Téléchargez le livre : Machine Learning for Indoor Localization and Navigation

Machine Learning for Indoor Localization and Navigation

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Springer


Paru le : 2023-06-29

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Description
While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve theaccuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation. 


In particular, the book:Provides comprehensive coverage of the application of machine learning to the domain of indoor localization;Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization;Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions.
Pages
567 pages
Collection
n.c
Parution
2023-06-29
Marque
Springer
EAN papier
9783031267116
EAN PDF
9783031267123
Informations sur l'ebook
Nombre pages copiables
5
Nombre pages imprimables
56
Taille du fichier
28611 Ko
Prix
116,04 €
EAN EPUB
9783031267123
Informations sur l'ebook
Nombre pages copiables
5
Nombre pages imprimables
56
Taille du fichier
112312 Ko
Prix
116,04 €

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