Smart Connected World: Technologies and Applications Shaping the Future

✍ Scribed by Sarika Jain (editor), San Murugesan (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 229
• Category: Library

✦ Synopsis

This book provides an overview of the emerging smart connected world, and discusses the roles and the usage of underlying semantic computing and Internet-of-Things (IoT) technologies.

The book comprises ten chapters overall, grouped in two parts. Part I “Smart Connected World: Overview and Technologies” consists of seven chapters and provides a holistic overview of the smart connected world and its supporting tools and technologies. Part II “Applications and Case Studies” consists of three chapters that describe applications and case studies in manufacturing, smart cities, health, and more. Each chapter is self-contained and can be read independently; taken together, readers get a bigger picture of the technological and application landscape of the smart connected world.

This book is of interest for researchers, lecturers, and practitioners in Semantic Web, IoT and related fields. It can serve as a reference for instructors and students taking courses in hybrid computing getting abreast of cutting edge and future directions of a connected ecosystem. It will also benefit industry professionals like software engineers or data scientists, by providing a synergy between Web technologies and applications.

This book covers the most important topics on the emerging field of the smart connected world. The contributions from leading active researchers and practitioners in the field are thought provoking and can help in learning and further research. The book is a valuable resource that will benefit academics and industry. It will lead to further research and advancement of the field. Bharat K. Bhargava, Professor of Computer Science, Purdue University, United States

