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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Dr. Sanju Tiwari is a Professor at Sharda University, Greater Noida, India; as well as CEO and Founder of ShodhGuru Research Labs, India. She is DAAD Post-Doc-Net AI Fellow for 2021 and visited different German Universities (Leibniz University Hannover, Leipzig University, Leipzig, Lubeck University and Luephana University Luneburg) in June 2022 under this DAAD fellowship. She is a Mentor of Google Summer of Code (GSoC 2022-23) at DBpedia and a member of InfAI, Leipzig University, Germany. She is also working as a curator of ORKG Grant Program, at TIB Hannover, Germany. She also appointed as Ph.D. Co-Supervisor at Rai University, Gujarat, India. She has worked as a Post-Doctoral Researcher in Ontology Engineering Group, Universidad Politecnica De Madrid, Spain. Prior to this, she worked as a Research Associate for a sponsored research project “Intelligent Real-time Situation Awareness and Decision Support System for Indian Defence” funded by DRDO, New Delhi, India. Her current research interests include, Ontology Engineering, Knowledge Graphs, Linked Data, Artificial Intelligence. She has to-date published >100 research papers and 6 Scopus indexed Books. She has edited books based on Semantic Web in IoT, Personal Knowledge Graphs and Semantic AI in Knowledge Graphs.
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.
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.
The power of IoT-based semantic models in eHealth is being harnessing by clinical researchers, clinicians, and other medical staff in order to observe the real world and generate diagnoses and treatments. Continuous health monitoring is a strong solution which can provide eHealth services to a community through the use of IoT-based devices which 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. Semantic Models in IoT and eHealth Applications explores the key role of semantic web modelling 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 adopting semantic web 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.
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