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" Wireless indoor localization : "
Chenshu Wu, Zheng Yang, Yunhao Liu.
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BL
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| Record Number
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889593
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| Main Entry
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Wu, Chenshu
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| Title & Author
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Wireless indoor localization : : a crowdsourcing approach /\ Chenshu Wu, Zheng Yang, Yunhao Liu.
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| Publication Statement
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Singapore :: Springer,, 2018.
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| Page. NO
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1 online resource
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| ISBN
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9789811303562
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: 9789811303579
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: 9811303568
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: 9811303576
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9789811303555
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981130355X
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| Bibliographies/Indexes
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Includes bibliographical references.
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| Contents
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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.
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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.
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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.
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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.
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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.
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| Abstract
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This book provides a comprehensive and in-depth understanding of wireless indoor localization for ubiquitous applications. The past decade has witnessed a flourishing of WiFi-based indoor localization, which has become one of the most popular localization solutions and has attracted considerable attention from both the academic and industrial communities. Specifically focusing on WiFi fingerprint based localization via crowdsourcing, the book follows a top-down approach and explores the three most important aspects of wireless indoor localization: deployment, maintenance, and service accuracy. After extensively reviewing the state-of-the-art literature, it highlights the latest advances in crowdsourcing-enabled WiFi localization. It elaborated the ideas, methods and systems for implementing the crowdsourcing approach for fingerprint-based localization. By tackling the problems such as: deployment costs of fingerprint database construction, maintenance overhead of fingerprint database updating, floor plan generation, and location errors, the book offers a valuable reference guide for technicians and practitioners in the field of location-based services. As the first of its kind, introducing readers to WiFi-based localization from a crowdsourcing perspective, it will greatly benefit and appeal to scientists and researchers in mobile and ubiquitous computing and related areas.
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| Subject
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Wireless localization.
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| Subject
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TECHNOLOGY ENGINEERING-- Mechanical.
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| Subject
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Wireless localization.
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| Dewey Classification
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621.382
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| LC Classification
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TK5103.4895
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| Added Entry
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Liu, Yunhao,1971-
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Yang, Zheng
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