Deep Learning and Blockchain Technology for Smart and Sustainable Cities

Subramaniyaswamy V, G Revathy, Logesh Ravi, N. Thillaiarasu, Naresh Kshetri

• Publisher: Auerbach Publications
• Year: 2025
• eBook ISBN: 9781040346266
• Topic: Computer Science
• Subtopic: City Planning & Urban Development
• Index: Computer Science

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.

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Editors
• Contributors
• 1 Applications of Smart City
• 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 in Smart City Applications
• 6 Enabling Smart Cities: A Comprehensive Study of IoT and IIoT Integration in Diverse Industries
• 7 Smart City Applications Using Blockchain Technologies
• 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 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’s Disease 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
• Index