Internet of Things and Fog Computing-Enabled Solutions for Real-Life Challenges

Description

In today’s world, the use of technology is growing rapidly, and people need effective solutions for their real-life problems. This book discusses smart applications of associated technologies to develop cohesive and comprehensive solutions for the betterment of humankind. It comprehensively covers the effective use of the Internet of Things (IoT), wireless sensor network, wearable sensors, body area network, cloud computing, and distributed computing methodologies. The book comprehensively covers IoT and fog computing sensor supported technologies or protocols including web of things, near-field communication, 6LoWPAN, LoRAWAN, XMPP, DDS, LwM2M, Mesh Protocol, and radio-frequency identification. The book- Discusses smart applications to develop cohesive and comprehensive solutions for real-life problems. Covers analytical descriptions with appropriate simulation and prototype models. Examines the role of IoT and fog computing technologies during global emergency situations. Discusses key technologies including cloud computing, 5G communication, big data, artificial intelligence, control systems, and wearable sensors. The text is primarily written for graduate students, and academic researchers working in diverse fields of electrical engineering, biomedical engineering, electronics and communication engineering, computer engineering, and information technology. Cover Half Title Title Page Copyright Page Table of Contents Preface About the Editors Contributors 1 Fog Computing Fundamentals in the Internet of Things: A Taxonomy, Survey, and Future Directions 1.1 Introduction 1.2 What Is Internet of Things 1.2.1 How IoT Works 1.2.2 IoT-Enabling Technology 1.3 Cloud Computing 1.3.1 Cloud Layers 1.3.2 Cloud Computing Architecture 1.3.3 Benefits of Cloud Computing 1.4 Fog Computing 1.4.1 History of Fog Computing 1.4.2 How Fog Computing Works 1.4.3 Application of Fog Computing 1.4.4 Fog Computing Benefits and Drawbacks 1.4.5 What Materializes Inside the Nodes of Fog and the Cloud? 1.4.6 IoT and Fog Computing 1.4.7 How IoT Actually Relates to Your Enterprise 1.4.8 How IoT Actually Relates to Your Infrastructure 1.5 How to Trace and Save You in COVID-19 Network Transmission With the Aid of Fog Computing 1.5.1 Contextual and Problems 1.5.2 Scope 1.5.2.1 Implementation Overview 1.6 Conclusion References 2 Role of IoT to Control the Movement of Infections During Pandemic 2.1 Introduction 2.2 The Internet of Things 2.3 Controlling Social Distances Using IoT 2.4 Early Diagnosis of Infection 2.5 Remote Patient Monitoring 2.6 Quarantine Control 2.7 IoT Applications 2.8 Future of the Internet of Medical Things 2.9 Conclusion References 3 Internet of Things (IoT)-Based Smart Farming System: A Broad Study of Emerging Technologies 3.1 Introduction 3.2 Significant Applications 3.2.1 Soil Sampling and Mapping 3.2.2 Water System 3.2.3 Manure 3.2.4 Yield Observation, Anticipating, and Accumulation 3.3 Advanced Agricultural Practices 3.3.1 Green House Farming 3.3.2 Vertical Farming 3.3.3 Hydroponic 3.3.4 Phenotyping 3.4 Significant Equipment and Technologies 3.4.1 Modern Tractor 3.4.1.1 Event Detection Algorithm 3.4.1.2 Design of the Descending Seed Course Monitoring (DSCM) Appliance 3.4.2 Collecting Robots 3.4.3 Correspondence in Agriculture 3.4.3.1 Cellular Communication 3.4.3.2 Zigbee 3.4.3.3 Bluetooth 3.4.3.4 LoRa 3.4.3.5 Sigfox 3.5 Cloud Computing 3.6 Conclusion References 4 IoT and FOG Space-Time Particulate Matter (PM2.5) Concentration Forecasting for IoT-Based Air Pollution Monitoring Systems 4.1 Introduction 4.2 IoT- Based Air Quality Monitoring 4.3 Related Works 4.4 Overview 4.4.1 Data Description 4.4.2 Problem Formulation 4.5 Proposed Methodology 4.5.1 Proposed CNN-Based Encoder 4.5.2 Proposed LSTM for Learning Patterns in the Series Represented in Latent Space 4.5.3 Modelling 4.6 Evaluation Metrics 4.7 Experiments and Results 4.7.1 Performance Comparison With Baseline Models 4.7.2 Effectiveness of 1D-CNN in the Proposed CNN-LSTM Architecture 4.8 Conclusion References 5 Model Predictive-Based Control for Supplies of Medicines During COVID-19 5.1 Introduction 5.2 System Model 5.3 Problem Formulation 5.4 System