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Wireless Indoor Localization

Autor Chenshu Wu, Zheng Yang, Yunhao Liu
en Limba Engleză Hardback – 3 sep 2018
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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Specificații

ISBN-13: 9789811303555
ISBN-10: 981130355X
Pagini: 240
Ilustrații: XVII, 220 p. 111 illus., 8 illus. in color.
Dimensiuni: 160 x 241 x 18 mm
Greutate: 0.52 kg
Ediția:1st ed. 2018
Editura: Springer
Locul publicării:Singapore, Singapore

Cuprins

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.

Notă biografică

Zheng Yang is an associate professor at the School of Software and BNRist, Tsinghua University. He holds a BE degree from Tsinghua University, and a PhD degree from Hong Kong University of Science and Technology. His research interests include Internet of Things, mobile computing, pervasive computing, industrial internet, smart city, etc. He is the author and co-author of 3 books and over 100 papers published in leading journals and conferences. Zheng received the China National Natural Science Award (2011). He is a senior member of IEEE and a member of ACM. Kun Qian is a post-doctoral researcher in the Department of Electrical and Computer Engineering, University of California San Diego. He received his Ph.D in 2019 at the School of Software, Tsinghua University. He received his B.E. in 2014 in Software Engineering from School of Software, Tsinghua University. His research interests include mobile computing and wireless sensing, etc. He has published over 20 papers in competitive conferences and journals. Chenshu Wu is an assistant professor at the University of Hong Kong. He is also the Chief Scientist at Origin Wireless Inc. His research focuses on wireless AIoT systems at the intersection of wireless sensing, ubiquitous computing, and the Internet of Things. He has published two books, over 60 papers in prestigious conferences and journals, and over 40 patents. His research has been commercialized as products, including LinkSys Aware that won the CES 2020 Innovation Award, HEX Home that won CES 2021 Innovation Award, and Origin Health Remote Patient Monitoring that won CES 2021 Best of Innovation Award. He holds BS and PhD degrees in Computer Science both from Tsinghua University. Yi Zhang is currently working toward his PhD degree at the School of Software in Tsinghua University. Prior to that, he received his BE degree from the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, in 2017. His research interests include wireless sensing, mobile computing, and machine learning. He is the author and co-author of over 6 papers published in leading journals and conferences.

Textul de pe ultima copertă

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. 

Caracteristici

Inspires numerous ubiquitous applications based on wireless indoor localization Reports the cutting-edge findings of world’s leading research lab on indoor localization As the first of its kind book introducing WiFi fingerprint based localization in a crowdsourcing perspective Covers three key issues in WiFi-based indoor localization: deployment, maintenance and location accuracy