Hardcover. 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 DL and blockchain applications promises solutions for problems in areas ranging from risk management and financial services to cryptocurrency to public and social services. Furthermore, the convergence of artificial intelligence 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. This book also discusses blockchain security enhancement solutions and summarizes main key points necessary for developing various blockchain and DLbased intelligent transportation systems.This 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 6Genabled DL and blockchain in realtime applications. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de ref. del art�culo 9781032748573

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T�tulo: Deep Learning and Blockchain Technology for ...

Editorial: Taylor & Francis Ltd, London

A�o de publicaci�n: 2025

Encuadernaci�n: Hardcover

Condici�n: new

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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 DL and blockchain applications promises solutions for problems in areas ranging from risk management and financial services to cryptocurrency to public and social services. Furthermore, the convergence of artificial intelligence 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. This book also discusses blockchain security enhancement solutions and summarizes main key points necessary for developing various blockchain and DL‑based intelligent transportation systems.

This 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.

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Dr. V. Subramaniyaswamy is a professor at the School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.

Dr. G Revathy is an assistant professor, Department of CSE, Srinivasa Ramanujan Centre, 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. N. Thillaiarasu is an associate professor at the School of Computing and Information Technology, REVA University, Bengaluru, India.

Dr. Naresh Kshetri is faculty member, Department of Cybersecurity at the Rochester Institute of Technology, Rochester, New York, USA.

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