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Edge of Intelligence: Exploring the Frontiers of AI at the Edge

Edge of Intelligence: Exploring the Frontiers of AI at the Edge

          
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About the Book

The book offers cutting-edge insights and practical applications for Edge AI, making it essential for anyone looking to stay ahead in the rapidly evolving landscape of artificial intelligence and Edge computing. Edge of Intelligence: Exploring the Frontiers of AI at the Edge examines the transformative potential of edge AI, showcasing how artificial intelligence is being seamlessly integrated with Edge computing to revolutionize various industries. This book offers a comprehensive overview of the latest research, trends, and practical applications of Edge AI, providing readers with valuable insights into how this cutting-edge technology is enhancing efficiency, reducing latency, and enabling real-time decision-making. From optimizing vehicular networks in the era of 6G to the innovative use of AI in crop monitoring and educational technology, this book covers a broad spectrum of topics, making it an essential read for anyone interested in the future of AI and Edge computing. Featuring contributions from leading experts and researchers, Edge of Intelligence highlights real-world examples and case studies that demonstrate the practical implementation of edge AI in diverse sectors such as smart cities, recruitment, and nano-process optimization. The book also addresses critical issues related to privacy, security, and the fusion of blockchain with edge computing, providing a holistic view of the challenges and opportunities in this rapidly evolving field. Audience Engineers, data scientists, IT professionals, researchers, and academics in the fields of artificial intelligence, computer science, and telecommunications, as well as industry professionals in sectors such as the automotive, agriculture, education, and urban planning industries.

