and Solutions in Received Signal Strength-Based Seamless Positioning

1 Introduction and Definitions

2 Overview of Fingerprinting Methods

2.1 Methods With Full Training Databases

2.2 Methods With Reduced Training Databases

2.2.1 Clustering Methods

2.2.2 Path-Loss Approaches

2.2.3 Image-Based Approaches

2.2.4 Other Approaches

3 Challenges and Solutions in Fingerprinting

3.1 Calibration Issues

3.1.1 The Effect of RSS Offsets

3.1.2 Possible Calibration Methods

3.2 Database-Size Reduction

3.2.1 Compression and Clustering

3.2.2 Access Point Number Reduction

3.3 Measurement Gaps

3.4 Height or Floor Estimation

4 Integration of WLAN With Other Signals of Opportunity

4.1 Signals of Opportunity and Their Characteristics

4.2 WLAN and BLE

4.3 WLAN and RFID

5 Integration of WLAN With GNSS

5.1 Fusing GNSS Pseudoranges With WLAN Ranges

5.2 Fusing GNSS Pseudoranges With WLAN RSS

5.2.1 Training Stage

5.2.2 Estimation Stage

5.2.3 Performance of Pseudorange and RSS Fusion Filter

6 Integration of WLAN With Other Data

6.1 Inertial Data

6.2 Vision Navigation

6.3 Visible Light Positioning

6.4 Magnetic Field Navigation

6.5 Positioning With Sounds or Ultrasonic Waves

6.6 Multimodal Positioning

6.7 Cloud Architectures

7 Open Issues and Conclusions

References

Chapter 14: Deployment of a Passive Localization System for Occupancy Services in a Lecture Building

1 Introduction

2 Overview of the Localization System

2.1 Deployment Cycle

2.2 Training Approach

2.3 Data Representation

3 Real Scenario: Occupancy for a Lecture Building

3.1 Overview

3.2 Characterization of the Passive Sensing

3.3 Considerations About Accuracy

3.4 Occupancy Services

4 Conclusions

References

Chapter 15: Remote Monitoring for Safety of Workers in Industrial Plants: Learned Lessons Beyond Technical Issues

1 Motivation

2 Remote Monitoring System for Safety of Workers in Refineries

2.1 The Architecture

2.1.1 Wearable Devices: The Wristband

2.1.2 Communication Infrastructure

2.1.3 Control Center

2.2 Data Anonymity

3 Learned Lessons in the Field

3.1 Person Related Issues

3.2 Logistics

4 Conclusions

Chapter 16: A Review of Indoor Localization Methods Based on Inertial Sensors

1 Introduction

2 Inertial Sensors and Magnetometers

3 Orientation Estimation

3.1 Prediction Stage

3.2 Update Stage

3.2.1 Absolute Gravity Update

3.2.2 Differential Gravity Update

3.2.3 Absolute Magnetic Field Update

3.2.4 Differential Magnetic Field Update

3.2.5 Absolute Compass Update

3.2.6 Zero Angular Rate Update

4 Shoe-Mounted Inertial Positioning

5 Non-shoe-Mounted Inertial Positioning

5.1 Step Detection on Horizontal Surfaces

5.2 Step Detection on Stairs

5.3 Step Length Estimation

5.4 Vertical Displacement Estimation

6 Drift Reduction Methods

6.1 Heuristic Drift Elimination Algorithms

6.2 SLAM-Based Algorithms

6.3 Multi-inertial Sensor Fusion

6.4 Landmark-Based Algorithms

6.5 Height Error Correction

7 Conclusions

References

Chapter 17: Fundamentals of Airborne Acoustic Positioning Systems

1 Introduction

2 Acoustic Wave Propagation in Air

2.1 Absorption

2.2 Propagation Speed

2.3 Impedance

2.4 Outdoor Propagation

3 Acoustic Signal Detection and Positioning Observables

4 Positioning Strategy

4.1 Spherical Lateration

4.2 Hyperbolic Lateration

5 Detection Hindering Phenomena and Compensation Strategies

5.1 Multiple Access Interference

5.2 Strong Multipath Propagation

5.3 Doppler Shift

6 Conclusions

References

Chapter 18: Indoor Positioning System Based on PSD Sensor

1 Introduction

2 Description and Modeling of the Optical Sensor System

2.1 PSD Sensor

2.2 Electrical System Modeling

2.3 Optical System Modeling

3 Sensor System Calibration

3.1 Electrical Calibration Process

3.2 Geometric Calibration

4 Three-Dimensional Position Determination Using AoA

4.1 Method 1: IPS Located in the Environment and IRED on Board of the Mobile Agent

4.2 Method 2: PSD Sensor on Board of Each Mobile Agent and Emitters in the Environment

5 Discussion

Acknowledgments

References

Index

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