Surjeet Dalal & Neeraj Dahiya 
Reshaping Intelligent Business and Industry [EPUB ebook] 
Convergence of AI and IoT at the Cutting Edge

List of Figures xxiii

List of Tables xxxi

Foreword xxxiii

Preface xxxv

Acknowledgments xli

Acronyms xliii

Part I: Artificial Intelligence Applications

1 Artificial Intelligence Overview: Architecture, Applications and Challenges 3
Geet Kiran Kaur, Nandita Malik, Sharad Chauhan, Mankiran Kaur

1.1 Introduction 4

1.2 Artificial Intelligence Agents 7

1.3 Artificial Intelligence Algorithms 9

1.4 Applications of Artificial Intelligence 11

1.5 Conclusion 16

References 16

2 Video Analytics Using Deep Learning Models 19
Sanjeev Kumar Bhatt, S. Srinivasan

2.1 Introduction 20

2.2 Video Analytics 27

2.3 Object Detection and Object Tracking 29

2.4 Industrial Application 44

2.5 Conclusion 46

References 46

3 Optimizing Search Engine for Enhancing Computing and Communication in Real-Time Systems 49
Meeta Singh, Poonam Nandal, Deepa Bura

3.1 Introduction 50

3.2 Literature Review 53

3.3 Requirement Specification 54

3.4 Testing and Validation 57

3.5 Result 64

3.6 Conclusion and Future Work 66

References 66

4 The Need for XAI: Challenges and Its Applications 69
Swati, Menu Vijarania, Vivek Jaglan, Dac-Nhuong Le

4.1 Introduction 70

4.2 Literature Review 71

4.3 The Need for Exploring XAI 72

4.4 Scope of Explanation 74

4.5 Differences in Research Methodology 75

4.6 Conclusion 78

References 78

5 Why Law Firms Need to Embrace Artificial Intelligence to Transform the Indian Legal Industry 81
B. Dharneesh, S. Thenisha, S. S. Srithick, A. Abirami

5.1 Introduction 82

5.2 What Is Artificial Intelligence? 83

5.3 The Law and Policy Relating to AI in India 88

5.4 The Morality Debate: The Ethicality of AI in Law 91

5.5 Conclusion 92

References 92

6 A Comparative Study of Supervised and Unsupervised Machine Learning Algorithms for Predictive Analytics 97
V. Belsini Gladshiya, Sharmila

6.1 Introduction 98

6.2 Predictive Analytics 98

6.3 Machine Learning 100

6.4 Applications of Supervised and Unsupervised Learning 104

6.5 Conclusion 104

References 105

7 Machine Learning Approach for Predicting the Price of Used Cars 107
Swati, Meenu Vijarania, Akshat Agarwal, Dac-Nhuong Le

7.1 Introduction 108

7.2 Related Work 108

7.3 Research Methodology 110

7.4 Model Description 113

7.5 Conclusion 114

References 115

Part II: Internet of Things Applications

8 Recent Industry-Defined and Domain-Specific Io T Architectures 119
Sharad Chauhan, Ritika Arora, Geetkiran Kaur

8.1 Introduction 120

8.2 Literature Review 121

8.3 Benefits and Major Components of Io T 123

8.4 Io T Implementation and Building Blocks 125

8.5 Io T Architecture 126

8.6 Conclusion 138

References 138

9 Io T Devices 141
Mukesh Choubisa

9.1 Introduction 142

9.2 Application of Io T 144

9.3 Io T Devices 148

9.4 Conclusion 156

References 156

10 Io T Securities: Applications, Security Issues and Solutions Using Diverse Technologies 157
Lovanya Bajaj, Nikhil Sharma, Prashant Giridhar Shambharkar

10.1 Introduction 158

10.2 Related Work 159

10.3 Overview of Internet of Things (Io T) 160

10.4 Security Issues Addressed Using Diverse Technologies 164

10.5 Open Challenges and Future Research Directions 168

10.6 Conclusion 169

References 169

11 FAMo S: Smart Farm Automatic Monitoring System 179
J. Dakshana, P. Balasubramaniam, A. Abirami, S. Tamil Selvan

11.1 Introduction 180

11.2 Related Work 181

11.3 Methodologies Proposed 183

11.4 Software Elements 184

11.5 Project Cost Estimation 193

11.6 Conclusion 195

References 195

12 Io T-Based Module to Control Electronic Devices Through Wi-Fi and Bluetooth 197
Ritu Shrivastava, Amit Shrivastava, Kapil Chaturvedi

12.1 Introduction 198

12.2 Literature Review 198

12.3 Proposed Wi-Fi Communication Module 198

12.4 IR (Infrared) Remote and Arduino Nano 203

12.5 Conclusion 206

References 206

13 An Insight into the Io T Building Blocks: Architecture, Framework, Principles, Applications and Challenges 207
Priyanka, Anoop Kumar, Keziah Nagaraj