Table of Contents:
Preface xvii 1 A Review on Computational Optimization Strategies and Collaborative Techniques of Vehicular Task Offloading in the Era of Internet of Vehicles and 6G 1 Aishwarya R., V. Vetriselvi and Meignanamoorthi D. 1.1 Introduction 2 1.2 Computational Optimization Strategies 7 1.3 Collaborative Techniques 29 1.4 Security 34 1.5 Challenges and Future Research Directions 39 1.6 Conclusion 41 2 A Study on EDGE AI Application in Crop Monitoring 51 N.A. Natraj, Pethuru Raj, M. Karpagam and S. Gunanandhini 2.1 Introduction 52 2.2 Crop Monitoring AI Basics 57 2.3 AI Applications in Crop Monitoring 60 2.4 Challenges and Possible Future Paths of AI in Crop Monitoring 65 2.5 Conclusion 70 3 A Survey on Reconfigurable Co-Processors Computing Linear Transformations 73 Atri Sanyal and Amitabha Sinha 3.1 Different Linear Transforms 74 3.2 Reconfigurable Computing 75 3.3 Field Programmable Gate Array 78 3.4 Survey of Existing Work 82 3.5 Performance Comparison of Different Reconfigurable Co-Processors Implementing Linear Transformation(s) 86 3.6 Conclusions and Future Work 88 4 Conversational AI Model for Effective Responses with Augmented Retrieval (CAMERA) Based Chatbot on NVIDIA Jetson Nano 93 Kiran Jot Singh, Divneet Singh Kapoor, Amit Singh Bora, Khushal Thakur and Anshul Sharma 4.1 Introduction 94 4.2 Background 100 4.3 Literature Review 103 4.4 Proposed Framework 108 4.5 Results 112 4.6 Conclusion and Future Scope 115 5 Edge Computing in Educational Technology: The Power of Edge AI for Dynamic and Personalized Learning 121 Ganeshayya Shidaganti, V. Aditya Raj, V.R. Monish Raman and Shubeeksh Kumaran 5.1 Introduction: Unveiling the Potential of Edge AI in Educational Technologies 122 5.2 Challenges of Traditional Education in the Digital Age 122 5.3 Edge Computing and AI: Revolutionizing Educational Dynamics 126 5.4.1 Methodology 132 5.5 Benefits of the Edge AI for Learning 139 5.6 Discussions on Edge AI for Education 142 5.7 Ethical Considerations in Edge AI for Educational Settings 144 5.8 Future of Education with Edge AI 147 5.9 Conclusion 149 6 Edge Computing Revolution: Unleashing Artificial Intelligence Potential in the World of Edge Intelligence 153 Saravanan Chandrasekaran, S. Athinarayanan, M. Masthan, Anmol Kakkar, Pranav Bhatnagar and Abdul Samad 6.1 Introduction 154 6.2 Definitions 157 6.3 Concepts and Architecture 160 6.4 Algorithms for Artificial Intelligence in Edge Computing 163 6.5 Optimization of Edge Devices Using a Class of Neural Networks 166 6.6 Bio-Inspired Algorithms for Edge Computing 169 6.7 Real-Time Intelligence-Based Edge Device 172 6.8 Conclusion 182 7 Ensuring Privacy and Security in Machine Learning: A Novel Approach to Efficient Data Removal 193 Velammal B. L. and Aarthy N. 7.1 Introduction 193 7.2 Related Works 195 7.3 Objectives 197 7.4 System Design 198 7.5 Experimental Results 206 7.6 Conclusion and Future Scope 212 8 Federated Learning in Secure Smart City Sensing: Challenges and Opportunities 215 Monika Gandhi, Sushil Kumar Singh, Ravikumar R. N. and Krunal Vaghela 8.1 Introduction 216 8.2 Related Work 218 8.3 Federated Learning-Based Smart Cities Sensing Architecture for IoT-Enabled Smart Cities Sensing 232 8.4 Open Issues, Related Challenges and Opportunities 239 8.5 Conclusions 246 9 Fusion of Blockchain and Edge Computing for Seamless Convergence 253 Indu Bala 9.1 Introduction to Blockchain and Edge Computing 254 9.2 Key Components of Blockchain and Edge Integration 258 9.3 Challenges and Opportunities in Integration 261 9.4 Security Considerations in a Converged Environment 264 9.5 Use Cases and Applications 265 9.6 Benefits of Blockchain and Edge Integration 268 9.7 Regulatory and Compliance Issues 269 9.8 Future Trends and Innovations 271 9.9 Recommendations 274 9.10 Conclusion 276 10 Industry Adapting the Machine Learning Scenario in Recruitment and Selection of Employees 279 Megha Ojha, Vinay Kandpal, Archana Singh and Amar Kumar Mishra 10.1 Introduction 280 10.2 Evolution of Machine Learning in Recruitment 280 10.3 Methodological Insights and Study Contexts 281 10.4 Ensuring Reliability and Replicability 283 10.5 Ethical Implications of ML in Hiring 288 10.6 Addressing Ethical Concerns in Real-World Applications 289 10.7 Ensuring Data Privacy in ML Models for Hiring 289 10.8 Areas for Future Research in ML for Hiring 301 11 Machine Learning for Nano Process Optimization 307 Manjushree Nayak and A. Sai Satya Narayana 11.1 Introduction 308 11.2 Literature Review 309 11.3 Conclusion 323 12 Quantum Computing for Cryptography: An Extensive Survey 327 Soma Debnath and Avishake Adhikary 12.1 Introduction 328 12.2 Related Works 336 12.3 Statistical Analysis 339 12.4 Comparative Analysis 341 12.5 Conclusion and Future Scope 345 13 Role of Blockchain Technology in e-HRM in the Era of Artificial Intelligence: Focus on the Indian Market 351 Archana Singh, Girish Lakhera, Megha Ojha and Amar Kumar Mishra 13.1 Introduction 351 13.2 Literature Review 354 13.3 Blockchains for Business and EHRM 357 13.4 Case Studies 361 13.6 Ethical Implications of Implementing Blockchain in HRM 362 13.7 Conclusion 364 14 Smart City Innovations and IoT as a Frontier of AI at the Edge of Intelligence 369 Priya Soni 14.1 Introduction: Smart City Innovations and Internet of Things for Data Analytics 370 14.2 Concept of Smart Cities and the Significance of Data-Driven Decision-Making 371 14.3 Fundamental Components of Data Analytics in Smart Cities 373 14.4 Advanced-Data Analytics Techniques 375 14.5 Uses of IoT-Enabled Data Analytics in Smart Cities 381 14.6 Challenges and Considerations 382 14.7 Future Prospects and Emerging Trends of Smart City Innovations and Internet of Things (IoT) for Data Analytics 384 14.8 Indian Case Studies: Successful Implementations on Smart City Innovations and Internet of Things for Data Analytics 386 14.9 Conclusion 388 15 Synergies Unleashed: The Convergence of AI and Edge Computing in Transformative Technologies 391 R. Shobarani, P. Dhivya, G. Savitha, S. Santhi, K. Surya Prakhash and R. Kavitha 15.1 Introduction 392 15.2 Related Study 395 15.3 Reduction of Latency 400 15.4 Bandwidth Efficiency 401 15.5 Privacy and Security 402 15.6 Real-Time Decision-Making: Decision Made with an Example 405 15.7 Distributed Architecture: Decentralized Processing Occurs with an Example 407 15.8 Edge Computing Use Cases 410 15.9 Challenges and Advancements 412 15.10 Future Trends 423 15.11 Conclusion 430 References 431 Index 433


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Product Details
  • ISBN-13: 9781394314379
  • Publisher: John Wiley & Sons Inc
  • Publisher Imprint: Wiley-Scrivener
  • Language: English
  • Returnable: Y
  • Weight: 851 gr
  • ISBN-10: 139431437X
  • Publisher Date: 21 Mar 2025
  • Binding: Hardback
  • No of Pages: 464
  • Sub Title: Exploring the Frontiers of AI at the Edge


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