Internet of Things in Business Transformation Developing an Engineering and Business Strategy for Industry 5.0

by Gandhi, Parul; Bhatia, Surbhi; Kumar, Abhishek; Alojail, Mohammad Ali; Rathore, Pramod Singh

• ISBN13: 9781119711124
• ISBN10: 1119711126
• Edition: 1st
• Format: Hardcover
• Copyright: 2021-02-03
• Publisher: Wiley-Scrivener

Summary

The objective of this book is to teach what IoT is, how it works, and how it can be successfully utilized in business. This book helps to develop and implement a powerful IoT strategy for business transformation as well as project execution. Digital change, business creation/change and upgrades in the ways and manners in which we work, live, and engage with our clients and customers, are all enveloped by the Internet of Things which is now named "Industry 5.0" or "Industrial Internet of Things." The sheer number of IoT(a billion+), demonstrates the advent of an advanced business society led by sustainable robotics and business intelligence. This book will be an indispensable asset in helping businesses to understand the new technology and thrive.

Author Biography

Parul Gandhi obtained her PhD in Computer Science and Software Engineering from Guru Jambheshwar University, Hisar, India. She is an associate professor at the Manav Rachna International Institute of Research and Studies (MRIIRS), Faridabad where she also handles the PhD program. She has published more than 30 research papers in reputed journals and conferences. Her research interests include software quality, soft computing, software metrics and component-based software development, data mining, IOT.

Surbhi Bhatia obtained her PhD in Computer Science and Engineering from Banasthali Vidypaith, India. She is an assistant professor in the Department of Information Systems, College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia. She has published seven patents with the Government of India and more than 25 papers in reputed journals and conferences in high indexing databases. She is an active researcher in the field of data mining, machine learning, deep learning and information retrieval.

Abhishek Kumar obtained his PhD in Computer Science from the University of Madras. He is an assistant professor in the Department of Computer Science & Engineering, Chitkara University Institute of Engineering and Technology, India. He has more than 60 publications in peer-reviewed journals and has edited more than 15 books. His research areas include AI, image processing, computer vision, data mining, machine learning.

Mohammad Alojail obtained his PhD in Information systems from RMIT University, Australia. He is the Chairman of Information System Department, College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia. He has considerable experience in the field of information systems and has delivered many presentations on leadership and management as well as successfully leading and managing teams to deliver large scale industrial projects. Dr. Alojail has written many scholarly papers in the field of IS and IT outsourcing.

Pramod Singh Rathore is pursuing his Doctorate in Computer Science & Engineering from Bundelkhand University, India. He has been working as an assistant professor at the Computer Science & Engineering Department at Aryabhatt Engineering College and Research Centre, Rajasthan. He has more than 45 publications in peer-reviewed journals.

Table of Contents

Preface xiii

1 Applications of IIoT-Based Systems in Detection Leakage in Pipeline Custody Transfer of Hydrocarbon Products 1
Pragyadiya Das

1.1 Introduction 1

1.2 Industrial Internet of Things 3

1.3 Pipeline Leaks 3

1.3.1 Various Techniques used to Detect Pipeline Leak 4

1.3.2 Use of IIoT to Detect Pipeline Leak 7

1.3.3 Use of Machine Learning Algorithms to Detect Pipeline Leak 9

1.3.4 Design and Analysis of Ensemble Learning-Based Approach for Pipeline Leak Detection 10

1.4 Conclusion 11

References 11

2 Heart Rate Monitoring System 15
Ramapriya Ranganath, Parag Jain, Akarash Kolekar, Sneha Baliga, A. Srinivas and M. Rajasekar

2.1 Introduction 16

2.2 Project Objectives 17

2.3 System Architecture 18

2.4 Conclusion 25

References 25

3 An Efficient Clustering Technique for Wireless Body Area Networks Based on Dragonfly Optimization 27
Bilal Mehmood and Farhan Aadil

