Smart City Computational Paradigms

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.