Preface xvii 1 Introduction to the Internet of Things: Opportunities, Perspectives and Challenges 1 F. Leo John, D. Lakshmi and Manideep Kuncharam 1.1 Introduction 2 1.1.1 The IOT Data Sources 4 1.1.2 IOT Revolution 6 1.2 IOT Platform 8 1.3 IOT Layers and its Protocols 10 1.4 Architecture and Future Problems for IOT Protection 27 1.5 Conclusion 32 References 32 2 Role of Battery Management System in IoT Devices 35 R. Deepa, K. Mohanraj, N. Balaji and P. Ramesh Kumar 2.1 Introduction 36 2.1.1 Types of Lithium Batteries 36 2.1.1.1 Lithium Battery (LR) 37 2.1.1.2 Button Type Lithium Battery (BLB) 37 2.1.1.3 Coin Type Lithium Battery (CLB) 37 2.1.1.4 Lithium-Ion Battery (LIB) 37 2.1.1.5 Lithium-Ion Polymer Battery (LIP) 37 2.1.1.6 Lithium Cobalt Battery (LCB) 38 2.1.1.7 Lithium Manganese Battery (LMB) 38 2.1.1.8 Lithium Phosphate Battery (LPB) 38 2.1.1.9 Lithium Titanate Battery (LTB) 38 2.1.2 Selection of the Battery 38 2.1.2.1 Nominal Voltage 39 2.1.2.2 Operating Time 39 2.1.2.3 Time for Recharge and Discharge 39 2.1.2.4 Cut Off Voltage 39 2.1.2.5 Physical Dimension 39 2.1.2.6 Environmental Conditions 40 2.1.2.7 Total Cost 40 2.2 Internet of Things 41 2.2.1 IoT – Battery Market 43 2.2.2 IoT - Battery Marketing Strategy 44 2.2.2.1 Based on the Type 44 2.2.2.2 Based on the Rechargeability 45 2.2.2.3 Based on the Region 45 2.2.2.4 Based on the Application 45 2.3 Power of IoT Devices in Battery Management System 45 2.3.1 Power Management 46 2.3.2 Energy Harvesting 47 2.3.3 Piezo-Mechanical Harvesting 48 2.3.4 Batteries Access to IoT Pioneers 49 2.3.5 Factors for Powering IoT Devices 49 2.3.5.1 Temperature 50 2.3.5.2 Environmental Factors 50 2.3.5.3 Power Budget 50 2.3.5.4 Form Factor 51 2.3.5.5 Status of the Battery 51 2.3.5.6 Shipment 52 2.4 Battery Life Estimation of IoT Devices 52 2.4.1 Factors Affecting the Battery Life of IoT Devices 53 2.4.2 Battery Life Calculator 53 2.4.3 Sleep Modes of IoT Processors 55 2.4.3.1 No Sleep 55 2.4.3.2 Modem Sleep 55 2.4.3.3 Light Sleep 55 2.4.3.4 Deep Sleep 56 2.4.4 Core Current Consumption 56 2.4.5 Peripheral Current Consumption 59 2.5 IoT Networking Technologies 59 2.5.1 Selection of an IoT Sensor 60 2.5.2 IoT - Battery Technologies 60 2.5.3 Battery Specifications 61 2.5.4 Battery Shelf Life 62 2.6 Conclusion 62 References 63 3 Smart Grid - Overview, Challenges and Security Issues 67 C. N. Vanitha, Malathy S. and S.A. Krishna 3.1 Introduction to the Chapter 68 3.2 Smart Grid and Its Uses 69 3.3 The Grid as it Stands-What’s at Risk? 72 3.3.1 Reliability 73 3.3.2 Efficiency 73 3.3.3 Security 74 3.3.4 National Economy 74 3.4 Creating the Platform for Smart Grid 75 3.4.1 Consider the ATM 76 3.5 Smart Grid in Power Plants 77 3.5.1 Distributed Power Flow Control 78 3.5.2 Power System Automation 79 3.5.3 IT Companies Disrupting the Energy Market 79 3.6 Google in Smart Grid 80 3.7 Smart Grid in Electric Cars 81 3.7.1 Vehicle-to-Grid 82 3.7.2 Challenges in Smart Grid Electric Cars 83 3.7.3 Toyota and Microsoft in Smart Electric Cars 84 3.8 Revisit the Risk 85 3.8.1 Reliability 85 3.8.2 Efficiency 86 3.8.3 Security 87 3.8.4 National Economy 88 3.9 Summary 88 References 88 4 IoT-Based Energy Management Strategies in Smart Grid 91 Seyed Ehsan