Semantic Technologies for Intelligent Industry 4.0 Applications
- 362 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Semantic Technologies for Intelligent Industry 4.0 Applications
About this book
As the world enters the era of big data, there is a serious need to give a semantic perspective to the data in order to find unseen patterns, derive meaningful information, and make intelligent decisions. Semantic technologies offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. These technologies reduce the problem of large semantic loss in the process of modelling knowledge, and provide sharable, reusable knowledge, and a common understanding of the knowledge. As a result, the interoperability and interconnectivity of the model make it priceless for addressing the issues of querying data. These technologies work with the concepts and relations that are very lose to the working of the human brain. They provide a semantic representation of any data format: unstructured or semi-structured. As a consequence, data becomes real-world entity rather than a string of characters. For these reasons, semantic technologies are highly valuable tools to simplify the existing problems of the industry leading to new opportunities. However, there are some challenges that need to be addressed to make industrial applications and machines smarter.
This book aims to provide a roadmap for semantic technologies and highlights the role of these technologies in industry. The book also explores the present and future prospects of these semantic technologies along with providing answers to various questions like: Are semantic technologies useful for the next era (industry 4.0)? Why are semantic technologies so popular and extensively used in the industry? Can semantic technologies make intelligent industrial applications? Which type of problem requires the immediate attention of researchers? Why are semantic technologies very helpful in people's future lives? This book will potentially serve as an important guide towards the latest industrial applications of semantic technologies for the upcoming generation, and thus becomes a unique resource for scholars, researchers, professionals and practitioners in the field.
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Table of contents
- Cover
- Half Title
- Series
- Title
- Copyright
- Contents
- Preface
- List of Contributors
- List of Figures
- List of Tables
- List of Abbreviations
- 1 Semantic Search Engine in Industry 4.0 Esingbemi Princewill Ebietomere and Godspower Osaretin Ekuobase
- 2 Semantic Web Services: The Interoperable Middleware Technology for Industry 4.0 Godspower Osaretin Ekuobase and Esingbemi Princewill Ebietomere
- 3 Semantic Web of Things for Healthcare Interoperability using IoMT Technologies Rajani Reddy Gorrepati, Prathiba Jonnala, Sitaramanjaneya Reddy Guntur, and Do-Hyeun Kim
- 4 AI Compatible Key Hardware Design for Smart Warehouse: A Practical Implementation Ngoc-Bich Le, Ngoc-Huan Le, Manh-Kha Kieu, Xuan-Hung Nguyen, Vu-Anh-Tram Nguyen, Tran-Thuy-Duong Ninh, Duc-Canh Nguyen, and Narayan C. Debnath
- 5 A Knowledge Graph-based Integration Approach for Research Digital Artifacts Zaenal Akbar, Arya Adhyaksa Waskita, Dadan Ridwan Saleh, Ariani Indrawati, and Yulia Aris Kartika
- 6 A Review of Ontology Development Methodologies: The Way Forward for Robust Ontology Design Enesi Femi Aminu, Ishaq Oyebisi Oyefolahan, and Muhammad Bashir Abdullahi
- 7 Semantic Web: An Overview and a .net-based Tool for Knowledge Extraction and Ontology Development Noman Islam, Darakhshan Syed, and Zubair A. Shaikh
- 8 AedesOnt: Ontology for Aedes Mosquito Vectors to Predict Semantic Relations of Biocontrol Agents G. Jeyakodi, Trisha Agarwal, and P. Shanthi Bala
- 9 Paradigms for Integration of Biomedical Knowledge with Patients’ Records: Brief Trajectory and Roles of Ontology Xia Jing, James J. Cimino, Xuequn Pan, and Shijuan Li
- 10 Semantic Checking of Information Support for Heterogeneous Resources of Train Speed Restrictions by Ontological Means V. Shynkarenko and L. Zhuchyi
- 11 A Tool for Automatic Anomaly Identification in OWL Ontologies João Paulo Orlando and Dilvan A. Moreira
- 12 Ontological Modeling for the Personalization of Learning Environment of the University Tatiana Avdeenko, Marina Murtazina, and Natalia Pustovalova
- Index
- About the Editors