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Wireless Indoor Localization A Crowdsourcing Approach
Título:
Wireless Indoor Localization A Crowdsourcing Approach
ISBN:
9789811303562
Autor personal:
Edición:
1st ed. 2018.
PRODUCTION_INFO:
Singapore : Springer Nature Singapore : Imprint: Springer, 2018.
Descripción física:
XVII, 220 p. 111 illus., 8 illus. in color. online resource.
Contenido:
Part I Getting Started -- Chapter 1 Background and Overview -- Chapter 2 Mobile Crowdsourcing and Inertial Sensing -- Part II: Boosting Deployment: Making It Available -- Chapter 3 Radio Map Construction without Site Survey -- Chapter 4 Building Tomography: Automatic Floor Plan Generation -- Part III: Facilitating Maintenance: Making It Sustainable -- Chapter 5 Adaptive Radio Map Updating -- Chapter 6 Self-Deployable Peer-to-Peer Navigation -- Part IV: Enhancing Accuracy: Making It Reliable -- Chapter 7 Exploiting Spatial Awareness via Fingerprint Spatial Gradient -- Chapter 8 Enhancing WiFi Fingerprinting with Visual Clues -- Chapter 9 Mitigating Large Errors in Practice -- Part V: Conclusions -- Chapter 10 Research Summary and Future Directions.
Síntesis:
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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