R. Rajasekar Professor and Head of the Department of Mechanical Engineering, Kongu Engineering College (An Autonomous Institution under Anna University), Tamilnadu, India. He obtained his PhD from the Indian Institute of Technology, Kharagpur, and specializes in material science and engineering, renewable energy, surface coating on solar cells, and tribological performance of carbide inserts. He has published more than 100 research articles in reputed international journals as well as more than 3o book chapters.  

C. Moganapriya is an associate professor in the Department of Mechanical Engineering, Kongu Engineering College (An Autonomous Institution under Anna University), Tamilnadu, India. She completed Ph D in 2019 and her current research area includes surface engineering of solar cells for performance enhancement of power conversion efficiency and tribological performance of cutting tool insert by adopting several hard coating materials. She has published 13 research articles and 15 book chapters with international publishers.

P. Sathish Kumar, PhD is an assistant professor in the Department of Manufacturing, Institute of Mechanical Engineering, Saveetha School of Engineering, SIMATS University, Chennai, Tamilnadu, India. He has published more than 6o research articles and 35 book chapters with international journals and publishers. His main research areas are in tribological studies of mining bits, thin film coating, natural fibee composites and renewable energy. 

M. Harikrishna Kumar, PhD is a lecturer in Sri Krishna Polytechnic College, Coimbatore, India. He has 12 years of teaching and 2 years of industry experience. He served as an assistant professor in Kongu Engineering College, Perundurai, India for 9 years.

Preface xvii

1 Evolution of Internet of Things (IoT): Past, Present and Future for Manufacturing Systems 1
Vaishnavi Vadivelu, Moganapriya Chinnasamy, Manivannan Rajendran, Hari Chandrasekaran and Rajasekar Rathanasamy

1.1 Introduction 2

1.2 IoT Revolution 2

1.3 IoT 4

1.4 Fundamental Technologies 5

1.4.1 RFID and NFC 5

1.4.2 Wsn 6

1.4.3 Data Storage and Analytics (DSA) 6

1.5 IoT Architecture 6

1.6 Cloud Computing (CC) and IoT 7

1.6.1 Service of cc 8

1.6.2 Integration of IoT With cc 10

1.7 Edge Computing (EC) and IoT 10

1.7.1 EC with IoT Architecture 11

1.8 Applications of IoT 12

1.8.1 Smart Mobility 12

1.8.2 Smart Grid 14

1.8.3 Smart Home System 14

1.8.4 Public Safety and Environment Monitoring 15

1.8.5 Smart Healthcare Systems 15

1.8.6 Smart Agriculture System 16

1.9 Industry 4.0 Integrated With IoT Architecture for Incorporation of Designing and Enhanced Production Systems 17

1.9.1 Five-Stage Process of IoT for Design and Manufacturing System 19

1.9.2 IoT Architecture for Advanced Manufacturing Technologies 21

1.9.3 Architecture Development 22

1.10 Current Issues and Challenges in IoT 24

1.10.1 Scalability 25

1.10.2 Issue of Trust 25

1.10.3 Service Availability 26

1.10.4 Security Challenges 26

1.10.5 Mobility Issues 27

1.10.6 Architecture for IoT 27

1.11 Conclusion 28

References 29

2 Fourth Industrial Revolution: Industry 4.0 41
Maheswari Rajamanickam, Elizabeth Nirmala John Gerard Royan, Gowtham Ramaswamy, Manivannan Rajendran and Vaishnavi Vadivelu

