國立虎尾科技大學 |

Wireless indoor localization = a crowdsourcing approach /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Wireless indoor localization/ by Chenshu Wu, Zheng Yang, Yunhao Liu.
其他題名:	a crowdsourcing approach /
作者:	Wu, Chenshu.
其他作者:	Yang, Zheng.
出版者:	Singapore :Springer Singapore : : 2018.,
面頁冊數:	xvii, 220 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Wireless localization. -
電子資源:	http://dx.doi.org/10.1007/978-981-13-0356-2
ISBN:	9789811303562

Wireless indoor localization = a crowdsourcing approach /
Wu, Chenshu.

Wireless indoor localizationa crowdsourcing approach /[electronic resource] :by Chenshu Wu, Zheng Yang, Yunhao Liu. - Singapore :Springer Singapore :2018. - xvii, 220 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9789811303562

Standard No.: 10.1007/978-981-13-0356-2doiSubjects--Topical Terms:

1140094
Wireless localization.

LC Class. No.: TK5103.4895

Dewey Class. No.: 621.382

Wireless indoor localization = a crowdsourcing approach /
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505 0 $a 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.
520 $a 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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