Stay ahead of the curve in urban innovation with this essential guide that provides a comprehensive roadmap for federated learning and blockchain to build secure, intelligent, and efficient smart city ecosystems.
As cities grow smarter, the demand for secure, decentralized, and privacy-preserving technologies is greater than ever. This book explores how federated learning and blockchain are transforming urban landscapes by enabling intelligent, secure, and efficient systems. By combining the power of decentralized machine learning with the transparency and security of blockchain, this book provides a roadmap for tackling challenges in urban mobility, energy management, public safety, and healthcare, delving into theoretical frameworks, architectural designs, security considerations, and real-world case studies to illustrate the impact of these technologies. This book serves as a comprehensive guide for researchers, industry professionals, and policymakers seeking to understand, implement, and innovate within smart city ecosystems.
Readers will find the volume:
Explores the synergy between federated learning and blockchain, offering cutting-edge solutions for smart city challenges; Addresses critical issues of data privacy, decentralized AI, and secure digital infrastructure in urban environments; Features practical case studies on smart transportation, energy management, healthcare, and governance; Provides a forward-looking perspective on how emerging technologies will shape the cities of tomorrow.
Audience
Academics, researchers, industry professionals, and policymakers working in the fields of artificial intelligence, machine learning, blockchain, IoT, cybersecurity, smart city planning, and urban technology development.
Preface xxiii Part I: Introduction and Fundamentals 1 1 Unlocking the Potential of Smart Cities: A Study of the Internet of Things and Artificial Intelligence Integration 3 Anuradha Dhull, Tripti Sharma, Shilpa Mahajan and Akansha Singh 2 Cutting Edge Smart IoT Applications: Transforming Everyday Life 27 Anuradha Dhull, Anshita Gera, Monika Lamba and Akansha Singh 3 Federated Learning in Smart Cities 57 Suman Chahar and Kuldeep Kaswan 4 Blockchain Revolutionizing Tourism Supply Chain Management: Transparency, Traceability, and Security 81 Suresh N., Sundar Rajan S. and Anitha G. Part II: Core Technologies and Methodologies 123 5 Enhancing Threshold Cryptosystems with Blockchain Technology: A Cost-Effective and Scalable Approach Using Smart Contracts and ZkSNARKs 125 Rahul Raghavan Tharammal 6 Perspective of Blockchain, Federated Learning, Smart Cities, and Economy 151 Rahul Vadisetty 7 Federal Learning Approach for Smart Cities 173 Rahul Vadisetty 8 Federated Learning Applications in Retail, Finance, and Banking for Smart Cities 195 Madhuri Gupta, Prince Gupta and Sameer Malik Part III: Integration of Technologies for Smart Cities 223 9 Leveraging Blockchain and Federated Learning for Smart Cities 225 Umesh Gupta, Gopal Singh Rawat, Jay Vardhan Singh and Akshat Jain 10 Integrating Blockchain and Federated Learning for Enhanced Security and Privacy in Smart Cities 257 Dipali Sarvate, Siddharth Shankar Mishra, V. Shanmugapriya and Dheerendra Panwar 11 Harnessing Federated Learning for Smart City Data Management in Cloud Environments 289 Naween Kumar, Akansha Singh, Vaibhav Saini, Ankit Dubey, Subham Sharma, Sasmita Pathy and Krishna Kant Singh Part IV: Applications and Case Studies 325 12 Smart Environments—A Fusion of Technology and Context-Aware Systems 327 Ashima Narang, Poonam Sharma, Akansha Singh and Krishna Kant Singh 13 Federated Learning Applications for Urban Intelligence: A Holistic Examination in Retail, Finance, and Banking 351 Baskar Kasi, Saravanan Ramalingam, T. Sathish Kumar and A. Mohan 14 Innovative Urban Data Processing: Federated Learning and Blockchain in Smart City Ecosystems 391 Naween Kumar, Akansha Singh, Subham Sharma, Ankit Dubey, Vaibhav Saini and Krishna Kant Singh 15 Transforming Urban Landscapes: The Role of IoT and Drones in Smart City Development 427 Naween Kumar, Akansha Singh, Vaibhav Saini, Subham Sharma, Sahani Pooja Jaiprakash and Krishna Kant Singh 16 Next-Generation Urban Infrastructure: Leveraging Cloud and Edge Computing for Smart City Development 467 Naween Kumar, Akansha Singh, Sahani Pooja Jaiprakash, Vaibhav Saini, Subham Sharma and Krishna Kant Singh Part V: Governance and Societal Impacts 503 17 Blockchain, Governance, and Government for Smart Cities 505 Rahul Vadisetty 18 Internet of Things and Artificial Intelligence in Smart Cities 529 Ashutosh Srivastava, Divya Srivastava, Madhushi Verma, Arpita Singh, Ishita Adhikari and Ayan Singh Rana 19 Effectiveness of Education and Blockchain for Smart Cities 549 Rahul Vadisetty Part VI: Advanced Applications and Future Directions 571 20 Data Science and Big Data Analytics for Enhanced Urban Planning in Smart Cities 573 Naween Kumar, Akansha Singh, Vaibhav Saini, Ankit Dubey, Subham Sharma and Krishna Kant Singh 21 Enhancement of Smart Cities Through Blockchain 611 Anand Polamarasetti 22 Federated Learning in Image Processing for Clothes Recognition 635 Madhuri Gupta, Harhsit Budhraja, Nipun Bhardwaj, Lakshit Agarwal, Ritvik Singh and Richa Chaturvedi 23 Performance Analysis of Segmentation Techniques for Knee Osteoarthritis Detection from X-Ray Images 659 Shashikala H.K. and Suresh M.B. 24 Blockchain for Smart Industry Management 683 Priya N. and Sudhagar Kalyanasundaram References 707 About the Editors 711 Index 713
Krishna Kant Singh, PhD is the Director at the Delhi Technical Campus, Greater Noida, India. He has authored 25 books and over 160 research papers in international journals. He is an associate editor of IEEE Transactions on Computational Social Systems, and Senior editor of IEEE Access. His research interests include machine vision, remote sensing, deep learning, and generative AI. Akansha Singh, PhD is a professor in the School of Computer Science, Engineering, and Technology at Bennett University, Greater Noida, India, with over 18 years of teaching and research experience. She has published over 100 research papers and authored over 30 books in advanced areas of computer science. Her expertise spans image processing, deep learning, machine learning, remote sensing, and IoT, with a strong focus on AI-driven solutions for healthcare and environmental sustainability. Mahesh T.R., PhD is the Program Head of the Department of Computer Science and Engineering in the School of Engineering and Technology, at Jain (Deemed-to-be University), Bengaluru, India. He has published over 180 research articles in international and edited several books. His research interests include image processing, machine learning, deep learning, artificial intelligence, IoT, and data science.