2.1 Introduction 42

2.1.1 Global Level Adaption 42

2.2 Evolution of Industry 44

2.2.1 Industry 1.0 44

2.2.2 Industry 2.0 44

2.2.3 Industry 3.0 44

2.2.4 Industry 4.0 (or) I4. 0 44

2.3 Basic IoT Concepts and the Term Glossary 45

2.4 Industrial Revolution 47

2.4.1 I4.0 Core Idea 47

2.4.2 Origin of I4.0 Concept 48

2.5 Industry 49

2.5.1 Manufacturing Phases 49

2.5.2 Existing Process Planning vs. I4. 0 50

2.5.3 Software for Product Planning—A Link Between Smart Products and the Main System ERP 52

2.6 Industry Production System 4.0 (Smart Factory) 56

2.6.1 IT Support 58

2.7 I4.0 in Functional Field 60

2.7.1 I4.0 Logistics 60

2.7.2 Resource Planning 60

2.7.3 Systems for Warehouse Management 61

2.7.4 Transportation Management Systems 61

2.7.5 Transportation Systems with Intelligence 63

2.7.6 Information Security 64

2.8 Existing Technology in I4. 0 65

2.8.1 Applications of I4.0 in Existing Industries 65

2.8.2 Additive Manufacturing (AM) 66

2.8.3 Intelligent Machines 66

2.8.4 Robots that are Self-Aware 66

2.8.5 Materials that are Smart 67

2.8.6 IoT 67

2.8.7 The Internet of Things in Industry (IIoT) 67

2.8.8 Sensors that are Smart 67

2.8.9 System Using a Smart Programmable Logic Controller (PLC) 67

2.8.10 Software 68

2.8.11 Augmented Reality (AR)/Virtual Reality (VR) 68

2.8.12 Gateway for the Internet of Things 68

2.8.13 Cloud 68

2.8.14 Applications of Additive Manufacturing in I4. 0 68

2.8.15 Artificial Intelligence (AI) 69

2.9 Applications in Current Industries 69

2.9.1 I4.0 in Logistics 69

2.9.2 I4.0 in Manufacturing Operation 70

2.10 Future Scope of Research 73

2.10.1 Theoretical Framework of I4. 0 73

2.11 Discussion and Implications 75

2.11.1 Hosting: Microsoft 75

2.11.2 Platform for the Internet of Things (IoT): Microsoft, GE, PTC, and Siemens 76

2.11.3 A Systematic Computational Analysis 76

2.11.4 Festo Proximity Sensor 77

2.11.5 Connectivity Hardware: HMS 77

2.11.6 IT Security: Claroty 77

2.11.7 Accenture Is a Systems Integrator 77

2.11.8 Additive Manufacturing: General Electric 78

2.11.9 Augmented and Virtual Reality: Upskill 78

2.11.10 ABB Collaborative Robots 78

2.11.11 Connected Vision System: Cognex 78

2.11.12 Drones/UAVs: PINC 79

2.11.13 Self-Driving in Vehicles: Clear Path Robotics 79

2.12 Conclusion 79

References 80

3 Interaction of Internet of Things and Sensors for Machining 85
Manivannan Rajendran, Kamesh Nagarajan, Vaishnavi Vadivelu, Harikrishna Kumar Mohankumar and Sathish Kumar Palaniappan

3.1 Introduction 86

3.2 Various Sensors Involved in Machining Process 88

3.2.1 Direct Method Sensors 89

3.2.2 Indirect Method Sensors 89

3.2.3 Dynamometer 90

3.2.4 Accelerometer 91

3.2.5 Acoustic Emission Sensor 93

3.2.6 Current Sensors 94

3.3 Other Sensors 94

3.3.1 Temperature Sensors 94

3.3.2 Optical Sensors 95

3.4 Interaction of Sensors During Machining Operation 96

3.4.1 Milling Machining 96

3.4.2 Turning Machining 97

3.4.3 Drilling Machining Operation 98

3.5 Sensor Fusion Technique 99

3.6 Interaction of Internet of Things 100

3.6.1 Identification 100

3.6.2 Sensing 101

3.6.3 Communication 101

3.6.4 Computation 101

3.6.5 Services 101

3.6.6 Semantics 101

3.7 IoT Technologies in Manufacturing Process 102

3.7.1 IoT Challenges 102

3.7.2 IoT-Based Energy Monitoring System 102

3.8 Industrial Application 104

3.8.1 Integrated Structure 104

3.8.2 Monitoring the System Related to Service Based on Internet of Things 106

3.9 Decision Making Methods 107

3.9.1 Artificial Neural Network 107

3.9.2 Fuzzy Inference System 108

3.9.3 Support Vector Mechanism 108

3.9.4 Decision Trees and Random Forest 109

3.9.5 Convolutional Neural Network 109

3.10 Conclusion 111

References 111

4 Application of Internet of Things (IoT) in the Automotive Industry 115
Solomon Jenoris Muthiya, Shridhar Anaimuthu, Joshuva Arockia Dhanraj, Nandakumar Selvaraju, Gutha Manikanta and C. Dineshkumar

