Preface xvii 1 A Look at IIoT: The Perspective of IoT Technology Applied in the Industrial Field 1 Ana Carolina Borges Monteiro, Reinaldo Padilha França, Rangel Arthur, Yuzo Iano, Andrea Coimbra Segatti, Giulliano Paes Carnielli, Julio Cesar Pereira, Henri Alves de Godoy and Elder Carlos Fernandes 1.1 Introduction 2 1.2 Relationship Between Artificial Intelligence and IoT 5 1.2.1 AI Concept 6 1.2.2 IoT Concept 10 1.3 IoT Ecosystem 15 1.
3.1 Industry 4.0 Concept 18 1.3.2 Industrial Internet of Things 19 1.4 Discussion 21 1.5 Trends 23 1.6 Conclusions 24 References 26 2 Analysis on Security in IoT Devices--An Overview 31 T.
Nalini and T. Murali Krishna 2.1 Introduction 32 2.2 Security Properties 33 2.3 Security Challenges of IoT 34 2.3.1 Classification of Security Levels 35 2.3.
1.1 At Information Level 36 2.3.1.2 At Access Level 36 2.3.1.3 At Functional Level 36 2.
3.2 Classification of IoT Layered Architecture 37 2.3.2.1 Edge Layer 37 2.3.2.2 Access Layer 37 2.
3.2.3 Application Layer 37 2.4 IoT Security Threats 38 2.4.1 Physical Device Threats 39 2.4.1.
1 Device-Threats 39 2.4.1.2 Resource Led Constraints 39 2.4.2 Network-Oriented Communication Assaults 39 2.4.2.
1 Structure 40 2.4.2.2 Protocol 40 2.4.3 Data-Based Threats 41 2.4.3.
1 Confidentiality 41 2.4.3.2 Availability 41 2.4.3.3 Integrity 42 2.5 Assaults in IoT Devices 43 2.
5.1 Devices of IoT 43 2.5.2 Gateways and Networking Devices 44 2.5.3 Cloud Servers and Control Devices 45 2.6 Security Analysis of IoT Platforms 46 2.6.
1 ARTIK 46 2.6.2 GiGA IoT Makers 47 2.6.3 AWS IoT 47 2.6.4 Azure IoT 47 2.6.
5 Google Cloud IoT (GC IoT) 48 2.7 Future Research Approaches 49 2.7.1 Blockchain Technology 51 2.7.2 5G Technology 52 2.7.3 Fog Computing (FC) and Edge Computing (EC) 52 References 54 3 Smart Automation, Smart Energy, and Grid Management Challenges 59 J.
Gayathri Monicka and C. Amuthadevi 3.1 Introduction 60 3.2 Internet of Things and Smart Grids 62 3.2.1 Smart Grid in IoT 63 3.2.2 IoT Application 64 3.
2.3 Trials and Imminent Investigation Guidelines 66 3.3 Conceptual Model of Smart Grid 67 3.4 Building Computerization 71 3.4.1 Smart Lighting 73 3.4.2 Smart Parking 73 3.
4.3 Smart Buildings 74 3.4.4 Smart Grid 75 3.4.5 Integration IoT in SG 77 3.5 Challenges and Solutions 81 3.6 Conclusions 83 References 83 4 Industrial Automation (IIoT) 4.
0: An Insight Into Safety Management 89 C. Amuthadevi and J. Gayathri Monicka 4.1 Introduction 89 4.1.1 Fundamental Terms in IIoT 91 4.1.1.
1 Cloud Computing 92 4.1.1.2 Big Data Analytics 92 4.1.1.3 Fog/Edge Computing 92 4.1.
1.4 Internet of Things 93 4.1.1.5 Cyber-Physical-System 94 4.1.1.6 Artificial Intelligence 95 4.
1.1.7 Machine Learning 95 4.1.1.8 Machine-to-Machine Communication 99 4.1.2 Intelligent Analytics 99 4.
1.3 Predictive Maintenance 100 4.1.4 Disaster Predication and Safety Management 101 4.1.4.1 Natural Disasters 101 4.1.
4.2 Disaster Lifecycle 102 4.1.4.3 Disaster Predication 103 4.1.4.4 Safety Management 104 4.
1.5 Optimization 105 4.2 Existing Technology and Its Review 106 4.2.1 Survey on Predictive Analysis in Natural Disasters 106 4.2.2 Survey on Safety Management and Recovery 108 4.2.
3 Survey on Optimizing Solutions in Natural Disasters 109 4.3 Research Limitation 110 4.3.1 Forward-Looking Strategic Vision (FVS) 110 4.3.2 Availability of Data 111 4.3.3 Load Balancing 111 4.
3.4 Energy Saving and Optimization 111 4.3.5 Cost Benefit Analysis 112 4.3.6 Misguidance of Analysis 112 4.4 Finding 113 4.4.
1 Data Driven Reasoning 113 4.4.2 Cognitive Ability 113 4.4.3 Edge Intelligence 113 4.4.4 Effect of ML Algorithms and Optimization 114 4.4.
5 Security 114 4.5 Conclusion and Future Research 114 4.5.1 Conclusion 114 4.5.2 Future Research 114 References 115 5 An Industrial Perspective on Restructured Power Systems Using Soft Computing Techniques 119 Kuntal Bhattacharjee, Akhilesh Arvind Nimje, Shanker D. Godwal and Sudeep Tanwar 5.1 Introduction 120 5.
