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Semantic Models in IoT and eHealth Applications. Intelligent Data-Centric Systems

  • Book

  • September 2022
  • Elsevier Science and Technology
  • ID: 5527378

Semantic Models in IoT and eHealth Applications explores the key role of semantic web modeling in eHealth technologies, including remote monitoring, mobile health, cloud data and biomedical ontologies. The book explores different challenges and issues through the lens of various case studies of healthcare systems currently adopting these technologies. Chapters introduce the concepts of semantic interoperability within a healthcare model setting and explore how semantic representation is key to classifying, analyzing and understanding the massive amounts of biomedical data being generated by connected medical devices.

Continuous health monitoring is a strong solution which can provide eHealth services to a community through the use of IoT-based devices that collect sensor data for efficient health diagnosis, monitoring and treatment. All of this collected data needs to be represented in the form of ontologies which are considered the cornerstone of the Semantic Web for knowledge sharing, information integration and information extraction.

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Table of Contents

1. Semantic Modelling for Healthcare Applications: An Introduction
2. Role of IoT and semantics in Ehealth
3. Evaluation and Visualization of Healthcare Semantic Models
4. Role of Connected objects in Healthcare Semantic Models
5. The Security and Privacy Aspects in Semantic Web enabled IoT based Healthcare Information Systems
6. Knowledge-based System as a Context-aware Approach for the Internet of Medical Connected Objects
7. Towards a Knowledge Graph for Medical Diagnosis: Issues and Usage Scenarios
8. A Naturopathy Knowledge Graph and Recommendation System to Boost the Immune System
9. SAREF4EHAW-Compliant Knowledge Discovery and Reasoning \\for IoT-based Preventive Healthcare and Well-Being
10. Reasoning Over Personalized Healthcare Knowledge Graph: A Case Study of Patients with Allergies and Symptoms
11. Integrated Context-aware Ontology for MNCH Decision Support
12.� IntelliOntoRec: A Knowledge Infused Semiautomatic Approach for Ontology Formulation in Healthcare and Medical Science

Authors

Sanju Tiwari Senior Researcher, Autonomous University of Tamaulipas, Victoria, Tamaulipas, Mexico. Dr Sanju Tiwari is a Senior Researcher at Universidad Autonoma de Tamaulipas, Mexico. She is DAAD Post-Doc-Net AI Fellow for 2021. She previously worked as a Post-Doctoral Researcher in the Ontology Engineering Group, Universidad Polytecnica de Madrid, Spain. Her research focuses on Semantic Web, Knowledge Graphs, Artificial Intelligence and Ontology Engineering. She has authored/edited four Books. She has worked as a Guest Editor for IGI-Global and Inderscience, Multimedia Tools and Applications Journal (MTAP) Journals and is currently working as Guest Editor for the the Journal of Cyber Security and Mobility, and IJWIS, Emerald . Sanju is General Chair (KGSWC 2020-21) and Program Chair for different International Conferences and Workshops (FTSE-2021, AMLDA-2021, RTIP2R-2021-22). Fernando Ortiz Rodriguez Full Professor, Autonomous University of Tamaulipas, Victoria, Tamaulipas, Mexico. Dr. Rodriguez is a Full Professor and is the Social Science Research Center Director at Tamaulipas Autonomous University. Before this, he was the Executive Director at the International Institute of Studies (IIES); he created the First Business School in Tamaulipas, Mexico, and before this, he was the Information Technology Manager at Emerson Electric, where he developed more than 40 software's, some of them used globally in Emerson and achieved technology convergence implementing the first efforts on IoT and Industry 4.0
He is a member of National Systems Researchers (SNI) of the National Council of Science and Technology (CONACYT). He published several articles, book chapters, and books in prestigious editorials. He has guided more than fifteen bachelor's and five postgraduate theses. Additionally, he has more than ten software patents. He received a Latin-American award (U-Gob) for implementing and developing software to help with Covid-19 diagnosis in Mexico. M.A. Jabbar Professor and Head of the Department of Computer Science and Engineering, Vardhaman College of Engineering, Hyderabad, Telangana, India. Dr. Jabbar is Professor and Head of the Department of Computer Science and Engineering, Vardhaman College of Engineering, Hyderabad, Telangana, India. He obtained his PhD from JNTUH, Hyderabad, and Telangana, India. He has been teaching for more than 20 years. His research interests include Artificial Intelligence, Big Data Analytics, Bioinformatics, Cyber Security, Machine Learning, Attack Graphs, and Intrusion Detection Systems. He has published more than 57 papers in various journals and conferences. He published 5 patents in machine learning and allied areas and one book, Heart Disease Data Classification using Data Mining Techniques (LAP LAMBERT Academic, 2019). He served as a technical committee member for more than 70 international conferences. He is Guest Editor for The Fusion of Internet of Things, AI, and Cloud Computing In Health Care: Opportunities and Challenges (Springer) Series, and Deep Learning in Biomedical and Health Informatics: Current Applications and Possibilities (CRC Press); Guest Editor for Emerging Technologies and Applications for a Smart and Sustainable World (Bentham Science); Guest editor for Machine Learning Methods for Signal, Image and Speech Processing (River Publishing). He is a senior member of IEEE, and Lifetime member of the Computer Society of India (CSI) and the Indian Science Congress Association (ISCA). He is chair of the IEEE CS chapter Hyderabad Section. He has also served as a member of the Machine Intelligence Laboratory, USA (MIRLABS) and USERN, Iran, and Asia Pacific Institute of Science and Engineering (APISE) Hong Kong.