Dynamics 5.4.1 Simulation Results 5.5 Demand Forecasting 5.6 Conclusion References 6 Role of Swarm Intelligence for Health Monitoring and Related Actions 6.1 Introduction 6.2 Proposed Technology 6.2.1 Sensors 6.2.2 Humidity and Temperature Sensors 6.2.3 Heart Rate Sensor 6.2.4 Accelerometer 6.2.5 Oximeter 6.2.6 Microcontroller/control Unit 6.2.7 Wireless Communication 6.2.8 Bluetooth 6.2.9 Wireless Fidelity (Wi-Fi) 6.2.10 IoT Server 6.2.11 Notifications of an Emergency 6.3 Obstacles and Constraints 6.3.1 Expenses for Servicing and Upkeep 6.3.2 Consumption of Energy 6.3.3 Confidentiality and Security of Data 6.3.4 The Administration of Data 6.3.5 Excavation of New Diseases 6.4 Potential Future Applications 6.4.1 Health-Related Internet of Things Services 6.4.2 Ambient Assisted Living (ALL) 6.4.3 The Importance of Mobile Connection in the IoT 6.4.4 Computed Intelligence 6.4.5 Healthcare Services in the Community 6.4.6 Information On Children’s Health (ICH) 6.4.7 Drug Adverse Response (DAR) 6.5 Real-Life Challenges and Their Solutions 6.5.1 Scheduling/load Balancing 6.5.2 Clustering 6.5.3 Optimization 6.5.4 Routing 6.6 Conclusion Acknowledgments References 7 Real-Time Implementation of an Implantable Antenna Using Chicken Swarm Optimization for IoT-Based Wearable Healthcare … 7.1 Introduction 7.2 Literature Review 7.3 Proposed Methodology 7.4 Results and Performance Analysis 7.4.1 Low Complex Channel Estimation Model 7.4.2 Data Preprocessing 7.4.3 Chicken Swarm Optimization (CSO) 7.4.4 Algorithm for CSO 7.4.5 Cooperative Antenna Selection – Neural Network Classifier 7.4.6 Gain 7.4.7 Mutual Coupling 7.4.8 Specific Absorption Rate (SAR) 7.4.9 Bandwidth 7.4.10 Efficiency 7.5 Conclusion and Future Discussion References 8 Intelligent Traffic Light Systems for the Smart Cities 8.1 Introduction 8.2 Traffic Light Control System 8.2.1 Conventional Traffic Light System 8.2.2 Intelligent Traffic Light System 8.3 Basic Electronic Circuit of Intelligent Traffic Light System 8.4 Wireless Communication Network-Based Centralized Traffic Management System 8.5 Fog Computing-Based Smart Traffic Control Using Phase Optimization [13] 8.6 Conclusions References 9 Case Study On Fog Computing With the Integration of Internet of Things: Applications, Challenges, and Future Directions 9.1 Introduction 9.1.1 Elements of IoT 9.2 Technologies Involved in IoT and Fog Computing 9.2.1 Wireless Sensor Network 9.3 Characteristics of Fog Computing 9.4 Fog Computing Principles 9.5 Fog Computing Architecture 9.6 Application of IoT and Fog Computing 9.6.1 Energy Efficient Datacenter 9.6.2 Home Automation 9.6.3 IoT in Agriculture 9.6.4 Reducing Pollution 9.6.5 Smart Transport System 9.6.6 Traffic Surveillance 9.6.7 Intelligent Parking Monitoring System 9.6.8 Safety Management 9.6.9 Traffic Lights Monitoring 9.6.10 Smart Water Management 9.6.11 Health Care Management System 9.6.12 Forest Fire Detection 9.6.13 IoT in Data Analytics 9.6.14 IoT-Based Real-Time Analytics in Fog Computing 9.6.15 IoT in Business Process 9.6.16 IoT Security 9.6.17 Identity Management and Privacy Using IoT 9.6.18 IoT in Education Sector 9.6.19 IoT Role in Oil and Gas Industry 9.7 Advantages of Using Fog Computing for IoT 9.8 Challenges Faced By Fog Architecture 9.9 Conclusion References 10 Virtual Health Management Through IoT 10.1 Introduction 10.2 IoT and Its Background for COVID-19 Pandemic 10.3 Cloud Computing Assistance in COVID-19 10.4 Benefits of Cloud Computing 10.4.1 Diversity 10.4.2 Processing Power 10.4.3 Data Sharing 10.4.4 Expenses 10.5 Processes Involved in IoT for COVID-19 10 5.1 Convenience 10.5.2 Timeless 10.5.3 Accurateness 10.5.4 Safety and Insurance 10.5.5 Mobility 10.6 IOT for Verification and Tracking 10.7 Problems of Handling in Tracking for COVID-19 10.8 Next-Generation Proposed Tools and Discussions 10.8.1 Deep Machine Learning 10.8.2 New Generation Challenges 10.8.3 Advantages 10.8.4 Disadvantages 10.9 Key IoT Tools to Fight COVID-19 Pandemic 10.10 Wearable IOT Devices 10.11 Drones to Combat COVID-19 10.11.1 Uses of Drones 10.11.2 Transportation 10.11.3 Aerial Spraying 10.11.4 Surveillance of the Public Spaces 10.12 Robots During COVID-19 Situation 10.13 Internet of Things Buttons 10.13.1 Advantages 10.14 Conclusion References Index