3.1 Introduction 28

3.2 Literature Review 29

3.3 Clustering Technique 31

3.3.1 Evolutionary Algorithms 32

3.4 Implementation Steps 34

3.4.1 Dragonfly Algorithm 35

3.5 Result and Simulations 37

3.6 Conclusion 41

References 41

4 Transformational Technology for Business Transformation in the New Era 43
Md Shamsul Haque Ansari and Monica Mehrotra

4.1 Introduction 43

4.1.1 Business Transformation 45

4.2 Digital Transformation and its Big Trend 46

4.2.1 Digital Transformation 46

4.2.2 How Important is Digital Transformation? 46

4.2.3 Digital Transformation Examples 48

4.2.4 Importance of Digital Transformation 50

4.2.5 Digital Transformation vs Business Transformation 50

4.2.6 What Does Digital Transformation Look Like? 50

4.3 Transformational Technology 51

4.3.1 Internet of Things 51

4.3.2 Robotic Process Automation 52

4.3.3 Automation and Artificial Intelligence 52

4.3.4 Blockchain 53

4.3.5 Cloud Computing 54

4.3.6 Smartphones and Mobile Apps 54

4.3.7 4G and 5G 55

4.3.8 Data Analytics 55

4.3.9 Social Media 55

4.4 How to Get “Digital Transformation” in a Right Way for Any Business 56

4.4.1 Look Beyond the Traditional Enterprise Firewall 56

4.4.2 Bring New Ideas From the Edge to the Core 57

4.4.3 Define the Role of the CIO in the Innovation Process 57

4.5 Relevance of IoT in Digital Transformation 58

4.6 Conclusion 59

References 59

5 Future of Artificial Intelligence: Will People be at More of an Advantage Than They Are Today? 61
Priyadarsini Patnaik and Ravi Prakash

5.1 Introduction 61

5.2 The State of Artificial Intelligence (AI) 63

5.3 How Do Customers Interact with AI Nowadays? 63

5.4 AI as Digital Assistants 63

5.5 AI and Privacy, Data Security 64

5.5.1 Artificial Intelligence and its Effect on Humans 64

5.5.2 Conclusion 67

References 67

6 Classifier for DDoS Attack Detection in Software Defined Networks 71
Gaganjot Kaur and Prinima Gupta

6.1 Introduction 72

6.2 Related Work 75

6.3 DDoS Attacks Overview 79

6.4 Types of DDoS Attacks 81

6.5 DDoS Detection Techniques in SDN 83

6.6 Detection Using ML Techniques 83

6.7 Proposed Work Using SVM Classifier 84

6.8 Data Set Used 85

6.9 Proposed Methodology 85

6.10 Existing & Proposed Results 86

6.11 Conclusion & Future Work 86

References 87

7 IoT-Based Optimized and Secured Ecosystem for Energy Internet: The State-of-the-Art 91
Shilpa Sambhi, Shikhar Sambhi and Vikas Singh Bhadoria

