This book is a guide to the combination of the Internet of Things (IoT) and the Semantic Web, covering a variety of tools, technologies and applications that serve the myriad needs of the researchers in this field. It provides a multi dimensional view of the concepts, tools, techniques and issues that are involved in the development of semantics for the Web of Things.
The various aspects studied in this book include Multi-Model Multi-Platform (SHM3P) databases for the IoT, clustering techniques for discovery services for the semantic IoT, dynamic security testing methods for the Semantic Web of Things, Semantic Web-enabled IoT integration for a smart city, IoT security issues, the role of the Semantic Web of Things in Industry 4.0, the integration of the Semantic Web and the IoT for e-health, smart healthcare systems to monitor patients, Semantic Web-based ontologies for the water domain, science fiction and searching for a job.
Author(s): Sanju Tiwari, Patrick Siarry, Shikha Mehta, M. A. Jabbar
Series: Information Systems, Web and Pervasive Computing Series
Publisher: Wiley-ISTE
Year: 2022
Language: English
Pages: 271
City: London
Cover
Title Page
Copyright Page
Contents
Preface
Chapter 1. The Role of Semantic Hybrid Multi-Model Multi-Platform (SHM3P) Databases for IoT
1.1. Introduction
1.2. Databases for multi-model data
1.3. Platforms
1.4. Variations of SHM3P DBMS
1.5. What are the benefits of SHM3P databases for IoT?
1.5.1. Data storage and placement
1.5.2. Data processing
1.5.3. IoT applications
1.6. Summary and conclusions
1.7. References
Chapter 2. A Systematic Review of Ontologies for the Water Domain
2.1. Introduction
2.2. Literature review
2.2.1. Features in the water domain
2.2.2. Semantic models in the water domain
2.2.3. A comprehensive review of ontologies in the water domain
2.3. Applications of ontologies in the water domain
2.4. Discussion and conclusion
2.5. References
Chapter 3. Semantic Web Approach for Smart Health to Enhance Patient Monitoring in Resuscitation
3.1. Introduction
3.2. Background
3.2.1. Semantic Web
3.2.2. SSN (Semantic Sensor Network) ontology
3.3. IoT Smart Health applications and semantics
3.4. Proposed approach and implementation
3.4.1. Knowledge representation
3.4.2. Ontology evaluation
3.4.3. Reasoning and querying
3.4.4. Linked Data
3.5. Conclusion
3.6. References
Chapter 4. Role of Clustering in Discovery Services for the Semantic Internet of Things
4.1. Introduction
4.2. Discovery services in IoT
4.2.1. Directory-based architectures
4.2.2. Directory-less architectures
4.3. Semantic-based architectures
4.3.1. Search engine-based
4.3.2. ONS DNS-based
4.4. Discovery services and clustering
4.5. Clustering methods in IoT
4.6. Conclusion
4.7. References
Chapter 5. Dynamic Security Testing Techniques for the Semantic Web of Things: Market and Industry Perspective
5.1. Introduction
5.2. Related studies
5.3. Background of dynamic security testing techniques
5.3.1. Black Box testing techniques
5.4. DAST using static analysis
5.4.1. Current implementation
5.5. DAST using user session
5.5.1. Current implementation
5.6. DAST using Extended Tainted Mode Model
5.6.1. Current implementation
5.7. Current issues and research directions
5.8. Conclusion
5.9. References
Chapter 6. SciFiOnto: Modeling, Visualization and Evaluation of Science Fiction Ontologies Based on Indian Contextualization with Automatic Knowledge Acquisition
6.1. Introduction
6.2. Literature survey
6.2.1. Formulation and modeling of ontologies for varied domains of importance
6.2.2. Auxiliary automatic and semi-automatic models in ontology synthesis
6.2.3. Ontology-driven systems and applications
6.2.4. Automatic Knowledge Acquisition systems
6.2.5. Science fiction as an independent domain of existence
6.3. Modeling and evaluation of the ontology
6.3.1. Ontology modeling
6.3.2. Ontology visualization
6.3.3. Ontology evaluation
6.4. Automatic Knowledge Acquisition model
6.4.1. System architecture
6.4.2. Acquisition algorithm
