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Autor(en): 
  • Yunhao Liu
  • Zheng Yang
  • Chenshu Wu
  • Wireless Indoor Localization: A Crowdsourcing Approach 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Februar 2019  
    Genre:  EDV / Informatik 
     
    angewandte informatik / Crowdsourcing / indoorlocalization / IndoorLocationSystem / IndoorPositioningSystem / Nachrichtententechnik, Telekommunikation / Personal Computer / Personalcomputing
    ISBN:  9789811343940 
    EAN-Code: 
    9789811343940 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 13 mm 
    Gewicht:  421 gr 
    Seiten:  240 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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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