SCALABLE SMART CITY PLATFORM USING IOT AND CLOUD COMPUTING
Abstract
Rapid urbanization has significantly increased pressure on transportation systems, healthcare, energy distribution, environmental monitoring, waste management, public safety, and other municipal services. Traditional city management approaches are increasingly unable to process the enormous volume of heterogeneous data generated by modern urban environments. The integration of the Internet of Things (IoT) with cloud computing provides an effective solution for developing scalable smart city platforms capable of supporting real-time monitoring, intelligent decision-making, and efficient resource management. This paper presents a scalable cloud-enabled smart city architecture that integrates IoT sensing devices, edge gateways, cloud infrastructure, big data analytics, and artificial intelligence to support multiple smart city services within a unified platform. The proposed architecture employs a layered framework consisting of perception, communication, edge computing, cloud services, data analytics, application, and security layers to improve scalability, interoperability, reliability, and service availability. The study critically reviews recent advances in IoT cloud integration, identifies major challenges including security, privacy, latency, interoperability, and energy efficiency, and proposes practical strategies for addressing these limitations through containerization, micro services,edge cloud collaboration, and AI-driven resource orchestration. The proposed framework demonstrates how cloud computing can dynamically allocate computational resources to accommodate growing IoT deployments while maintaining quality of service. The paper concludes that scalable IoT-cloud platforms represent the foundation for next-generation smart cities and recommends future integration with digital twins, federated learning, block chain, and 6G communication technologies for improved sustainability and resilience.