7.1 Introduction 92

7.2 Distinguishing Features Between Home Automation and Smart Home 95

7.3 Energy Generation Shift Towards Renewable Sources 99

7.4 Robust Energy Management with IoT Technology 100

7.5 Solution from IoT Technology for Secured Transactions 103

7.5.1 Category I: Centralized Approach 103

7.5.2 Category II: Decentralized Approach 103

7.5.2.1 Blockchain Technology 104

7.5.2.2 Software Defined Networking (SDN) 107

7.6 Role of IoT in Smart Grid 109

7.6.1 Power Generation 109

7.6.2 Power Transmission 111

7.6.3 Power Distribution 111

7.6.4 Consumer Consumption 112

7.7 Bottleneck Areas of Existing System 112

7.8 Fusion of Energy Internet with IoT and Blockchain 113

7.9 Challenges for Safe and Secured Ecosystem in Energy Internet 116

7.9.1 The Case of Smart Grids 117

7.9.2 The Case of Smart Cities 119

References 121

8 A Novel Framework for Intelligent Spaces 127
Deepali Kamthania

8.1 Introduction 127

8.2 Intelligent Space 128

8.2.1 Sensing 128

8.2.2 Multimodal Perception 129

8.2.3 Context-Based Data Interpretation 129

8.2.4 Narrative Engines 129

8.3 Product Identification 130

8.4 Position Measurements 131

8.5 Proposed Framework 134

8.6 Conclusions 136

References 136

9 Defense and Isolation in the Internet of Things 141
Ravi Kumar Sharma, Tejinder Pal Singh Brar and Parul Gandhi

9.1 Introduction 142

9.1.1 IoT Reference Model 143

9.1.2 IoT Security Threats 144

9.1.3 IoT Security Requirements 145

9.1.3.1 Scale 146

9.1.3.2 IP Protocol-Based IoT 146

9.1.3.3 Heterogeneous IoT 147

9.1.3.4 Lightweight Security 147

9.2 IoT Security Overview 149

9.2.1 IoT Protocols 149

9.2.2 Network and Transport Layer Challenges 152

9.2.3 IoT Gateways and Security 152

9.2.4 IoT Routing Attacks 153

9.2.5 Bootstrapping and Authentication 155

9.2.6 Authorization Mechanisms 156

9.2.6.1 Resource Owner 156

9.2.6.2 Resource Server (Service Provider, SP) 156

9.2.6.3 Client (Service Consumer, SC) 156

9.2.6.4 Authorization Server 157

9.2.7 IoT OAS 157

9.3 Security Frameworks for IoT 158

9.3.1 Light Weight Cryptography 158

9.3.1.1 Symmetric-Key LWC Algorithms 159

9.3.1.2 Asymmetric LWC Algorithms 160

9.3.1.3 Key Agreement, Distribution, and Bootstrapping 160

9.3.1.4 Security Bootstrapping 161

9.4 Privacy in IoT Networks 161

9.4.1 Secure Data Aggregation 162

9.4.2 Enigma 163

9.4.3 Zero-Knowledge Protocols 164

9.4.4 Privacy in Beacons 164

9.5 Summary and Conclusions 166

References 166

10 Realization of Business Intelligence using Machine Learning 169
Mamata Rath

10.1 Introduction 170

10.2 Business Intelligence and Machine Learning Technology 170

10.3 Literature Study 173

10.4 Business Analytics and Machine Learning 174

10.5 IoT in Machine Learning 177

10.6 Conclusion 180

References 181

11 Current Trends and Future Scope for the Internet of Things 185
Iram Abrar, Zahrah Ayub and Faheem Masoodi

11.1 Introduction 185

11.2 IoT in Healthcare 188

11.3 IoT in Agriculture 191

11.4 IoT in Industries 195

11.5 IoT-Based Smart Cities 198

11.6 IoT in Robotics 201

11.7 Conclusion and Future Scope 203

References 204

12 Challenges for Agile Autonomous Team in Business Organization 211
Gurmeet Kaur, Jyoti Pruthi and Rachna Soni

12.1 Introduction 212

12.2 Literature Review 212

12.3 Types of Autonomy 214

12.3.1 Outside/External Autonomy 214

12.3.2 Interior/Internal Autonomy 215

12.3.3 Singular Autonomy 215

12.3.4 Consistent Learning and Improvement Ensures Individual and Internal Autonomy 215

12.4 Challenges for Autonomous Team 216

12.4.1 Planning 216

