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Full Description
The smart city paradigm combines smart homes, smart healthcare, smart transportation, smart industry, smart environment, and smart energy to ensure sustainability, well-being and comfortable living within the urban environment for the city's citizens. IoT enables computational intelligence to leverage the power of data analytics, machine learning, and artificial intelligence to extract meaningful insights from the vast amount of data generated by IoT devices. This synergy empowers connected devices to collect, process, and analyze data in real-time, enabling informed decision-making and predictive insights. Through adaptive algorithms and edge computing, the system can autonomously respond to changing conditions, optimize resource usage, and enhance energy efficiency. Security and anomaly detection mechanisms ensure the integrity of the IoT network, while human-machine interaction capabilities, facilitated by natural language processing, enable intuitive communication. This convergence of computational intelligence and IoT not only transforms data into actionable knowledge but also fosters the development of autonomous, efficient, and adaptive systems across diverse domains, ranging from smart cities to healthcare and industrial applications. The integration of computational intelligence with IoT enhances the capabilities of connected systems, making them smarter, more efficient, and better equipped to handle the complexities of the modern world. Smart City Computational Paradigms describes the connections between these state-of-the-art technologies and provides a comprehensive overview for readers interested in advanced technologies, identifying mentioned challenges and proposed solutions as well as developed framework. It covers the underlying theory, design techniques, classification, taxonomy and analytical tools, focusing primarily on the real time applications, uncertainty solutions and approaches with hands-on demonstration for decision making outcomes.
Contents
An Introduction to Sustainable Smart city: Taxonomy, Computing Paradigm, and Challenges
Edge-enabled IoT Architecture for Smart Cities
Bridging Social Disparities in Smart Cities with Multi-Microgrid Networks and its Dynamic Boundaries
Harnessing Deep Q Learning for Optimal Renewable Energy Grid Management
Integration of Edge-Enabled IoT in Vehicular Networks in Smart Cities
Enhanced Security in Vehicles: Adaptive Speed Control Mechanism Based on Seat Belts Wearing Patterns
Harnessing AI-driven IoT Solutions for Smart Environment
Revolutionizing Breast Cancer Diagnosis: A Comprehensive Review of AIoT Applications and Opportunities
Sustainable Health Monitoring with Multimodal Fusion: A Federated IoMT Framework for Early Myocardial Infarction Detection
DIdA-IoT: Digital Identification and authentication framework for access management of IoT Devices using blockchain
Block Withholding Attack Mitigation in Blockchains for Smart Cyber Physical System
Blockchain Integrated Federated Learning for Privacy Preserving Artificial Intelligence and Sustainable Smart City Infrastructure
Blockchain Empowered Federated Learning to Enhance Data Privacy and Sustainability in Smart Cities
Blockchain-Enabled Smart City Services: Integrating IoT and XAI for Efficient Public Fund Management
National and International Drift on Smart Cities
AI and Real-Time Auditing/Taxation in Smart City Economies: Navigating the Future