Ahmadi and Sina Delpasand 4.1 Introduction 92 4.2 Application of IoT for Energy Management in Smart Grids 93 4.3 Energy Management System 94 4.3.1 Objectives of EMS 94 4.3.2 Control Frameworks of EMS 95 4.3.2.1 Centralized Approach 96 4.3.2.2 Decentralized Approach 97 4.3.2.3 Hierarchical Approach 97 4.4 Types of EMS at Smart Grid 98 4.4.1 Smart Home EMS 99 4.4.2 Smart Building EMS 100 4.5 Participants of EMS 103 4.5.1 Network Operator 104 4.5.2 Data and Communication Technologies 105 4.5.3 Aggregators 107 4.6 DER Scheduling 108 4.7 Important Factors for EMS Establishment 111 4.7.1 Uncertainty Modeling and Management Methods 111 4.7.2 Power Quality Management 112 4.7.3 DSM and DR Programs 114 4.8 Optimization Approaches for EMS 115 4.8.1 Mathematical Approaches 117 4.8.2 Heuristic Approaches 118 4.8.3 Metaheuristic Approaches 119 4.8.4 Other Programming Approaches 119 4.9 Conclusion 121 References 121 5 Integrated Architecture for IoTSG: Internet of Things (IoT) and Smart Grid (SG) 127 Malathy S., K. Sangeetha, C. N. Vanitha and Rajesh Kumar Dhanaraj 5.1 Introduction 128 5.1.1 Designing of IoT Architecture 129 5.1.2 IoT Characteristics 132 5.2 Introduction to Smart Grid 134 5.2.1 Smart Grid Technologies (SGT) 136 5.3 Integrated Architecture of IoT and Smart Grid 138 5.3.1 Safety Concerns 140 5.3.2 Security Issues 142 5.4 Smart Grid Security Services Based on IoT 143 References 154 6 Exploration of Assorted Modernizations in Forecasting Renewable Energy Using Low Power Wireless Technologies for IoTSG 157 Logeswaran K., Suresh P., Ponselvakumar A.P., Savitha S., Sentamilselvan K. and Adhithyaa N. 6.1 Introduction to the Chapter 158 6.1.1 Fossil Fuels and Conventional Grid 158 6.1.2 Renewable Energy and Smart Grid 160 6.2 Intangible Architecture of Smart Grid (SG) 161 6.3 Internet of Things (IoT) 164 6.4 Renewable Energy Source (RES)- Key Technology for SG 167 6.4.1 Renewable Energy: Basic Concepts and Readiness 167 6.4.2 Natural Sources of Renewable Energy 169 6.4.3 Major Issues in Following RES to SG 173 6.4.4 Integration of RES with SG 176 6.4.5 SG Renewable Energy Management Facilitated by IoT 177 6.4.6 Case Studies on Smart Grid: Renewable Energy Perception 180 6.5 Low Power Wireless Technologies for IoTSG 181 6.5.1 Role of IoT in SG 181 6.5.2 Innovations in Low Power Wireless Technologies 182 6.5.3 Wireless Communication Technologies for IoTSG 183 6.5.4 Case Studies on Low Power Wireless Technologies Used in IoTSG 186 6.6 Conclusion 188 References 188 7 Effective Load Balance in IOTSG with Various Machine Learning Techniques 193 Thenmozhi K., Pyingkodi M. and Kanimozhi K. I. Introduction 194 II. IoT in Big Data 195 III. IoT in Machine Learning 197 IV. Machine Learning Methods in IoT 199 V. IoT with SG 200 VI. Deep Learning with IoT 201 VII. Challenges in IoT for SG 202 VIII. IoT Applications for SG 202 IX. Application of IoT in Various Domain 204 X. Conclusion 205 References 206 8 Fault and Delay Tolerant IoT Smart Grid 207 K. Sangeetha and P. Vishnu Raja 8.1 Introduction 207 8.1.1 The Structures of the Intelligent Network 209 8.1.1.1 Operational Competence 209 8.1.1.2 Energy Efficiency 209 8.1.1.3 Flexibility in Network Topology 210 8.1.1.4 Reliability 210 