AI-Cloud for Next Generation Smart Cites and Smarter Infrastructure

The rapid growth of urbanization has increased the need for intelligent, efficient, and sustainable approach, it needs AI-Cloud integrated technology for rapid evolution of urban environments demands intelligent systems capable of optimizing infrastructure, reducing energy utilization, traffic congestion, and fault response time. This study presents an AI–Cloud Integrated Smart City System designed to unify Artificial Intelligence (AI) and Cloud Computing (CC) technologies for efficient urban infrastructure management. This work implemented using Python-based AI frameworks integrated with AWS cloud infrastructure to evaluate the performance of the proposed AI–Cloud architecture. This paper also provides as Unified model repository with lifecycle management. The performance indicators are energy utilization, traffic congestion, and fault response time were analysed across multiple urban service domains and also found that data processing latency, resource allocation efficiently, system scalability and operational cost reduction and proved that AI–Cloud performed through the real-world smart city and smart infrastructure, the results obtained as AI-Cloud efficient than 27% for energy utilization efficiency, a 35% reduction in traffic congestion, and a 40% faster response time than conventional system.