In this digital era, a smart city can become an intelligent society by using advances in emerging technologies. Specifically, the rapid adoption of deep learning (DL) in fusion with blockchain technology has led to a new digital smart city ecosystem. A broad spectrum of deep learning and blockchain applications promise solutions for problems in areas ranging from risk management and financial services to cryptocurrency to public and social services. Furthermore, the convergence of AI and blockchain technology is revolutionizing the smart city network architecture to build sustainable ecosystems. However, these advances in technology bring both opportunities and challenges in creating sustainable smart cities.To help planners and developers to meet these challenges and exploit these opportunities, Deep Learning and Blockchain Technology for Smart and Sustainable Cities takes a deep dive into the technologies and applications that enable smart and sustainable cities. It provides a comprehensive literature review of the security issues and problems that impact the deployment of blockchain systems in smart cities. It presents a detailed discussion of key factors in the convergence of blockchain and DL technologies that help form sustainable smart societies. The book also discusses blockchain security enhancement solutions and summarizes main key points necessary for developing various blockchain and DL-based intelligent transportation systems.The book concludes with a discussion of open issues and future research direction. These include new security suggestions and guidelines for a sustainable smart city ecosystem. Also discussed is 6G-enabled DL and blockchain in real time applications
Les mer
This book examines the paradigm shift towards a new digital smart city ecosystem brought about by the rapid adoption of deep learning, which has been combined with blockchain technology. Deep learning and blockchain applications cover a wide range of domains, ranging from risk management to social services, which this book explores.
Les mer
1. Applications of Smart City in India 2. Assessing the Efficiency of Integrated RBSA and SBFS Approaches Utilizing Machine Learning Techniques for Email Categorization in Smart City Infrastructure 3. Unleashing the Power of Data and Security by Integrating Deep Learning and Blockchain in Smart City Infrastructure Development: A Future Perspective 4. An Extensive Analysis of Blockchain Technology Addressing Many Facets of IoT, Smart Cities, and Deep Learning 5. Exploring the Potential of Blockchain and Deep Learning nn Smart City Applications 6. Enabling Smart Cities: A Comprehensive Study of IoT and IIoT Integration in Diverse Industries 7. Applications of Smart City 8. Insights into Tomorrow: A Review of Rainfall Intelligence Integration in Smart City Innovations for Future Urban Development 9. IIOT for Smart Cities 10. Enhancing Smart City Sustainability through Multiple Coal Classification Utilizing Deep Learning. 11. Preventive Care: Smart Strategies for Elderly Fall Detection and Prevention 12. smartVAST: Vulnerability, Attacks, Security, and Threats on Smart Cities with Impact and Ability in Blockchain Technology 13. Empowering Urban Planning with Accurate Air Quality Index Prediction: Hybrid Deep Learning Models for Smart Cities 14. Enhancing Healthcare in Smart Cities: The Fusion of MCPS and IoT 15. Efficiency Analysis of LSTM-based Earthquake Forecasting for Smart City Resilience: A Time Complexity Perspective 16. Smart Farming: Empowering Agriculture in Smart Cities 17. Anomaly Detection of Parkinson Diseases with Voice Analysis Patterns Using ML Algorithms in Smart Cities 18. Location and Weather-based Prediction of Yields Using Machine Learning Algorithms in Smart Cities 19. Gesture Language Translator in Smart Cities 20. Blockchain-Driven AI Framework for Early Human Monkeypox Detection
Les mer

Produktdetaljer

ISBN
9781032748573
Publisert
2025-05-22
Utgiver
Vendor
Auerbach
Høyde
234 mm
Bredde
156 mm
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
392

Biographical note

Dr. Subramaniyaswamy V is a professor at the School of Computing, SASTRA Deemed University, Thanjavur, India.

Dr. G Revathy is an assistant professor at the School of Computing, SASTRA Deemed University, Thanjavur, India.

Dr. Logesh Ravi is an assistant professor at the Centre for Advanced Data Science (CADS), Vellore Institute of Technology, Chennai, India.

Dr. Thillaiarasu N is an associate professor at the School of Computing and Information Technology, REVA University, Bengaluru, India.

Dr. Naresh Kshetri is an assistant professor of cybersecurity at the College of Science, Technology, and Health, Lindenwood University, St. Charles, MO, USA.