13.1 Introduction 208

13.2 Related Work 208

13.3 Traditional and New Architecture of Io T 209

13.4 Design Principles and Decision Framework of Io T 213

13.5 Applications and Challenges 216

13.6 Conclusion 220

References 221

14 Interoperability: A Conceptual Framework 223
Soni Chaurasia, Kamal Kumar

14.1 Introduction 224

14.2 Inclusions in Io T Network 225

14.3 Io T Interoperability Protocols 226

14.4 Interoperability Conceptual Framework Proposed 228

14.5 Conclusion 233

References 234

15 Securing Io T Devices Against MITM and Do S Attacks: An Analysis 237
Vicky Tyagi, Amar Saraswat, Ashwani Kumar, Shalini Gambhir

15.1 Introduction 238

15.2 Architecture of Io T 238

15.3 Attacks on Io T 240

15.4 Some Possible Solutions to Avoid/Prevent Cyberattacks 246

15.5 Conclusions 247

References 247

Part III: Artificial Intelligence of Things: Smart City and Social Applications

16 AIo T-Based Smart Cities 253
Shelly Garg, Namitan

16.1 What Are Smart Cities? 254

16.2 Internet of Things 255

16.3 Introduction to Artificial Intelligence 258

16.4 AIo T in Smart Cities 263

16.5 Conclusion 265

References 265

17 Integrating Artificial Intelligence and Io T for Smart Cities: Applications and Challenges 267
Varsha Bhatia, Vivek Jaglan

17.1 Introduction 268

17.2 Overview of Smart Cities 270

17.3 AIo T in Smart Cities 273

17.4 Open Issues and Challenges 276

17.5 Conclusion 276

References 276

18 A Comprehensive Review of the Convergence of Blockchain, AI and Io T for Improving Social Interactions 279
Priya Sachdeva

18.1 Introduction 280

18.2 Research Methodology 282

18.3 The Risks and Challenges of Convergence in the Making of Smart Cities 287

18.4 Results and Findings 289

18.5 Future Research Directions for the Convergence of Blockchain, AI and Io T 290

18.6 Conclusion 291

References 292

19 AIo T-Based Smart Bin for Real-Time Monitoring and Management of Solid Waste 295
Ritik Agarwal

19.1 Introduction 296

19.2 Literature Review 297

19.3 Proposed Methodology 299

19.4 Conclusion 302

19.5 Challenges and Future Work 302

References 302

20 AIo T in the Education Sector 305
Zhumaniyaz Mamatnabiyev, Meirambek Zhaparov

20.1 Introduction 306

20.2 AIo T Applications in the Education Sector 307

20.3 Io T Development Stages 309

20.4 Conclusion 313

References 313

21 Artificial Intelligence of Things (AIo T)-Enabled Personalized Banking: Investigating Intention to Adopt 315
Ashok Singh Malhi, Raj K Kovid, Thipendra P Singh

21.1 Introduction 316

21.2 Literature Review and Hypotheses 317

21.3 Methodology 319

21.4 Results and Discussion 320

21.5 Conclusion 323

References 323

Part IV: Artificial Intelligence of Things: Applications in Healthcare

22 AI- and Io T-Enabled Healthcare Applications: A Review 327
N. Krishna Chaitanya, Mangesh M. Ghonge, G. Vimala Kumari, S.Leela Lakshmi

22.1 Introduction 328

22.2 Literature Review 329

22.3 Io T in Healthcare 329

22.4 Role of Artificial Intelligence in Healthcare 336

22.5 Challenges of Io T in Healthcare 340

22.6 Conclusion 340

References 341

23 An Extensive Survey of AIo T in Healthcare: Applications, Challenges and Future Opportunities 343
Gunjan, Ishwari Singh Rajput, Aditya Gupta, Soni Chaurasia

23.1 Introduction 344

23.2 Background 344

23.3 AIo T in Healthcare 351

23.4 AIo T Challenges and Opportunities 352

23.5 Conclusion 355

References 356

24 AI- and Io T-Based Face Recognition Model for Identification of Human Diseases 359
Pushan Kumar Dutta, Susanta Mitra

24.1 Introduction 360

24.2 Problem Identification 362

24.3 Proposed Methodology 364

24.4 Findings and Discussion 368

24.5 Conclusion 370

References 370

25 Io T in the Medical Field 373
S. Sasikala, K. Sharmila

25.1 Introduction 374

25.2 Security Matters for Io T in Healthcare 379

25.3 Cholesterol Control Levels 380

25.4 Io R Device for Cholesterol Test: CURO L 7 384

25.5 Challenges, Limitations, and Future Scope 385

25.6 Conclusion 386

References 387

26 Using Deep Learning to Characterize Persistent Physiological Parameters in Patient Monitoring Systems 391
Dhyanendra Jain, Anjani Gupta, Amit Kumar Pandey, Prashant Vats

26.1 Introduction 392

26.2 Using Deep Learning and AI for Surveillance 393

26.3 Other Ways that Do Not Rely on Machine Learning Knowledge 393

26.4 The Present Position of Learning Algorithms and Patient Monitoring 394

26.5 Possible Uses for Machine Learning Surveillance 397

26.6 Concerns and Future Objectives 399

26.7 Conclusions 400

References 400

Part V: Artificial Intelligence of Things: Applications in Agriculture and Industries

