Preface xiShikha MEHTA, Sanju TIWARI, Patrick SIARRY and M.A JABBAR Chapter 1 The Role of Semantic Hybrid Multi-Model Multi-Platform (SHM3P) Databases for IoT 1Sven GROPPE, Jinghua GROPPE and Tobias GROTH 1.1 Introduction 1 1.2 Databases for multi-model data 5 1.3 Platforms 7 1.4 Variations of SHM3P DBMS 13 1.5 What are the benefits of SHM3P databases for IoT? 14 1.5.1 Data storage and placement 14 1.5.2 Data processing 15 1.5.3 IoT applications 15 1.6 Summary and conclusions 16 1.7 References 16 Chapter 2 A Systematic Review of Ontologies for the Water Domain 21Sanju TIWARI and Raúl GARCÍA-CASTRO 2.1 Introduction 21 2.2 Literature review 23 2.2.1 Features in the water domain 23 2.2.2 Semantic models in the water domain 24 2.2.3 A comprehensive review of ontologies in the water domain 24 2.3 Applications of ontologies in the water domain 32 2.4 Discussion and conclusion 35 2.5 References 36 Chapter 3 Semantic Web Approach for Smart Health to Enhance Patient Monitoring in Resuscitation 41Fatima Zahra AMARA, Mounir HEMAM, Meriem DJEZZAR and Moufida MAIMOUR 3.1 Introduction 42 3.2 Background 43 3.2.1 Semantic Web 43 3.2.2 SSN (Semantic Sensor Network) ontology 44 3.3 IoT Smart Health applications and semantics 45 3.4 Proposed approach and implementation 46 3.4.1 Knowledge representation 47 3.4.2 Ontology evaluation 51 3.4.3 Reasoning and querying 51 3.4.4 Linked Data 55 3.5 Conclusion 56 3.6 References 57 Chapter 4 Role of Clustering in Discovery Services for the Semantic Internet of Things 61Shachi SHARMA 4.1 Introduction 61 4.2 Discovery services in IoT 64 4.2.1 Directory-based architectures 64 4.2.2 Directory-less architectures 66 4.3 Semantic-based architectures 67 4.3.1 Search engine-based 67 4.3.2 ONS DNS-based 68 4.4 Discovery services and clustering 68 4.5 Clustering methods in IoT 69 4.6 Conclusion 71 4.7 References 71 Chapter 5 Dynamic Security Testing Techniques for the Semantic Web of Things: Market and Industry Perspective 75Dhananjay SINGH CHAUHAN, Gaurav CHOUDHARY, Shishir Kumar SHANDILYA and Vikas SIHAG 5.1 Introduction 75 5.2 Related studies 77 5.3 Background of dynamic security testing techniques 79 5.3.1 Black Box testing techniques 80 5.4 DAST using static analysis 82 5.4.1 Current implementation 82 5.5 DAST using user session 84 5.5.1 Current implementation 84 5.6 DAST using Extended Tainted Mode Model 86 5.6.1 Current implementation 87 5.7 Current issues and research directions 88 5.8 Conclusion 89 5.9 References 89 Chapter 6 SciFiOnto: Modeling, Visualization and Evaluation of Science Fiction Ontologies Based on Indian Contextualization with Automatic Knowledge Acquisition 93Gerard DEEPAK, Ayush A KUMAR and Sheeba J PRIYADARSHINI 6.1 Introduction 94 6.2 Literature survey 97 6.2.1 Formulation and modeling of ontologies for varied domains of importance 97 6.2.2 Auxiliary automatic and semi-automatic models in ontology synthesis 97 6.2.3 Ontology-driven systems and applications 98 6.2.4 Automatic Knowledge Acquisition systems 99 6.2.5 Science fiction as an independent domain of existence 99 6.3 Modeling and evaluation of the ontology 100 6.3.1 Ontology modeling 100 6.3.2 Ontology visualization 104 6.3.3 Ontology evaluation 107 6.4 Automatic Knowledge Acquisition model 111 6.4.1 System architecture 111 6.4.2 Acquisition algorithm 113 6.5 Conclusion 119 6.6 References 119 Chapter 7 Semantic Web-Enabled IoT Integration for a Smart City 123Ronak PANCHAL and Fernando ORTIZ-RODRIGUEZ 7.1 Introduction: Semantic Web and sensors 123 7.2 Motivation and challenge 124 7.3 Literature review 124 7.4 Implementation of forest planting using SPARQL queries 125 7.4.1 Architecture sketch with conceptual diagram 125 7.4.2 Implementation ontology from the dataset 126 7.4.3 Technologies and tools 129 7.5 Conclusion 136 7.6 References 136 Chapter 8 Heart Rate Monitoring Using IoT and AI 139Kalpana MURUGAN, Cherukuri NIKHIL KUMAR, Donthu Sai SUBASH and Sangam DEVA KISHORE REDDY 8.1 Introduction 