6.5. Conclusion
6.6. References
Chapter 7. Semantic Web-Enabled IoT Integration for a Smart City
7.1. Introduction: Semantic Web and sensors
7.2. Motivation and challenge
7.3. Literature review
7.4. Implementation of forest planting using SPARQL queries
7.4.1. Architecture sketch with conceptual diagram
7.4.2. Implementation ontology from the dataset
7.4.3. Technologies and tools
7.5. Conclusion
7.6. References
Chapter 8. Heart Rate Monitoring Using IoT and AI
8.1. Introduction
8.2. Literature survey
8.3. Heart rate monitoring system
8.4. Results and discussion
8.5. Conclusion and future works
8.6. References
Chapter 9. IoT Security Issues and Its Defensive Methods
9.1. Introduction
9.2. IoT security architecture
9.2.1. Typical IoT architecture
9.2.2. Centralized and distributed approaches over the IoT security architecture
9.2.3. IoT security architecture based on blockchain
9.2.4. Internet of Things security architecture: trust zones and boundaries
9.2.5. Threat modeling in IoT security architecture
9.3. Specific security challenges and approaches
9.3.1. Identity and authentication
9.3.2. Access control
9.3.3. Protocol and network security
9.3.4. Privacy
9.3.5. Trust and governance
9.3.6. Fault tolerance
9.4. Methodologies used for securing the systems
9.4.1. PKI and digital certificates
9.4.2. Network security
9.4.3. API security
9.4.4. Network access control
9.4.5. Segmentation
9.4.6. Security gateways
9.4.7. Patch management and software updates
9.5. Conclusion
9.6. References
Chapter 10. Elucidating the Semantic Web of Things for Making the Industry 4.0 Revolution a Success
10.1. Introduction
10.2. Correlation of the Semantic Web of Things with IR4.0
10.2.1. Smart machines
10.2.2. Smart products
10.2.3. Augmented operators
10.2.4. The Web of Things
10.2.5. Semantic Web of Things
10.3. Smart manufacturing system and ontologies
10.3.1. Vertical level integration
10.3.2. Horizontal level of integration
10.3.3. End-to-end integration
10.4. Literature survey
10.5. Conclusion and future work
10.6. References
Chapter 11. Semantic Web and Internet of Things in e-Health for Covid-19
11.1. Introduction
11.2. Dataset
11.3. Application of IoT for Covid-19
11.3.1. Continuous real-time remote monitoring
11.3.2. Remote monitoring using W-kit
11.3.3. Early identification and monitoring
11.3.4. Continuous and reliable health monitoring
11.3.5. ANN-assisted patient monitoring
11.3.6. City lockdown monitoring
11.3.7. Technologies for tracking and tracing
11.3.8. Tracking and tracing suspected cases
11.3.9. Anonymity preserving contact tracing model
11.3.10. Cognitive radio-based IoT architecture
11.3.11. Analyzing reasons for the outbreak
11.3.12. Analyzing Covid-19 cases using disruptive technology
11.3.13. Post-Covid applications
11.4. Semantic Web applications for Covid-19
11.4.1. Ontological approach for drug development
11.4.2. Early detection and diagnosis
11.4.3. Knowledge-based pre-diagnosis system
11.4.4. Semantic-based searching for online learning resources
11.4.5. Ontology-based physiological monitoring of students
11.4.6. Analysis of clinical trials
11.4.7. Data annotation of EHRs
11.4.8. Disease pattern study
11.4.9. Surveillance in primary care
11.4.10. Performance assessment of healthcare services
11.4.11. Vaccination drives and rollout strategies
11.5. Limitations and challenges of IoT and SW models
11.6. Discussion
11.7. Conclusion
11.8. References
Chapter 12. Development of a Semantic Web Enabled Job_Search Ontology System
12.1. Introduction
12.1.1. Ontology
12.1.2. Importance of ontology
12.1.3. Semantic Web and its solutions
12.1.4. Online recruitment scenarios
12.2. Review of the related work done for online recruitment
12.3. Design of “SearchAJob” ontology for the IT domain
12.3.1. Ontology structure
12.4. Implementing the proposed ontology
12.4.1. Architecture of semantics-based job ontology
12.5. Benefits of Semantic Web enabled SearchAJob system
12.6. Conclusion and future scope
12.7. References
List of Authors
Index
EULA