4.1 Introduction 116

4.2 Need For IoT in Automobile Field 118

4.3 Fault Diagnosis in Automobile 119

4.4 Automobile Security and Surveillance System in IoT-Based 123

4.5 A Vehicle Communications 125

4.6 The Smart Vehicle 126

4.7 Connected Vehicles 128

4.7.1 Vehicle-to-Vehicle (V2V) Communications 130

4.7.2 Vehicle-to-Infrastructure (V2I) Communications 131

4.7.3 Vehicle-to-Pedestrian (V2P) Communications 132

4.7.4 Vehicle to Network (V2N) Communication 133

4.7.5 Vehicle to Cloud (V2C) Communication 134

4.7.6 Vehicle to Device (V2D) Communication 134

4.7.7 Vehicle to Grid (V2G) Communications 135

4.8 Conclusion 135

References 136

5 IoT for Food and Beverage Manufacturing 141
Manju Sri Anbupalani, Gobinath Velu Kaliyannan and Santhosh Sivaraj

5.1 Introduction 142

5.2 The Influence of IoT in a Food Industry 143

5.2.1 Management 143

5.2.2 Workers 143

5.2.3 Data 143

5.2.4 It 143

5.3 A Brief Review of IoT’s Involvement in the Food Industry 144

5.4 Challenges to the Food Industry and Role of IoT 144

5.4.1 Handling and Sorting Complex Data 144

5.4.2 A Retiring Skilled Workforce 145

5.4.3 Alternatives for Supply Chain Management 145

5.4.4 Implementation of IoT in Food and Beverage Manufacturing 145

5.4.5 Pilot 145

5.4.6 Plan 146

5.4.7 Proliferate 146

5.5 Applications of IoT in a Food Industry 146

5.5.1 IoT for Handling of Raw Material and Inventory Control 146

5.5.2 Factory Operations and Machine Conditions Using IoT 146

5.5.3 Quality Control With the IoT 147

5.5.4 IoT for Safety 147

5.5.5 The Internet of Things and Sustainability 147

5.5.6 IoT for Product Delivery and Packaging 147

5.5.7 IoT for Vehicle Optimization 147

5.5.8 IoT-Based Water Monitoring Architecture in the Food and Beverage Industry 148

5.6 A FW Tracking System Methodology Based on IoT 150

5.7 Designing an IoT-Based Digital FW Monitoring and Tracking System 150

5.8 The Internet of Things (IoT) Architecture for a Digitized Food Waste System 152

5.9 Hardware Design: Intelligent Scale 152

5.10 Software Design 153

References 157

6 Opportunities: Machine Learning for Industrial IoT Applications 159
Poongodi C., Sayeekumar M., Meenakshi C. and Hari Prasath K.

6.1 Introduction 160

6.2 I-IoT Applications 163

6.3 Machine Learning Algorithms for Industrial IoT 170

6.3.1 Supervised Learning 171

6.3.2 Semisupervised Learning 173

6.3.3 Unsupervised Learning 173

6.3.4 Reinforcement Learning 175

6.3.5 The Most Common and Popular Machine Learning Algorithms 176

6.4 I-IoT Data Analytics 177

6.4.1 Tools for IoT Analytics 177

6.4.2 Choosing the Right IoT Data Analytics Platforms 184

6.5 Conclusion 185

References 186

7 Role of IoT in Industry Predictive Maintenance 191
Gobinath Velu Kaliyannan, Manju Sri Anbupalani, Suganeswaran Kandasamy, Santhosh Sivaraj and Raja Gunasekaran