8.1.2 Need for Smart Grid 210 8.1.3 Motivation for Enabling Delay Tolerant IoT 211 8.1.4 IoT-Enabled Smart Grid 211 8.2 Architecture 212 8.3 Opportunities and Challenges in Delay Tolerant Network for the Internet of Things 215 8.3.1 Design Goals 215 8.4 Energy Efficient IoT Enabled Smart Grid 219 8.5 Security in DTN IoT Smart Grid 220 8.5.1 Safety Problems 220 8.5.2 Safety Works for the Internet of Things-Based Intelligent Network 221 8.5.3 Security Standards for the Smart Grid 222 8.5.3.1 The Design Offered by NIST 222 8.5.3.2 The Design Planned by IEEE 222 8.6 Applications of DTN IoT Smart Grid 224 8.6.1 Household Energy Management in Smart Grids 224 8.6.2 Data Organization System for Rechargeable Vehicles 224 8.6.3 Advanced Metering Infrastructure (AMI) 225 8.6.4 Energy Organization 226 8.6.5 Transmission Tower Protection 226 8.6.6 Online Monitoring of Power Broadcast Lines 227 8.7 Conclusion 227 References 228 9 Significance of Block Chain in IoTSG - A Prominent and Reliable Solution 235 S. Vinothkumar, S. Varadhaganapathy, R. Shanthakumari and M. Ramalingam 9.1 Introduction 236 9.2 Trustful Difficulties with Monetary Communications for IoT Forum 239 9.3 Privacy in Blockchain Related Work 242 9.4 Initial Preparations 244 9.4.1 Blockchain Overview 244 9.4.2 k-Anonymity 246 9.4.2.1 Degree of Anonymity 246 9.4.2.2 Data Forfeiture 247 9.5 In the IoT Power and Service Markets, Reliable Transactions and Billing 248 9.5.1 Connector or Bridge 250 9.5.2 Group of Credit-Sharing 251 9.5.3 Local Block 251 9.6 Potential Applications and Use Cases 253 9.6.1 Utilities and Energy 253 9.6.2 Charging of Electric Vehicles 253 9.6.3 Credit Transfer 254 9.7 Proposed Work Execution 254 9.7.1 Creating the Group of Energy Sharing 255 9.7.2 Handling of Transaction 255 9.8 Investigation of Secrecy and Trustworthy 259 9.8.1 Trustworthy 259 9.8.2 Privacy-Protection 260 9.8.2.1 Degree of Confidentiality 261 9.8.2.2 Data Forfeiture 263 9.8.3 Evaluation of Results 265 9.9 Conclusion 267 References 267 10 IoTSG in Maintenance Management 273 T.C. Kalaiselvi and C.N. Vanitha 10.1 Introduction to the Chapter 274 10.2 IoT in Smart Grid 276 10.2.1 Uses and Facilities in SG 278 10.2.2 Architectures in SG 280 10.3 IoT in the Generation Level, Transmission Level, Distribution Level 288 10.4 Challenges and Future Research Directions in SG 295 10.5 Components for Predictive Management 296 10.6 Data Management and Infrastructure of IoT for Predictive Management 298 10.6.1 PHM Algorithms for Predictive Management 303 10.6.2 Decision Making with Predictive Management 305 10.7 Research Challenges in the Maintenance of Internet of Things 310 10.8 Summary 315 References 315 11 Intelligent Home Appliance Energy Monitoring with IoT 319 S. Tamilselvan, D. Deepa, C. Poongodi, P. Thangavel and Sarumathi Murali 11.1 Introduction 320 11.2 Survey on Energy Monitoring 320 11.3 Internet of Things System Architecture 322 11.4 Proposed Energy Monitoring System with IoT 323 11.5 Energy Management Structure (Proposed) 324 11.6 Implementation of the System 325 11.6.1 Implementation of IoT Board 325 11.6.2 Software Implementation 325 11.7 Smart Home Automation Forecasts 326 11.7.1 Energy Measurement 326 11.7.2 Periodically