Efficient Data Handling for Massive Internet of Medical Things

Healthcare Data Analytics de

, , ,

Éditeur :

Springer


Collection :

Internet of Things

Paru le : 2021-09-01

eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
137,14

Téléchargement immédiat
Dès validation de votre commande
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

Description
This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies.  In a nutshell, this book gives a comprehensive overview of thestate-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things. 
Pages
388 pages
Collection
Internet of Things
Parution
2021-09-01
Marque
Springer
EAN papier
9783030666323
EAN PDF
9783030666330

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
38
Taille du fichier
8684 Ko
Prix
137,14 €
EAN EPUB
9783030666330

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
38
Taille du fichier
24781 Ko
Prix
137,14 €