<![CDATA[The rapid development of Internet of Things (IoT) technology has significantly transformed the conceptualization and implementation of smart city applications. This study aims to analyze the performance of Internet of Things (IoT) architecture in supporting smart city applications across various urban service domains, including transportation, environmental monitoring, public safety, and energy management. The research focuses on evaluating key performance indicators such as latency, throughput, scalability, reliability, and energy efficiency within a multilayer IoT architecture consisting of perception, network, middleware, and application layers.A quantitative experimental approach was employed by simulating smart city scenarios using heterogeneous sensors and communication protocols. Performance metrics were collected and analyzed under varying traffic loads and data transmission frequencies. The results indicate that network latency and bandwidth utilization significantly affect real-time data processing capabilities, particularly in time-sensitive services such as intelligent traffic systems and emergency response monitoring. Furthermore, the study found that edge computing integration enhances response time and reduces cloud dependency, thereby improving overall system efficiency and scalability.The findings suggest that optimizing network configuration, adopting lightweight communication protocols, and implementing distributed processing mechanisms are critical factors in enhancing IoT architectural performance for smart city applications. This research contributes to the development of a more reliable and efficient IoT infrastructure framework to support sustainable and data-driven urban governance. Future studies are recommended to explore security resilience and interoperability challenges in large-scale smart city deployments.]]>
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