Implementation of Smart Healthcare Systems using AI, IoT, and Blockchain

Erscheinungsjahr 2022
ISBN: 978-0-323-91916-6
Verlag: Elsevier Science & Technology

Buch, Englisch, 360 Seiten, Format (B × H): 234 mm x 191 mm, Gewicht: 630 g

Implementation of Smart Healthcare Systems using AI, IoT, and Blockchain provides imperative research on the development of data fusion and analytics for healthcare and their implementation into current issues in a real-time environment. While highlighting IoT, bio-inspired computing, big data, and evolutionary programming, the book explores various concepts and theories of data fusion, IoT, and Big Data Analytics. It also investigates the challenges and methodologies required to integrate data from multiple heterogeneous sources, analytical platforms in healthcare sectors.

This book is unique in the way that it provides useful insights into the implementation of a smart and intelligent healthcare system in a post-Covid-19 world using enabling technologies like Artificial Intelligence, Internet of Things, and blockchain in providing transparent, faster, secure and privacy preserved healthcare ecosystem for the masses.

Autoren/Hrsg.

Chakraborty, Chinmay

Abdul Ahad, Mohd

Pani, Subhendukumar

Xin, Qin

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie

Inhaltsverzeichnis

1. Artificial Intelligence enabled Internet of Medical Things for Enhanced Healthcare Systems
2. Integrating Sensor, Actuators and IoT for for Smart Healthcare in Post COVID-19 World
3. Voice Signal based Disease Diagnosis using IoT and Learning Algorithms for Healthcare
4. Intelligent and sustainable approaches for medical big data management
5. A Predictive method for Emotional Sentiment Analysis by Machine Learning from EEG of Brainwave Data
6. Role of AI and IoT based medical diagnostics smart health care system for post-Covid-19 world
7. Windowed Modified Discrete Cosine Transform based Textural Descriptor approach for Voice Disorder Detection
8. Internet of Medical Things for Abnormality detection in Infants using Mobile Phone App with cry Signal Analysis
9. IoT based Effective Wearable Healthcare Monitoring System for Remote Areas

10. Blockchain for Transparent, Privacy Preserved and Secure Health Data Management
11. SPSHS: Security and Privacy Concerns in Smart Healthcare System

Über Autor(innen)

Chakraborty, Chinmay
Chinmay Chakraborty is an Assistant Professor (Sr.) in the Dept. of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India. His main research interests include the Internet of Medical Things, Wireless Body Area Network, Wireless Networks, Telemedicine, m-Health/e-health, and Medical Imaging. He is an Editorial Board Member of various different journals and conferences

Xin, Qin
Qin Xin graduated with his Ph.D. in the Department of Computer Science at the University of Liverpool, UK, in December 2004. He is currently working as a FULL professor of Computer Science in the Faculty of Science and Technology at the University of the Faroe Islands (UoFI). His primary research focuses on designing and

analyzing sequential, parallel, and distributed algorithms for various communication and optimization problems in wireless communication networks and cryptography and digital currencies, including quantum money. Moreover, he investigates combinatorial optimization problems with Bioinformatics, Data Mining, and Space Research applications. Currently, he is serving on the Management Committee Board of Denmark for several EU ICT projects.

Abdul Ahad, Mohd
Mohd Abdul Ahad is a Senior Member of IEEE and is currently working in the Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India. He obtained his Ph.D. degree in the field of Big Data Architecture. His research areas include Big Data architecture, Distributed Computing, IoT, Sustainable Computing. He is currently serving as an Editor-in-Chief of the International Journal of End User Computing and Development (IJEUCD), IGI Global, USA.

Pani, Subhendukumar
Dr. Subhendu kumar Pani received his Ph.D. from Utkal University ,Odisha, India. He is working as professor at Krupajal Engineeing College under BPUT, Odisha, India. He has almost 2 decades of teaching and research experience. His research interests include Data mining, Big Data Analysis, web data analytics, Fuzzy Decision Making and Computational Intelligence. He is the recipient of 5 researcher awards. He has published dozens of international journal papers. His professional activities include roles as Book Series Editor, Associate Editor, Editorial board member and/or reviewer of various international journals. He is Associated with a number of conference societies. He has more than 150 international publications, 5 authored books, 15 edited and upcoming books; 20 book chapters into his account. He is a fellow in SSARSC and life member in IE, ISTE, ISCA,OBA.OMS, SMIACSIT, SMUACEE, CSI.