2 Fuzzy Logic 121 5.2.1 Fuzzy Sets 121 5.2.2 Fuzzy Logic Basics 122 5.2.3 Fuzzy Logic and Power System 122 5.2.
4 Fuzzy Logic--Automatic Generation Control 123 5.2.5 Fuzzy Microgrid Wind 123 5.3 Genetic Algorithm 123 5.3.1 Important Aspects of Genetic Algorithm 124 5.3.2 Standard Genetic Algorithm 126 5.
3.3 Genetic Algorithm and Its Application 127 5.3.4 Power System and Genetic Algorithm 127 5.3.5 Economic Dispatch Using Genetic Algorithm 128 5.4 Artificial Neural Network 128 5.4.
1 The Biological Neuron 129 5.4.2 A Formal Definition of Neural Network 130 5.4.3 Neural Network Models 131 5.4.4 Rosenblatt''s Perceptron 131 5.4.
5 Feedforward and Recurrent Networks 132 5.4.6 Back Propagation Algorithm 133 5.4.7 Forward Propagation 133 5.4.8 Algorithm 134 5.4.
9 Recurrent Network 135 5.4.10 Examples of Neural Networks 136 5.4.10.1 AND Operation 136 5.4.10.
2 OR Operation 137 5.4.10.3 XOR Operation 137 5.4.11 Key Components of an Artificial Neuron Network 138 5.4.12 Neural Network Training 141 5.
4.13 Training Types 142 5.4.13.1 Supervised Training 142 5.4.13.2 Unsupervised Training 142 5.
4.14 Learning Rates 142 5.4.15 Learning Laws 143 5.4.16 Restructured Power System 144 5.4.17 Advantages of Precise Forecasting of the Price 145 5.
5 Conclusion 145 References 146 6 Recent Advances in Wearable Antennas: A Survey 149 Harvinder Kaur and Paras Chawla 6.1 Introduction 150 6.2 Types of Antennas 153 6.2.1 Description of Wearable Antennas 153 6.2.1.1 Microstrip Patch Antenna 153 6.
2.1.2 Substrate Integrated Waveguide Antenna 153 6.2.1.3 Planar Inverted-F Antenna 153 6.2.1.
4 Monopole Antenna 153 6.2.1.5 Metasurface Loaded Antenna 154 6.3 Design of Wearable Antennas 154 6.3.1 Effect of Substrate and Ground Geometries on Antenna Design 154 6.3.
1.1 Conducting Coating on Substrate 154 6.3.1.2 Ground Plane With Spiral Metamaterial Meandered Structure 157 6.3.1.3 Partial Ground Plane 158 6.
3.2 Logo Antennas 159 6.3.3 Embroidered Antenna 159 6.3.4 Wearable Antenna Based on Electromagnetic Band Gap 160 6.3.5 Wearable Reconfigurable Antenna 161 6.
4 Textile Antennas 162 6.5 Comparison of Wearable Antenna Designs 168 6.6 Fractal Antennas 168 6.6.1 Minkowski Fractal Geometries Using Wearable Electro-Textile Antennas 171 6.6.2 Antenna Design With Defected Semi-Elliptical Ground Plane 172 6.6.
3 Double-Fractal Layer Wearable Antenna 172 6.6.4 Development of Embroidered Sierpinski Carpet Antenna 172 6.7 Future Challenges of Wearable Antenna Designs 174 6.8 Conclusion 174 References 175 7 An Overview of IoT and Its Application With Machine Learning in Data Center 181 Manikandan Ramanathan and Kumar Narayanan 7.1 Introduction 181 7.1.1 6LoWPAN 183 7.
1.2 Data Protocols 185 7.1.2.1 CoAP 185 7.1.2.2 MQTT 187 7.
1.2.3 Rest APIs 187 7.1.3 IoT Components 189 7.1.3.1 Hardware 190 7.
1.3.2 Middleware 190 7.1.3.3 Visualization 191 7.2 Data Center and Internet of Things 191 7.2.
1 Modern Data Centers 191 7.2.2 Data Storage 191 7.2.3 Computing Process 192 7.2.3.1 Fog Computing 192 7.
2.3.2 Edge Computing 194 7.2.3.3 Cloud Computing 194 7.2.3.
4 Distributed Computing 195 7.2.3.5 Comparison of Cloud Computing and Fog Computing 196 7.3 Machine Learning Models and IoT 196 7.3.1 Classifications of Machine Learning Supported in IoT 197 7.3.
1.1 Supervised Learning 197 7.3.1.2 Unsupervised Learning 198 7.3.1.3 Reinforcement Learning 198 7.
3.1.4 Ensemble Learning 199 7.3.1.5 Neural Network 199 7.4 Challenges in Data Center and IoT 199 7.4.
1 Major Challenges 199 7.5 Conclusion 201 References 201 8 Impact of IoT to Meet Challenges in Drone Delivery System 203 J. Ranjani, P. Kalaichelvi, V.K.G Kalaiselvi, D. Deepika Sree and K. Swathi 8.
1 Introduction 204 8.1.1 IoT Components 204 8.1.2 Main Division to Apply IoT in Aviation 205 8.1.3 Required Field of IoT in Aviation 206 8.1.
3.1 Airports as Smart Cities or Airports as Platforms 207 8.1.3.2 Architecture of Multidrone 208 8.1.3.3 The Multidrone Design has the Accompanying Prerequisites 208 8.
2 Literature Survey 209 8.3 Smart Airport Architecture 211 8.4 Barriers to IoT Implementation 215 8.4.1 How is the Internet of Things Converting the Aviation Enterprise? 216 8.5 Current Technologies in Aviation Industry 216 8.5.1 Methodology or Research Design 217 8.
6 IoT Adoption Challenges 218 8.6.1 Deployment of IoT Applications on Broad Scale Includes the Underlying Challenges 218 8.7 Transforming.