Updating the Status in the Cloud 327 11.7.3 Irregularity Detection 328 11.7.4 Finding the Problems with the Device 328 11.7.5 Indicating the House Owner About the Issues 329 11.7.6 Suggestions for Remedial Actions 329 11.8 Energy Reduction Based on IoT 330 11.8.1 House Energy Consumption (HEC) - Cost Saving 330 11.9 Performance Evaluation 330 11.9.1 Data Analytics and Visualization 330 11.10 Benefits for Different User Categories 332 11.11 Results and Discussion with Benefits of User Categories 332 11.12 Summary 334 References 334 12 Applications of IoTSG in Smart Industrial Monitoring Environments 339 Mohanasundaram T., Vetrivel S.C., and Krishnamoorthy V. 12.1 Introduction 340 12.2 Energy Management 342 12.3 Role of IoT and Smart Grid in the Banking Industry 345 12.3.1 Application of IoT in the Banking Sector 346 12.3.1.1 Customer Relationship Management (crm) 347 12.3.1.2 Loan Sanctions 348 12.3.1.3 Customer Service 348 12.3.1.4 Leasing Finance Automation 348 12.3.1.5 Capacity Management 348 12.3.2 Application of Smart Grid in the Banking Sector 349 12.4 Role of IoT and Smart Grid in the Automobile Industry 349 12.4.1 Application of IoT in the Automobile Industry 350 12.4.1.1 What Exactly is the Internet of Things (IoT) Mean to the Automobile Sector? 350 12.4.1.2 Transportation and Logistics 351 12.4.1.3 Connected Cars 351 12.4.1.4 Fleet Management 352 12.4.2 Application of Smart Grid (SG) in the Automobile Industry 354 12.4.2.1 Smart Grid Can Change the Face of the Automobile Industry 355 12.4.2.2 Smart Grid and Energy Efficient Mobility System 357 12.5 Role of IoT and SG in Healthcare Industry 357 12.5.1 Applications of IoT in Healthcare Sector 358 12.5.2 Application of Smart Grid (SG) in Health Care Sector 360 12.6 IoT and Smart Grid in Energy Management - A Way Forward 360 12.7 Conclusion 362 References 363 13 Solar Energy Forecasting for Devices in IoT Smart Grid 365 K. Tamil Selvi, S. Mohana Saranya and R. Thamilselvan 13.1 Introduction 366 13.2 Role of IoT in Smart Grid 368 13.3 Clear Sky Models 370 13.3.1 REST2 Model 370 13.3.2 Kasten Model 370 13.3.3 Polynomial Fit 371 13.4 Persistence Forecasts 372 13.5 Regressive Methods 373 13.5.1 Auto-Regressive Model 373 13.5.2 Moving Average Model 373 13.5.3 Mixed Auto Regressive Moving Average Model 373 13.5.4 Mixed Auto Regressive Moving Average Model with Exogeneous Variables 374 13.6 Non-Linear Stationary Models 374 13.7 Linear Non-Stationary Models 376 13.7.1 Auto Regressive Integrated Moving Average Models 376 13.7.2 Auto-Regressive Integrated Moving Average Model with Exogenous Variables 376 13.8 Artificial Intelligence Techniques 377 13.8.1 Artificial Neural Network 377 13.8.2 Multi-Layer Perceptron 377 13.8.3 Deep Learning Model 380 13.8.3.1 Stacked Auto-Encoder 381 13.8.3.2 Deep Belief Network 382 13.8.3.3 Deep Recurrent Neural Network 383 13.8.3.4 Deep Convolutional Neural Network 384 13.8.3.5 Stacked Extreme Learning Machine 386 13.8.3.6 Generative Adversarial Network 386 13.8.3.7 Comparison of Deep Learning Models for Solar Energy Forecast 387 13.9 Remote Sensing Model 389 13.10 Hybrid Models 389 13.11 Performance Metrics for Forecasting Techniques 390 13.12 Conclusion 391 References 392 14 Utilization