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Internet of Things Use Cases for the Healthcare Industry [electronic resource] /

Contributor(s): Material type: TextTextPublisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 1st ed. 2020Description: XII, 296 p. 96 illus., 77 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030375263
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 004.6 23
LOC classification:
  • TK5105.5-5105.9
Online resources:
Contents:
AI in Health Sector -- Real-Time Smart Healthcare Model using IoT -- A Fog Based Approach for Real-Time Analytics of IoT-Enabled Healthcare -- Applications of IoT in Indoor Air Quality Monitoring Systems -- CloudIoT for Smart Healthcare: Architecture, Issues and Challenges -- Impact of IoT on the Healthcare Producers: Epitomizing Pharmaceutical Drug Discovery Process -- Cyber-Security Threats in Medical Devices -- Smart Healthcare Use Cases and Applications -- IoT Use Cases and Applications -- Internet of Things for Ambient Assisted Living - An Overview -- Smart Health care Applications and Real Time Analytics through Edge Computing -- The Role of Blockchain for Medical Electronics Security -- Clinical Data Analysis using IoT Data Analytics Platforms -- Internet of Things - Tools and Technologies in Healthcare -- Clinical data analysis using IoT -- Security Issues in IoT and Healthcare Devices.
In: Springer Nature eBookSummary: This book explores potentially disruptive and transformative healthcare-specific use cases made possible by the latest developments in Internet of Things (IoT) technology and Cyber-Physical Systems (CPS). Healthcare data can be subjected to a range of different investigations in order to extract highly useful and usable intelligence for the automation of traditionally manual tasks. In addition, next-generation healthcare applications can be enhanced by integrating the latest knowledge discovery and dissemination tools. These sophisticated, smart healthcare applications are possible thanks to a growing ecosystem of healthcare sensors and actuators, new ad hoc and application-specific sensor and actuator networks, and advances in data capture, processing, storage, and mining. Such applications also take advantage of state-of-the-art machine and deep learning algorithms, major strides in artificial and ambient intelligence, and rapid improvements in the stability and maturity of mobile, social, and edge computing models. .
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AI in Health Sector -- Real-Time Smart Healthcare Model using IoT -- A Fog Based Approach for Real-Time Analytics of IoT-Enabled Healthcare -- Applications of IoT in Indoor Air Quality Monitoring Systems -- CloudIoT for Smart Healthcare: Architecture, Issues and Challenges -- Impact of IoT on the Healthcare Producers: Epitomizing Pharmaceutical Drug Discovery Process -- Cyber-Security Threats in Medical Devices -- Smart Healthcare Use Cases and Applications -- IoT Use Cases and Applications -- Internet of Things for Ambient Assisted Living - An Overview -- Smart Health care Applications and Real Time Analytics through Edge Computing -- The Role of Blockchain for Medical Electronics Security -- Clinical Data Analysis using IoT Data Analytics Platforms -- Internet of Things - Tools and Technologies in Healthcare -- Clinical data analysis using IoT -- Security Issues in IoT and Healthcare Devices.

This book explores potentially disruptive and transformative healthcare-specific use cases made possible by the latest developments in Internet of Things (IoT) technology and Cyber-Physical Systems (CPS). Healthcare data can be subjected to a range of different investigations in order to extract highly useful and usable intelligence for the automation of traditionally manual tasks. In addition, next-generation healthcare applications can be enhanced by integrating the latest knowledge discovery and dissemination tools. These sophisticated, smart healthcare applications are possible thanks to a growing ecosystem of healthcare sensors and actuators, new ad hoc and application-specific sensor and actuator networks, and advances in data capture, processing, storage, and mining. Such applications also take advantage of state-of-the-art machine and deep learning algorithms, major strides in artificial and ambient intelligence, and rapid improvements in the stability and maturity of mobile, social, and edge computing models. .

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