The accelerated pace of urbanization and density of population density in metropolitan areas have created significant challenges in energy management, transportation, healthcare, waste management, and public safety. Traditional approaches to urban infrastructure are insufficient to ensure long-term sustainability and resilience. The Internet of Things (IoT), when integrated with intelligent decision-making technologies such as Artificial Intelligence (AI), Edge/Fog computing, and Block chain, offers a transformative solution for building sustainable smart cities. This paper proposes an Intelligent IoT-Enabled Framework for Sustainable Smart Cities, which integrates heterogeneous IoT devices with multi-layered architectures to enable real-time monitoring, predictive analytics, and energy-efficient operations. The framework consists of five layers-IoT perception, edge/fog processing, cloud intelligence, application services, and security/privacy-designed to optimize system scalability, reduce latency, and ensure data confidentiality. By leveraging AI-driven analytics at the edge and cloud layers, the system supports smart energy grids, intelligent traffic control, healthcare monitoring, and waste management, leading to improved quality of life and reduced environmental footprint. The proposed framework also introduces lightweight security mechanisms and block chain-based trust management to address vulnerabilities inherent in large-scale IoT deployments. Preliminary analysis and simulations suggest that the framework can achieve up to 25-30% energy savings, reduce traffic congestion by 20%, and enhance data security in resource-constrained IoT environments. This work contributes toward the vision of sustainable, intelligent, and resilient urban ecosystems, offering practical guidelines for city planners, researchers, and policymakers.
Prasad et al. (Sat,) studied this question.
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