140 8.2 Literature survey 142 8.3 Heart rate monitoring system 145 8.4 Results and discussion 149 8.5 Conclusion and future works 152 8.6 References 152 Chapter 9 IoT Security Issues and Its Defensive Methods 155Keshavi NALLA and Seshu VARDHAN POTHABATHULA 9.1 Introduction 155 9.2 IoT security architecture 158 9.2.1 Typical IoT architecture 158 9.2.2 Centralized and distributed approaches over the IoT security architecture 161 9.2.3 IoT security architecture based on blockchain 163 9.2.4 Internet of Things security architecture: trust zones and boundaries 164 9.2.5 Threat modeling in IoT security architecture 168 9.3 Specific security challenges and approaches 170 9.3.1 Identity and authentication 170 9.3.2 Access control 171 9.3.3 Protocol and network security 172 9.3.4 Privacy 172 9.3.5 Trust and governance 173 9.3.6 Fault tolerance 173 9.4 Methodologies used for securing the systems 174 9.4.1 PKI and digital certificates 174 9.4.2 Network security 174 9.4.3 API security 174 9.4.4 Network access control 175 9.4.5 Segmentation 175 9.4.6 Security gateways 175 9.4.7 Patch management and software updates 175 9.5 Conclusion 176 9.6 References 176 Chapter 10 Elucidating the Semantic Web of Things for Making the Industry 4.0 Revolution a Success 179Deepika CHAUDHARY and Jaiteg SINGH 10.1 Introduction 179 10.2 Correlation of the Semantic Web of Things with IR4.0 180 10.2.1 Smart machines 181 10.2.2 Smart products 182 10.2.3 Augmented operators 182 10.2.4 The Web of Things 183 10.2.5 Semantic Web of Things 184 10.3 Smart manufacturing system and ontologies 185 10.3.1 Vertical level integration 185 10.3.2 Horizontal level of integration 185 10.3.3 End-to-end integration 185 10.4 Literature survey 188 10.5 Conclusion and future work 190 10.6 References 190 Chapter 11 Semantic Web and Internet of Things in e-Health for Covid-19 195ANURAG and Naren JEEVA 11.1 Introduction 196 11.2 Dataset 197 11.3 Application of IoT for Covid-19 198 11.3.1 Continuous real-time remote monitoring 198 11.3.2 Remote monitoring using W-kit 198 11.3.3 Early identification and monitoring 198 11.3.4 Continuous and reliable health monitoring 198 11.3.5 ANN-assisted patient monitoring 199 11.3.6 City lockdown monitoring 199 11.3.7 Technologies for tracking and tracing 199 11.3.8 Tracking and tracing suspected cases 199 11.3.9 Anonymity preserving contact tracing model 200 11.3.10 Cognitive radio-based IoT architecture 200 11.3.11 Analyzing reasons for the outbreak 200 11.3.12 Analyzing Covid-19 cases using disruptive technology 200 11.3.13 Post-Covid applications 201 11.4 Semantic Web applications for Covid-19 201 11.4.1 Ontological approach for drug development 202 11.4.2 Early detection and diagnosis 202 11.4.3 Knowledge-based pre-diagnosis system 202 11.4.4 Semantic-based searching for online learning resources 203 11.4.5 Ontology-based physiological monitoring of students 203 11.4.6 Analysis of clinical trials 203 11.4.7 Data annotation of EHRs 204 11.4.8 Disease pattern study 204 11.4.9 Surveillance in primary care 204 11.4.10 Performance assessment of healthcare services 205 11.4.11 Vaccination drives and rollout strategies 205 11.5 Limitations and challenges of IoT and SW models 205 11.6 Discussion 206 11.7 Conclusion 206 11.8 References 207 Chapter 12 Development of a Semantic Web Enabled Job_Search Ontology System 211Hina J CHOKSHI, Dhaval VYAS and Ronak PANCHAL 12.1 Introduction 211 12.1.1 Ontology 212 12.1.2 Importance of ontology 213 12.1.3 Semantic Web and its solutions 214 12.1.4 Online recruitment scenarios 214 12.2 Review of the related work done for online recruitment 215 12.3 Design of “SearchAJob” ontology for the IT domain 217 12.3.1 Ontology structure 218 12.4 Implementing the proposed ontology 222 12.4.1 Architecture of semantics-based job ontology 223 12.5 Benefits of Semantic Web enabled SearchAJob system 231 12.6 Conclusion and future scope 232 12.7 References 233 List of Authors 237 Index 241