Tools, languages, methodologies for representing semantics on the web of things / edited by Shikha Mehta [and more]
Contributor(s): Mehta, Shikha [editor.]
Publisher: London, UK : Hoboken, NJ : ISTE, Ltd. ; Wiley, 2022Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781786307644 ; 9781394171460; 1394171463Subject(s): Semantic Web | Internet of thingsGenre/Form: Electronic books.DDC classification: 006 LOC classification: TK1505.88815Online resources: Full text available at Wiley Online Library Click here to view| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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COLLEGE LIBRARY | COLLEGE LIBRARY | 006 T618 2022 (Browse shelf) | Available |
Table of Contents
Preface xi
Shikha MEHTA, Sanju TIWARI, Patrick SIARRY and M.A JABBAR
Chapter 1 The Role of Semantic Hybrid Multi-Model Multi-Platform (SHM3P) Databases for IoT 1
Sven 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 21
Sanju 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 41
Fatima 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 61
Shachi 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 75
Dhananjay 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 93
Gerard 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 123
Ronak 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 139
Kalpana 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 155
Keshavi 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 179
Deepika 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-19 195
ANURAG 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 211
Hina 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
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
About the Author
Shikha Mehta is Associate Professor in the Department of CSE & IT, Jaypee Institute of Information Technology, India. Her research interests include machine/deep learning algorithms, nature-inspired computing and social networks analytics.
Sanju Tiwari is Senior Researcher at Universidad Autonoma de Tamaulipas, Mexico, DAAD Post-Doc-Net AI Fellow and PhD co-supervisor at Rai University, India, and has worked as a post-doctoral researcher in OEG, Universidad Politecnica de Madrid, Spain. Her research interests include artificial intelligence, knowledge graphs and ontology engineering.
Patrick Siarry is Professor in automatics and informatics at University Paris Est Créteil, France. His research interests include the design of stochastic global optimization heuristics and their applications to various engineering fields. M.A. Jabbar is Professor and Head of the Department of CSE (AI & ML), Vardhaman College of Engineering, India. His research interests include artificial intelligence, Big Data analytics, bio-informatics and machine learning.
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