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Wireless indoor localization : a crowdsourcing approach
- Author / Creator
- Available as
- Online
Details
- Creator
- Chenshu Wu, Zheng Yang, Yunhao Liu
- Format
- Books
- Language
- English
- Contributors
- Publication
-
- Singapore : Springer, 2018
- Physical Details
-
- 1 online resource
- ISBNs
- 9789811303562, 9789811303555, 981130355X, 9811303568
- OCLC
- on1049802566
- Includes bibliographical references.
- Intro; Preface; Organization of the Book; Anticipated Audience; Acknowledgments; Contents; Acronyms; Part I Getting Started; 1 Background and Overview; 1.1 Wireless Indoor Localization; 1.2 State-of-the-Art Approaches; 1.2.1 Infrastructure; 1.2.2 General Architecture; 1.2.3 Historical Stages; 1.3 WiFi Fingerprint-Based Approach; 1.3.1 General Frameworks; 1.3.2 Challenges for Ubiquitous Applications; 1.4 Book Organization; References; 2 Mobile Crowdsourcing and Inertial Sensing; 2.1 Harnessing Crowdsourcing in Mobile Computing; 2.2 Embracing Mobility via Inertial Sensing; 2.2.1 Sensors Types
- 2.2.2 Mobility Information2.2.2.1 Displacement Information; 2.2.2.2 Direction Information; 2.2.2.3 Integrated Information; References; Part II Boosting Deployment: Making It Available; 3 Radio Map Construction Without Site Survey; 3.1 Introduction; 3.2 Related Work; 3.3 Overview; 3.3.1 Data Collection; 3.3.2 System Architecture; 3.4 Stress-Free Floor Plan; 3.5 Fingerprint Space; 3.5.1 Fingerprint Collection; 3.5.2 Pre-processing; 3.5.3 Fingerprint Space Construction; 3.6 Mapping; 3.6.1 Feature Extraction; 3.6.1.1 Corridor Recognition; 3.6.1.2 Room Recognition; 3.6.1.3 Reference Point Mapping
- 3.6.2 Space Transformation3.6.2.1 Floor-Level Transformation; 3.6.2.2 Room-Level Transformation; 3.7 Experiments; 3.7.1 Experiment Design; 3.7.2 Performance Evaluation; 3.7.2.1 Fingerprint Space Generation; 3.7.2.2 Mapping Performance; 3.7.2.3 Localization Error; 3.8 Conclusion; References; 4 Building Tomography: Automatic Floor Plan Generation; 4.1 Introduction; 4.2 Related Works; 4.3 System Overview; 4.4 Trace Collection; 4.4.1 User Data Collection; 4.4.2 Dead-Reckoning; 4.5 Trace Realization; 4.5.1 Entrance Discovery; 4.5.2 Reference Point Extraction; 4.5.3 Reference Point Matching
- 4.5.4 Drift Fixing4.5.5 Multi-floor Case; 4.6 Map Generation; 4.6.1 Space Regionalization; 4.6.2 Functionality Recognition; 4.7 Experiments; 4.7.1 Experiment Setup; 4.7.2 Reference Point Matching Performance; 4.7.3 Regionalization Performance; 4.7.4 Functionality Recognition; 4.8 Conclusion; References; Part III Facilitating Maintenance: Making It Sustainable; 5 Adaptive Radio Map Updating; 5.1 Introduction; 5.2 Related Works; 5.3 Preliminaries and Measurements; 5.3.1 Measurements of RSS Dynamics; 5.3.2 Radio Map Updating with Reference Points; 5.4 Overview; 5.5 Method Design
- 5.5.1 Pin Data Collection5.5.1.1 Pin Data Specification; 5.5.1.2 Mobility Monitoring; 5.5.2 Reference Point Estimation; 5.5.3 Map Updating; 5.5.3.1 Learning the Regression Model; 5.5.3.2 Updating the Radio Map; 5.6 Implementations and Evaluation; 5.6.1 Experimental Methodology; 5.6.2 Performance Evaluation; 5.6.2.1 Performance of Trajectory Matching; 5.6.2.2 Performance of Map Updating; 5.6.2.3 Localization Performance; 5.7 Discussions and Limitations; 5.8 Conclusions; References; 6 Self-Deployable Peer-to-Peer Navigation; 6.1 Introduction; 6.2 Related Works; 6.3 Motivations and Challenges