Intelligent IoT Systems in Personalized Health Care (eBook, ePUB)

Redaktion: Sangaiah, Arun Kumar; Mukhopadhyay, Subhas Chandra

• Format: ePub

Produktbeschreibung

Intelligent IoT Systems in Personalized Health Care delivers a significant forum for the technical advancement of IoMT learning in parallel computing environments across biomedical engineering diversified domains and its applications. Pursuing an interdisciplinary approach, the book focuses on methods used to identify and acquire valid, potentially useful knowledge sources. The book presents novel, in-depth, fundamental research contributions from a methodological/application perspective to help readers understand the fusion of AI with IoT and its capabilities in solving a diverse range of problems for biomedical engineering and its real-world personalized health care applications. The book is well suited for researchers exploring the significance of IoT based architecture to perform predictive analytics of user activities in sustainable health. - Presents novel, in-depth, fundamental research contributions from a methodological/application perspective to help readers understand the fusion of AI with IoT - Illustrates state-of-the-art developments in new theories and applications of IoMT techniques as applied to parallel computing environments in biomedical engineering systems - Presents concepts and technologies successfully used in the implementation of today's intelligent data-centric IoT systems and Edge-Cloud-Big data

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 360
• Erscheinungstermin: 6. November 2020
• Englisch
• ISBN-13: 9780128232040
• Artikelnr.: 61688284

Autorenporträt

Prof. Arun Kumar Sangaiah received his PhD from the School of Computer Science and Engineering, VIT University, Vellore, India. He is currently a Full Professor with National Yunlin University of Science and Technology, Taiwan. He is also a Professor at the School of Computing Science and Engineering, VIT University, Vellore, India. His areas of research interest include machine learning, Internet of Things, Sustainable Computing. He has published more than 300 research articles in refereed journals, 11 edited books, one patent (held and filed), as well as four projects funded by MOST-TAIWAN, one funded by Ministry of IT of India, and several international projects (CAS, Guangdong Research fund, Australian Research Council). Dr. Sangaiah has received many awards, Yushan Young Scholar, Clarivate Top 1% Highly Cited Researcher (2021,2022, 2023), Top 2% Scientist (Standord Report-2020,2021,2022, 2023), PIFI-CAS fellowship, Top-10 outstanding researcher, CSI significant Contributor etc. He is also serving as Editor-in-Chief and/or Associate Editor of various reputed ISI journals. Dr. Sangaiah is a visiting scientist (2018-2019) with Chinese Academy of Sciences (CAS), China and visiting researcher of Université Paris-Est (UPEC), France (2019-2020) and etc.

Inhaltsangabe

1. Combining IoT architectures in next generation healthcare computing systems
2. RFID-based unsupervised apnea detection in health care system
3. Designing a cooperative hierarchical model of interdiction median problem with protection and its solution approach: A case study of health-care network
4. Parallel machine learning and deep learning approaches for internet of medical things (IoMT)
5. Cloud-based IoMT framework for cardiovascular disease prediction and diagnosis in personalized E-health care
6. A study on security privacy issues and solutions in internet of medical things - A review
7. Application of computational intelligence models in IoMT big data for heart disease diagnosis in personalized health care
8. An improved canny detection method for detecting human flexibility
9. Prediction and classification of diabetes mellitus using genomic data
10. An application of cypher query-based dynamic rule-based decision tree over suicide statistics dataset with Neo4j
11. Exploring the possibilities of security and privacy issues in health-care IoT