✦ Table of Contents

Foreword
Preface
Key Features
Chapter Preview
Part I: Smart Connected World: Overview and Technologies
Part II: Applications and Case Studies
Acknowledgments
Contents
Editors and Contributors
Abbreviations and Acronyms
Part I: Smart Connected World: Overview and Technologies
Chapter 1: Smart Connected World: A Broader Perspective
1.1 Introduction
1.2 IoT: The Trajectory of Technological Progress
1.3 Artificial Intelligence and IoT
1.3.1 Artificial Intelligence of Things
1.3.2 Ambient Intelligence (AmI)
1.3.3 AIoT on the Edge/Fog/Cloud
1.4 Potential Barriers to a Smart and Connected Ecosystem
1.4.1 Data Explosion and Actionable Insights
1.4.2 Challenges and Opportunities
1.5 Semantic Technologies as the Enabler of Smart Connected World
1.5.1 Cognitive Computing
1.5.2 The Semantic Data Model
1.5.3 Semantic Standards
1.6 Intelligent Applications in a Connected World
1.6.1 Ontologies for Sensor Network
1.6.2 Data Integration
1.6.3 Intelligent Applications
1.7 Conclusion
References
Chapter 2: Cyber-Physical-Social Systems: An Overview
2.1 Introduction
2.2 Cyber-Physical-Social Systems (CPSSs)
2.2.1 Physical Layer and Communications
2.2.2 Social Layer
2.2.3 Cyber Layer and Computing Techniques
2.3 Applications of CPSS
2.3.1 CPSS in Transportation
2.3.2 CPSS in Smart City
2.3.3 CPSS in Industry
2.3.4 CPSS in Healthcare
2.3.5 CPSS in Education
2.3.6 CPSS in Entertainment
2.3.7 CPSS in Social Networks
2.3.8 CPSS in Digital Commerce
2.4 Challenges in CPSSs
2.4.1 Safety and Security
2.4.2 Privacy and Ethical Issues
2.4.3 Interdependence and Compatibility
2.5 Conclusion
References
Chapter 3: The Web of Things Ecosystem
3.1 Introduction
3.2 Architecture of WoT
3.3 Web of Things Applications
3.3.1 Crowdsourced Applications
3.3.2 Conventional IoT Applications
3.4 Challenges of the Web of Things Ecosystem
3.5 Existing Semantic Approaches
3.6 Open Issues
3.7 Conclusion
References
Chapter 4: Semantic Intelligence in Big Data Applications
4.1 Introduction
4.2 From Data to Big Data to Smart Data Processing
4.2.1 Variety of Data Sources
4.2.2 The Need for Semantic Standards
4.2.3 Semantic Integration and Semantic Data Lake Concept
4.3 Semantics and Data Analytics
4.4 Semantics and Business Intelligence Applications
4.5 Role of Semantics in (Big) Data Tools
4.6 Summary
References
Chapter 5: Securing Smart Connected World: Key Challenges and Possible Solutions
5.1 Introduction
5.2 Privacy
5.2.1 Data Privacy
5.2.2 Contextual Privacy
5.2.3 Privacy-Preserving Data Processing
5.3 Authentication and Access Control
5.4 Trust Management
5.5 Securing Collaboration with Semantic Solutions
5.6 Summary
References
Chapter 6: Ontology for Data Analytics
6.1 What Is Data Analytics?
6.1.1 Types of Data Analytics
6.1.1.1 Descriptive Analytics
6.1.1.2 Diagnostic Analytics
6.1.1.3 Predictive Analytics
6.1.1.4 Prescriptive Analytics
6.1.2 Processes of Data Analytics
6.2 What are Ontologies?
6.2.1 Ontologies and Their Applications
6.2.2 Ontology and Data Analytics
6.3 Different Perspectives on Ontology and Data Analytics
6.3.1 Business Intelligence
6.3.2 Healthcare
6.3.3 Information Retrieval and Ontology
6.3.4 Social Network Analysis
6.4 The Present and Future of Semantic Data Analytics
6.5 Conclusion
References
Chapter 7: Multilingual Semantic Representation of Smart Connected World Data
7.1 Introduction
7.2 Motivation
7.3 Ontology Engineering Methodology
7.4 Making Ontologies Multilingual
7.4.1 Inclusion of Multilingual Information in the Ontology
7.4.2 One Conceptualization per Linguistic Anthropology
7.4.3 Association of External Multilingual Information
7.5 Smart Devices (Applications Using AIoT)
7.5.1 Self-Driving Vehicles
7.5.2 Smart Cameras
7.6 Conclusion
References
Part II: Applications and Case Studies
Chapter 8: Smart Manufacturing
8.1 Introduction to Smart Manufacturing
8.1.1 The Manufacturing Process
8.1.2 Making Manufacturing Smarter
8.2 The (Industrial) Internet of Things
8.2.1 Sensing Technology
8.2.1.1 Tool Condition Monitoring
8.2.1.2 Machine Tool Health Monitoring
8.2.1.3 Additive Process Performance
8.2.1.4 Sub-surface Material Quality
8.2.1.5 Legacy Devices and Low-Cost Sensing
8.2.2 Smart Hand Tools
8.2.3 Location Tracking Technologies
8.2.4 Industrial Machinery Connectivity
8.2.5 Moving to Wireless Connectivity
8.3 From Sensors to Business Value
8.3.1 Cloud Computing
8.3.2 Big Data Analytics
8.3.3 Artificial Intelligence
8.3.3.1 Predictive Maintenance
8.3.3.2 Identifying Defects and Quality Control
8.3.3.3 Robots and Automation
8.4 Beyond the Physical World
8.4.1 Digital Twin
8.4.2 Extended Reality
8.4.3 Simulating Manufacturing
8.5 Summary
References
Chapter 9: Role of Semantics in Smart City Applications
9.1 Introduction
9.2 Principles of Semantic Applications of Smart Cities
9.2.1 Ontologies for Smart Cities
9.2.2 Data
9.2.3 Energy-Saving
9.2.4 Security and Safety
9.2.5 Traffic
9.2.6 Healthcare and Social Applications
9.3 Role of Semantics in Smart Cities
9.3.1 The Role of Semantics and IoT
9.3.2 Sustainable Development and Its Impacts
9.4 Challenges for Semantics in Smart City Applications
9.5 Factors to Compare the Ontologies of Smart Cities and IoT
9.6 Summary
References
Chapter 10: Detection of Depression Signals from Social Media Data
10.1 Introduction
10.2 Background Study
10.3 Challenges of Social Web
10.4 Microblogging (e.g., Twitter)
10.5 Semantics Microblogging
10.6 Semantic Technologies and Their Importance for Social Media and Depression Signals
10.6.1 Emotion Ontology
10.6.2 Mental Disease Ontology
10.7 Sample Case Study: Depression Detection from Twitter Dataset Using Naïve Bayes Classifier for Sentiment Analysis
10.7.1 Data Pre-processing
10.7.2 Naïve Bayes Classifier for Sentiment Analysis
10.7.3 Testing the Model Using Naïve Bayes Classifier
10.8 Further Work
10.9 Summary of the Chapter
References
Index