27 Smart Agriculture System Using Artificial Intelligence and Internet of Things 405
Meenakshi Yadav, Preety, Esha Saxena, Akhilesh Das

27.1 Introduction 406

27.2 Artificial Intelligence and Io T in Agriculture 407

27.3 Components of AI and Io T for Agriculture 410

27.4 Application of Io T and AI in Agricultural Automation 412

27.5 Challenges and Opportunities 414

27.6 Conclusion and Future Trends 416

References 417

28 Application of AI and Io T in Agriculture 419
Rashmi Singh

28.1 Agricultural Process 420

28.2 The Use of Artificial Intelligence in Agricultural Applications 421

28.3 Predictive Analytics and Precision Agriculture 422

28.4 Agricultural Robotics (Agrobots) 426

28.5 AI-Enabled System for Pest Control and Disease Diagnosis 433

28.6 Adopting AI: A Challenge for Farmers 435

28.7 Conclusion 436

References 436

29 Traffic Management System Using AIo T 439
Pallavi Choudekar, Rashmi Singh

29.1 Introduction 440

29.2 Smart Road Traffic Management System (SRTMS) 444

29.3 Smart Traffic Information System (TIS) 445

29.4 Smart Parking Management System 449

29.5 Smart Pavement Management System 452

29.6 Conclusion 454

References 455

30 Autonomous Vehicles: A Convergence Application of AI and Io T 459
Neha Gehlot, Amritpal Kuar

30.1 Introduction 460

30.2 Technical Challenges in Self-Driving Cars 465

30.3 Other Very Critical Areas 467

30.4 Blind Spots in Autonomous Vehicles 469

30.5 Potential Cyberattacks on Automated Vehicles 471

30.6 Conclusion 472

References 473

31 Convergence of Artificial Intelligence and Internet of Things for Software-Defined Radios 475
Shilpa Mehta, Xue Jun Li, Surjeet Dalal

31.1 Introduction 476

31.2 Review of SDR Receiver Architectures 477

31.3 Integration of SDR and Io T 482

31.4 Artificial Intelligence 484

31.5 Proposed AI-Based Receiver Architecture 492

31.6 AI Optimization 498

31.7 Results and Discussion 498

31.8 Conclusion 501

References 501

32 Artificial Intelligence of Things (AIo T) for Intelligent Data Design 507
Parul Gandhi, Raj Kumar

32.1 Introduction 508

32.2 AI, Io T, and Big Data Analytics 511

32.3 AIo T-Based Data Analytics and Decision-Making 512

32.4 Challenges 514

32.5 Role of AIo T in the Context of COVID- 19 515

32.6 Future Direction and Conclusion 516

References 516

33 A Study of Implementation of Blockchain Technology in Land Registration: A SWOT Analysis 519
Ankita Goyal, Upendra Singh

33.1 Introduction 520

33.2 Literature Review 521

33.3 Research Methodology 523

33.4 Discussion, Analysis, Limitation and Future Work 523

33.5 Conclusion 527

References 528

34 Smart Mask Disinfection System (SMDS) 531
N. Swetha Sridevi, N. C. Preethika, T. Subiksha

34.1 Introduction 532

34.2 Related Work 533

34.3 Smart Mask Disinfection System 534

34.4 Results and Discussion 544

34.5 Conclusion 545

References 546

Editors 547

Index 551

Surjeet Dalal, Ph D, is an associate professor in the Depar tment of Computer Science & Engineering at SR M Universit y, Har  yana, India. His cur rent research areas are ar  tif  icial intelligence, cloud computing, and Io T. He has published t wo cloud computing books and published 20+ papers in inter  national jour  nals.
Neeraj Dahiya, Ph D, is an assistant professor in the Depar tment of Computer Science & Engineering, SR M University, Har yana, India. His research areas include artificial intelligence, machine learning, speech processing, etc. Along with publishing research papers, Dahiya has four patents in artif icial intelligence and machine lear ning.
Vivek Jaglan, Ph D, is a professor at the DPG Institute of Technology and Management, Haryana, India. His research areas include artificial intelligence, neural networks & fuzzy logic, and Io T. Jaglan has published one book on cloud computing, 30+ papers in national/international journals, and 40+ papers for national and international conferences.
Deepika Koundal, Ph D, is an assistant professor at the University of Petroleum and Energy St udies, Dehradun, India. Her areas of interest are ar   tif   icial intelligence, biomedical imaging and signals, image processing, etc. She has published two books and 40+ research papers in inter  national jour  nals.
Dac-Nhuong Le, Ph D, obtained his doctorate in computer science from Vietnam National University, Vietnam in 2015. He is deputy head of the Faculty of Information Technology, Haiphong University, Vietnam. His area of research includes evaluation computing and approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, Io T, and image processing in biomedicine. He has over 50 publications and edited/authored many computer science books with the Wiley-Scrivener imprint.