Details

Reshaping Intelligent Business and Industry

Convergence of AI and IoT at the Cutting Edge
1. Aufl.

von: Surjeet Dalal, Neeraj Dahiya, Vivek Jaglan, Deepika Koundal, Dac-Nhuong Le
216,99 €
Verlag:	Wiley
Format:	EPUB
Veröffentl.:	06.09.2024
ISBN/EAN:	9781119905189
Sprache:	englisch
Anzahl Seiten:	640

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Beschreibungen

Titelbeschreibung

The convergence of Artif icial Intelligence (AI) and Internet of Things (IoT) is reshaping the way industries, businesses, and economies function; the 34 chapters in this collection show how the full potential of these technologies is being enabled to create intelligent machines that simulate smart behavior and support decision-making with little or no human interference, thereby providing startling organizational efficiencies. Readers will discover that in Reshaping Intelligent Business and Industry: <ul> <li>The book unpacks the two superpowers of innovation, AI and IoT, and explains how they connect to better communicate and exchange information about online activities;</li> <li>How the center and the network's edge generate predictive analytics or anomaly alerts;</li> <li>The meaning of AI at the edge and IoT networks.</li> <li>How bandwidth is reduced and privacy and security are enhanced;</li> <li>How AI applications increase operating efficiency, spawn new products and services, and enhance risk management;</li> <li>How AI and IoT create 'intelligent' devices and how new AI technology enables IoT to reach its full potential;</li> <li>Analyzes AIOT platforms and the handling of personal information for shared frameworks that remain sensitive to customers’ privacy while effectively utilizing data.</li> </ul> Audience This book will appeal to all business and organization leaders, entrepreneurs, policymakers, and economists, as well as scientists, engineers, and students working in artificial intelligence, software engineering, and information technology.

Inhaltsverzeichnis

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 IoT Architectures 119 Sharad Chauhan, Ritika Arora, Geetkiran Kaur 8.1 Introduction 120 8.2 Literature Review 121 8.3 Benefits and Major Components of IoT 123 8.4 IoT Implementation and Building Blocks 125 8.5 IoT Architecture 126 8.6 Conclusion 138 References 138 9 IoT Devices 141 Mukesh Choubisa 9.1 Introduction 142 9.2 Application of IoT 144 9.3 IoT Devices 148 9.4 Conclusion 156 References 156 10 IoT 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 (IoT) 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 FAMoS: Smart Farm Automatic Monitoring System 179 J. Dakshana, P. Balasubramaniam, A. Abirami, S. TamilSelvan 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 IoT-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 IoT 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 IoT 209 13.4 Design Principles and Decision Framework of IoT 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 IoT Network 225 14.3 IoT Interoperability Protocols 226 14.4 Interoperability Conceptual Framework Proposed 228 14.5 Conclusion 233 References 234 15 Securing IoT Devices Against MITM and DoS Attacks: An Analysis 237 Vicky Tyagi, Amar Saraswat, Ashwani Kumar, Shalini Gambhir 15.1 Introduction 238 15.2 Architecture of IoT 238 15.3 Attacks on IoT 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 AIoT-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 AIoT in Smart Cities 263 16.5 Conclusion 265 References 265 17 Integrating Artificial Intelligence and IoT for Smart Cities: Applications and Challenges 267 Varsha Bhatia, Vivek Jaglan 17.1 Introduction 268 17.2 Overview of Smart Cities 270 17.3 AIoT 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 IoT 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 IoT 290 18.6 Conclusion 291 References 292 19 AIoT-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 AIoT in the Education Sector 305 Zhumaniyaz Mamatnabiyev, Meirambek Zhaparov 20.1 Introduction 306 20.2 AIoT Applications in the Education Sector 307 20.3 IoT Development Stages 309 20.4 Conclusion 313 References 313 21 Artificial Intelligence of Things (AIoT)-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 IoT-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 IoT in Healthcare 329 22.4 Role of Artificial Intelligence in Healthcare 336 22.5 Challenges of IoT in Healthcare 340 22.6 Conclusion 340 References 341 23 An Extensive Survey of AIoT 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 AIoT in Healthcare 351 23.4 AIoT Challenges and Opportunities 352 23.5 Conclusion 355 References 356 24 AI- and IoT-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 IoT in the Medical Field 373 S. Sasikala, K. Sharmila 25.1 Introduction 374 25.2 Security Matters for IoT in Healthcare 379 25.3 Cholesterol Control Levels 380 25.4 IoR 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 IoT in Agriculture 407 27.3 Components of AI and IoT for Agriculture 410 27.4 Application of IoT 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 IoT 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 AIoT 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 IoT 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 IoT 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 (AIoT) for Intelligent Data Design 507 Parul Gandhi, Raj Kumar 32.1 Introduction 508 32.2 AI, IoT, and Big Data Analytics 511 32.3 AIoT-Based Data Analytics and Decision-Making 512 32.4 Challenges 514 32.5 Role of AIoT 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

Autorenportrait

Surjeet Dalal, PhD, 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 IoT. He has published t wo cloud computing books and published 20+ papers in inter national jour nals. Neeraj Dahiya, PhD, 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, PhD, is a professor at the DPG Institute of Technology and Management, Haryana, India. His research areas include artificial intelligence, neural networks & fuzzy logic, and IoT. Jaglan has published one book on cloud computing, 30+ papers in national/international journals, and 40+ papers for national and international conferences. Deepika Koundal, PhD, 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, PhD, 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, IoT, and image processing in biomedicine. He has over 50 publications and edited/authored many computer science books with the Wiley-Scrivener imprint.

Back cover copy

The convergence of Artif icial Intelligence (AI) and Internet of Things (IoT) is reshaping the way industries, businesses, and economies function; the 34 chapters in this collection show how the full potential of these technologies is being enabled to create intelligent machines that simulate smart behavior and support decision-making with little or no human interference, thereby providing startling organizational efficiencies. Readers will discover that in Reshaping Intelligent Business and Industry: <ul><li>The book unpacks the two superpowers of innovation, AI and IoT, and explains how they connect to better communicate and exchange information about online activities; </li> <li>How the center and the network’s edge generate predictive analytics or anomaly alerts;</li> <li>The meaning of AI at the edge and IoT networks. </li> <li>How bandwidth is reduced and privacy and security are enhanced;</li> <li>How AI applications increase operating efficiency, spawn new products and services, and enhance risk management;</li> <li>How AI and IoT create ‘intelligent’ devices and how new AI technology enables IoT to reach its full potential;</li> <li>Analyzes AIOT platforms and the handling of personal information for shared frameworks that remain sensitive to customers’ privacy while effectively utilizing data.</li></ul> Audience This book will appeal to all business and organization leaders, entrepreneurs, policymakers, and economists, as well as scientists, engineers, and students working in artificial intelligence, software engineering, and information technology.