of Wireless Technologies in IoTSG for Energy Monitoring in Smart Devices 395 S. Suresh Kumar, A. Prakash, O. Vignesh and M. Yogesh Iggalore 14.1 Introduction to Internet of Things 396 14.2 IoT Working Principle 397 14.3 Benefits of IoT 398 14.4 IoT Applications 399 14.5 Introduction to Smart Home 399 14.5.1 Benefits of Smart Homes 400 14.6 Problem Statement 401 14.6.1 Methodology 401 14.7 Introduction to Wireless Communication 402 14.7.1 Merits of Wireless 402 14.8 How Modbus Communication Works 403 14.8.1 Rules for Modbus Addressing 404 14.8.2 Modbus Framework Description 404 14.8.2.1 Function Code 404 14.8.2.2 Cyclic Redundancy Check 405 14.8.2.3 Data Storage in Modbus 405 14.9 MQTT Protocol 406 14.9.1 Pub/Sub Architecture 406 14.9.2 MQTT Client Broker Communication 407 14.9.3 MQTT Standard Header Packet 407 14.9.3.1 Fixed Header 408 14.10 System Architecture 408 14.11 IoT Based Electronic Energy Meter-eNtroL 410 14.11.1 Components Used in eNtroL 411 14.11.2 PZEM-004t Energy Meter 411 14.11.3 Wi-Fi Module 412 14.11.4 Switching Device 413 14.11.5 230V AC to 5V Dc Converter 414 14.11.6 LM1117 IC- 5V to 3.3V Converter 414 14.12 AC Control System for Home Appliances – Switch2Smart 415 14.12.1 Opto-Coupler- H11AA1 IC 415 14.12.2 TRIAC Driven Opto Isolator- MOC3021M IC 416 14.12.3 Triac, Bt136-600 Ic 416 14.13 Scheduling Home Appliance Using Timer – Switch Binary 417 14.14 Hardware Design 418 14.14.1 Kaicad Overview 418 14.14.2 PCB Designing Using Kaicad 418 14.14.2.1 Designing of eNtroL Board Using Kaicad 418 14.14.2.2 Designing of Switch2smart Board Using Kaicad 420 14.14.2.3 Designing of Switch Binary Board Using Kaicad 421 14.15 Implementation of the Proposed System 422 14.16 Testing and Results 424 14.16.1 Testing of eNtrol 425 14.16.2 Testing of Switch2Smart 427 14.16.3 Testing of SwitchBinary 428 14.17 Conclusion 429 References 429 15 Smart Grid IoT: An Intelligent Energy Management in Emerging Smart Cities 431 R. S. Shudapreyaa, G. K. Kamalam, P. Suresh and K. Sentamilselvan 15.1 Overview of Smart Grid and IoT 432 15.1.1 Smart Grid 432 15.1.2 Smart Grid Data Properties 434 15.1.3 Operations on Smart Grid Data 435 15.2 IoT Application in Smart Grid Technologies 436 15.2.1 Power Transmission Line - Online Monitoring 436 15.2.2 Smart Patrol 437 15.2.3 Smart Home Service 437 15.2.4 Information System for Electric Vehicle 438 15.3 Technical Challenges of Smart Grid 438 15.3.1 Inadequacies in Grid Infrastructure 438 15.3.2 Cyber Security 439 15.3.3 Storage Concerns 439 15.3.4 Data Management 440 15.3.5 Communication Issues 440 15.3.6 Stability Concerns 440 15.3.7 Energy Management and Electric Vehicle 440 15.4 Energy Efficient Solutions for Smart Cities 441 15.4.1 Lightweight Protocols 441 15.4.2 Scheduling Optimization 441 15.4.3 Energy Consumption 441 15.4.4 Cloud Based Approach 441 15.4.5 Low Power Transceivers 442 15.4.6 Cognitive Management Framework 442 15.5 Energy Conservation Based Algorithms 442 15.5.1 Genetic Algorithm (GA) 442 15.5.2 BFO Algorithm 444 15.5.3 BPSO Algorithm 445 15.5.4 WDO Algorithm 447 15.5.5 GWDO Algorithm 447 15.5.6 WBFA Algorithm 450 15.6 Conclusion 451 References 451 Index 455
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