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Integration of federated learning and blockchain for smart cities /

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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 tec...

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Bibliographic Details
Corporate Author: Safari, an O'Reilly Media Company
Other Authors: Singh, Krishna Kant (Editor), Singh, Akansha (Editor), T.R., Mahesh (Editor)
Format: eBook
Language:English
Published: Hoboken, NJ : Beverly, MA : John Wiley & Sons, Inc. ; Scrivener Publishing LLC, 2025.
Subjects:
Smart cities > Technological innovations.
Villes intelligentes > Innovations.
Intelligence (AI) & Semantics.
COMPUTERS.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Cover
  • Series Page
  • Title Page
  • Copyright Page
  • Contents
  • Preface
  • Part I: Introduction and Fundamentals
  • Chapter 1 Unlocking the Potential of Smart Cities: A Study of the Internet of Things and Artificial Intelligence Integration
  • 1.1 Introduction
  • 1.2 The Rise of Smart Cities
  • 1.3 Challenges of Urbanization
  • 1.4 The Promise of AI and IoT
  • 1.5 The Internet of Things (IoT) in Smart Cities
  • 1.6 What is IoT
  • 1.6.1 Components of an IoT Ecosystem
  • 1.7 Applications of IoT in Smart Cities
  • 1.7.1 Smart Infrastructure
  • 1.7.2 Smart Transportation
  • 1.7.3 Smart Energy Management
  • 1.7.4 Public Safety and Security
  • 1.8 Artificial Intelligence (AI) for Smart Cities
  • 1.9 Types of AI Relevant to Smart Cities
  • 1.9.1 Machine Learning
  • 1.9.2 Deep Learning
  • 1.9.3 Natural Language Processing (NLP)
  • 1.10 Applications of AI in Smart Cities
  • 1.10.1 Traffic Management and Optimization
  • 1.10.2 Smart Parking Management
  • 1.10.3 Smart Energy
  • 1.10.4 Smart Pavement Management System
  • 1.11 AI-Empowered IoT Security for Smart Cities
  • 1.12 Secure Smart Cities Framework Using IoT and AI
  • 1.13 IoT Paradigm into the Smart City Vision: A Survey
  • 1.13.1 Smart Cities and the Internet of Things
  • 1.14 Challenges Related to Implementing AI and IoT in Smart Cities
  • 1.15 The Future of AI and IoT in Smart Cities
  • 1.16 Conclusion
  • References
  • Chapter 2 Cutting Edge Smart IoT Applications: Transforming Everyday Life
  • 2.1 Introduction
  • 2.2 Transition of Internet to IoT
  • 2.3 The IoT Architecture
  • 2.3.1 The Architectural Three-Layer Structure
  • 2.3.2 The Five-Layer Architecture
  • 2.3.3 Sensors and Actuators
  • 2.4 Integration of IoT and Big Data Analytics
  • 2.4.1 Relationship between IoT and Big Data Analytics
  • 2.5 IoT Innovation: Emerging Trends and Applications- A Literature Review
  • 2.6 Mainstream Use Cases for Emerging Smart Applications for IoT
  • 2.7 IoT-Driven Intelligent Agricultural Applications
  • 2.8 The Emergence of Internet of Things (IoT) Devices into Smart Grids
  • 2.9 IoT Developments for Smart Home Usage
  • 2.10 IoT's Contribution to Industry 4.0 Adoption
  • 2.11 IoT-Driven Smart Transportation/Vehicles
  • 2.12 Utilizing IoT to Create Intelligent Energy Systems
  • 2.13 AI Supported IoT Technologies in Developing Smart Libraries
  • 2.14 IoT-Powered Wearable Biosensors with Nano-Integration
  • 2.15 Innovations in IoT-Powered Smart Environment Monitoring Systems
  • 2.15.1 Smart Water Pollution Monitoring (SWPM) Systems
  • 2.15.2 Smart Air Quality Monitoring (SAQM) Systems
  • 2.16 Conclusion
  • References
  • Chapter 3 Federated Learning in Smart Cities
  • 3.1 Introduction
  • 3.1.1 Overview of Smart Cities
  • 3.2 The Role of Machine Learning in Smart City Infrastructure
  • 3.3 Federated Learning: Concept and Principles
  • 3.3.1 Definition and Fundamentals of Federated Learning