12.4.1.1 Planning Associate Teams 216

12.4.1.2 Closed-Loop Communication 217

12.4.2 Conflict 217

12.4.2.1 Inter-Personal Conflict 217

12.4.2.2 Intra-Group Struggle 218

12.4.2.3 Heightened Inter-Personal Conflict 218

12.4.3 Trust 219

12.4.4 Standards/Norms 220

12.4.5 One to One/Injunctive Norms 221

12.4.6 Descriptive Norms 222

12.4.7 Concurrent Norms 222

12.4.8 Mental Safety 223

12.4.9 Changing Norms 223

12.5 Suggestions for Training 224

12.5.1 Locate the Correct Kind of Space 224

12.5.2 Adjust the Administration Limits Constantly 225

12.5.3 Execute API Forming and the Executives 225

12.6 Conclusion 225

References 226

13 Role of Big Data Analytics in Business Transformation 231
Riyaz Abdullah Sheikh and Nitin S. Goje

13.1 Introduction to Technology-Enabled Business Transformation 232

13.1.1 21st Century Business Challenges and Problems 232

13.1.2 Needs for Business Transformation 232

13.1.3 Digital Transformation 233

13.2 Introduction to Big Data, Big Data Analytics & Business Intelligence 234

13.2.1 What is Big Data? 234

13.2.1.1 Dimensions of Big Data 235

13.2.2 Big Data Analytics 237

13.2.2.1 What is Big Data Analytics (BDA)? 237

13.2.2.2 Why is Big Data Analytics Important? 238

13.2.3 Business Intelligence (BI) 238

13.3 Big Data Analytics and its Role in Business Transformation 239

13.3.1 Big Data Analytics and Value Proposition 240

13.3.2 Strategic Business Value of BDA 241

13.3.3 BDA Framework for Creating Business Value 242

13.3.3.1 Building Big Data Analytics Capabilities 244

13.3.3.2 Realization of Big Data Analytics Capabilities 244

13.4 Successful Real World Cases Leveraging BDA for Business Transformation 245

13.4.1 BDA in Retail: Walmart 245

13.4.2 BDA in Online Retail: Amazon 247

13.4.3 BDA in Social Media: Facebook 248

13.4.4 BDA in Manufacturing: Rolls-Royce 249

13.4.5 BDA in Healthcare: Apixio 249

13.5 BDA Capability Building Challenges 253

13.5.1 Data Quality 253

13.5.2 Management Challenges 254

13.5.3 BDA Value Assessment 254

13.6 Conclusion 255

References 256

14 Internet of Thing Trends 261
Sunny Preety and lbanga Kpereobong

14.1 Architecture of IoT 261

14.1.1 Covering Big Information Issue Using IoT 264

14.1.2 Tools and Analytics of Big Data 264

14.2 Dependency of Healthcare on IoT 267

14.2.1 Improved Disease Management 268

14.2.2 Remote Monitoring of Health 268

14.2.3 Connected Healthcare and Virtual Infrastructure 269

14.2.4 Accurate Data Collection and its Availability 270

14.2.5 Drug Management 270

14.2.6 Emergency 270

14.3 High Demand of Smart Homes 270

14.3.1 Advantages of Home Automation System 272

14.3.2 Smart City Implementation using IoT 273

14.3.3 IoT Applications for Smart Cities 273

14.3.4 Fitness of Buildings 273

14.4 Environmental Monitoring 274

14.5 Waste Management 274

14.6 Smart Parking 274

14.7 Routing System for Inner-City Bus Riders 275

14.8 Self-Ruling Driving 275

References 276

15 Internet of Things: Augmenting Business Growth 279
Trapty Agarwal, Gurjot Singh, Shubham Pradhan and Vikash Verma

15.1 Introduction 279

15.2 Role of IoT in the Business Growth 281

15.2.1 Architecture of IoT 281

15.2.1.1 3-Layer Architecture 281

15.2.1.2 4-Layer Architecture 282

15.2.1.3 5-Layer Architecture 283

15.2.2 Business Process 284

15.2.3 Business Models 285

15.3 Short Comes or Hurdles of IoT 286

15.3.1 Security Issues 286

15.3.2 Size Miniaturization 288

15.3.3 Ethical Challenges 289

15.3.4 Legal Concerns 290

15.3.5 Interoperability Issues 291

References 291

Index 293