Intelligent Internet of Things for Healthcare and Industry [electronic resource] /

Contributor(s):

Material type: Text

TextSeries: Internet of Things, Technology, Communications and ComputingPublisher: Cham : Springer International Publishing : Imprint: Springer, 2022Edition: 1st ed. 2022Description: XV, 384 p. 120 illus., 108 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783030814731

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:

621.38 23

LOC classification:

TK7895.E42
TK5105.8857

Online resources:

Click here to access online

Contents:

Chapter 1. Effectiveness of machine and deep learning in IoT enabled devices for healthcare system -- Chapter 2. Network protocols for the internet of health things -- Chapter 3. Affective computing for eHealth using low cost remote internet-of-things based EMG platform -- Chapter 4. Application of internet of things (IoT) to fight Covid-19 epidemic -- Chapter 5. An enhanced IoT based array of sensors for monitoring patients health -- Chapter 6. A secured smart healthcare monitoring systems using blockchain technology -- Chapter 7. Computational intelligence in healthcare with special emphasis on bioinformatics and internet of medical things -- Chapter 8. A review on security and privacy of internet of medical things -- Chapter 9. An Introduction to Wearable Sensor Technology -- Chapter 10. A fog based intelligent secured IoMT framework for early diabetes prediction -- Chapter 11. A comprehensive analysis of sustainable IoT infrastructure in the post-covid-19 era -- Chapter 12. Reinforced rider optimization algorithm for diagnosis of autism spectrum disorder and medical data -- Chapter 13. Machine Learning for Fog Computing Based IoT Networks in Smart City Environment -- Chapter 14. QoS and Energy Efficiency Using Green Cloud Computing -- Chapter 15. Privacy issues in smart IoT for Healthcare and Industry -- Chapter 16. Intelligent IoT for automotive industry 4.0 - challenges, opportunities, and future trends -- Chapter 17. Smart security for industrial and healthcare IoT applications.

In: Springer Nature eBookSummary: This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures. This book is focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives. The data analytics discussed are relevant for healthcare and industry to meet many technical challenges and issues that need to be addressed to realize this potential. The IoT discussed helps to design and develop the intelligent medical and industry solutions assisted by data analytics and machine learning. At the end of every chapter readers are encouraged to check their understanding by means of brainstorming summary, discussion, exercises and solutions. Focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives; Promotes an exchange of researchacross disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures; Features case studies emphasizing social and research perspectives on cyber-physical systems, data analytics, intelligence and security.

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This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures. This book is focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives. The data analytics discussed are relevant for healthcare and industry to meet many technical challenges and issues that need to be addressed to realize this potential. The IoT discussed helps to design and develop the intelligent medical and industry solutions assisted by data analytics and machine learning. At the end of every chapter readers are encouraged to check their understanding by means of brainstorming summary, discussion, exercises and solutions. Focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives; Promotes an exchange of researchacross disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures; Features case studies emphasizing social and research perspectives on cyber-physical systems, data analytics, intelligence and security.

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