7.1 Introduction 192

7.2 Predictive Maintenance 194

7.3 IPdM Systems Framework and Few Key Methodologies 196

7.3.1 Detection and Collection of Data 196

7.3.2 Initial Processing of Collected Data 196

7.3.3 Modeling as Per Requirement 197

7.3.4 Influential Parameters 198

7.3.5 Identification of Best Working Path 198

7.3.6 Modifying Output with Respect Sensed Input 198

7.4 Economics of PdM 198

7.5 PdM for Production and Product 200

7.6 Implementation of IPdM 202

7.6.1 Manufacturing with Zero Defects 202

7.6.2 Sense of the Windsene INDSENSE 202

7.7 Case Studies 202

7.7.1 Area 1—Heavy Ash Evacuation 203

7.7.2 Area 2—Seawater Pumps 203

7.7.3 Evaporators 204

7.7.4 System Deployment Considerations in General 205

7.8 Automotive Industry—Integrated IoT 205

7.8.1 Navigation Aspect 205

7.8.2 Continual Working of Toll Booth 206

7.8.3 Theft Security System 206

7.8.4 Black Box–Enabled IoT 206

7.8.5 Regularizing Motion of Emergency Vehicle 207

7.8.6 Pollution Monitoring System 207

7.8.7 Timely Assessment of Driver’s Condition 207

7.8.8 Vehicle Performance Monitoring 207

7.9 Conclusion 208

References 208

8 Role of IoT in Product Development 215
Bhuvanesh Kumar M., Balaji N. S., Senthil S. M. and Sathiya P.

8.1 Introduction 216

8.1.1 Industry 4.0 217

8.2 Need to Understand the Product Architecture 220

8.3 Product Development Process 222

8.3.1 Criteria to Classify the New Products 223

8.3.2 Product Configuration 224

8.3.3 Challenges in Product Development while Developing IoT Products (Data-Driven Product Development) 225

8.3.4 Role of IoT in Product Development for Industrial Applications 226

8.3.5 Impacts and Future Perspectives of IoT in Product Development 229

8.4 Conclusion 231

References 232

9 Benefits of IoT in Automated Systems 235
Adithya K. and Girimurugan R.

9.1 Introduction 235

9.2 Benefits of Automation 236

9.2.1 Improved Productivity 236

9.2.2 Efficient Operation Management 236

9.2.3 Better Use of Resources 237

9.2.4 Cost-Effective Operation 237

9.2.5 Improved Work Safety 237

9.2.6 Software Bots 237

9.2.7 Enhanced Public Sector Operations 237

9.2.8 Healthcare Benefits 238

9.3 Smart City Automation 238

9.3.1 Smart Agriculture 240

9.3.2 Smart City Services 240

9.3.3 Smart Energy 240

9.3.4 Smart Health 241

9.3.5 Smart Home 241

9.3.6 Smart Industry 242

9.3.7 Smart Infrastructure 242

9.3.8 Smart Transport 242

9.4 Smart Home Automation 243

9.5 Automation in Manufacturing 247

9.5.1 IoT Manufacturing Use Cases 249

9.5.2 Foundation for IoT in Manufacturing 251

9.6 Healthcare Automation 253

9.6.1 IoT in Healthcare Applications 254

9.6.2 Architecture for IoT-Healthcare Applications 257

9.6.3 Challenges and Solutions 258

9.7 Industrial Automation 259

9.7.1 IoT in Industrial Automation 260

9.7.2 The Essentials of an Industrial IoT Solution 260

9.7.3 Practical Industrial IoT Examples for Daily Use 261

9.8 Automation in Air Pollution Monitoring 265

9.8.1 Methodology 266

9.8.2 Working Principle 267

9.8.3 Results 267

9.9 Irrigation Automation 268

References 269

10 Integration of IoT in Energy Management 271
Ganesh Angappan, Santhosh Sivaraj, Premkumar Bhuvaneshwaran, Mugilan Thanigachalam, Sarath Sekar and Rajasekar Rathanasamy

10.1 Introduction 272

10.2 Energy Management Integration with IoT in Industry 4.0 274

10.3 IoT in Energy Sector 276

10.3.1 Energy Generation 276

10.3.2 Smart Cities 277

10.3.3 Smart Grid 277

10.3.4 Smart Buildings 278

10.3.5 IoT in the Energy Industry 279

10.3.6 Intelligent Transportation 280

10.4 Provocations in the IoT Applications 281

10.4.1 Energy Consumption 281

10.4.2 Subsystems and IoT Integration 282

10.5 Energy Generation 284

10.5.1 Conversion of Mechanical Energy 285

10.5.2 Aeroelastic Energy Harvesting 290

10.5.3 Solar Energy Harvesting 292

10.5.4 Sound Energy Harvesting 292

10.5.5 Wind Energy Harvesting 292

10.5.6 Radiofrequency Energy Harvesting 293

10.5.7 Thermal Energy 293

10.6 Conclusion 294

References 294

11 Role of IoT in the Renewable Energy Sector 305
Veerakumar Chinnasamy and Honghyun Cho

11.1 Introduction 305

11.2 Internet of Things (IoT) 306

11.3 IoT in the Renewable Energy Sector 307

11.3.1 Automation of Energy Generation 307

11.3.2 Smart Grids 309

11.3.3 IoT Increases the Renewable Energy Use 312

11.3.4 Consumer Contribution 312

11.3.5 Balancing Supply and Demand 313

11.3.6 Smart Buildings 313

11.3.7 Smart Cities 314

11.3.8 Cost-Effectiveness 314

11.4 Data Analytics 314

11.4.1 Data Forecasting 314

11.4.2 Safety and Reliability 315

11.5 Conclusion 315

References 315

Index 317

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