Patel A., Debnath N.C. (eds.) Semantic Technologies for Intelligent Industry 4.0 Applications

River Publishers, 2023. — 395 p. — (River Publishers Series in Computing and Information Science and Technology). — ISBN: 978-87-7022-996-8.Semantic technologies work with the concepts and relations that are very close to the workings of the human brain. By using these technologies, data becomes a real-world entity rather than a string of characters. Semantic technologies are highly valuable tools to simplify the existing problems of the industry, leading to new opportunities. However, some challenges need to be addressed to make industrial applications and machines smarter. The proposed book aims to provide a roadmap for semantic technolo­gies and highlights the role of these technologies in the industry. The book covers semantic search engine, semantic web services, semantic web of things, AI-compatible key hardware design, knowledge-graph-based integration, ontology development methodologies, knowledge extraction, prediction of semantic relations of biocontrol agents, integration of biomedical knowledge, semantic checking of information support, a tool for automatic anomaly identification in OWL ontologies, challenges and prospects of industry 4.0, and ontological modeling.As the world enters the era of big data, there is a serious need to give a semantic perspective to the data 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 modeling 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 close to the workings of the human brain. They provide a semantic representation of any data format: unstructured or semi-structured. As a consequence, data becomes a 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, some challenges 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 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 toward 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.Semantic Search Engine in Industry 4.0 Esingbemi Princewill Ebietomere and Godspower Osaretin Ekuobase.
Semantic Web Services: The Interoperable Middleware Technology for Industry 4.0.
Semantic Web of Things for Healthcare Interoperability using IoMT Technologies.
AI Compatible Key Hardware Design for Smart Warehouse: A Practical Implementation.
A Knowledge Graph-based Integration Approach for Research Digital Artifacts.
A Review of Ontology Development Methodologies: The Way Forward for Robust Ontology Design.
Semantic Web: An Overview and a .net-based Tool for Knowledge Extraction and Ontology Development.
AedesOnt: Ontology for Aedes Mosquito Vectors to Predict Semantic Relations of Biocontrol Agents.
Paradigms for Integration of Biomedical Knowledge with.
Patients’ Records: Brief Trajectory and Roles of Ontology.
Semantic Checking of Information Support for Heterogeneous Resources of Train Speed Restrictions by Ontological Means.
A Tool for Automatic Anomaly Identification in OWL Ontologies.
Ontological Modeling for the Personalization of Learning Environment of the University.