<![CDATA[The Internet of Things (IoT) has increasingly played a significant role in the development of adaptive and real-time environmental monitoring systems. However, integrating multiple IoT devices remains challenging due to variations in data transmission intervals, communication protocols, and processing capabilities across devices. These differences often complicate system interoperability and data management within a unified monitoring platform. To address this issue, this study proposes an API-based modular architecture as a solution for integrating heterogeneous IoT devices in environmental monitoring systems. The proposed architecture separates core system functions into independent modules, including data acquisition, device management, and data visualization. The proposed architecture is evaluated through a multi-device environmental monitoring implementation configured with different logging intervals in order to assess communication performance and data consistency. The novelty of this study lies in its architectural approach to handling heterogeneous data transmission intervals in multi-device IoT environments using a modular API-based design. The experimental results indicate that the average communication latency is approximately 200ms, while the average daily data logging volume exceeds 3,500 entries per device. Furthermore, analysis of logging interval variations shows a time deviation of less than 3 seconds, which remains within the acceptable range for real-time environmental monitoring applications. The results demonstrate that the proposed architecture achieves success rate of over 97%, confirming the reliability of the proposed API-based modular architecture. Overall, the findings suggest that the modular API-driven architecture not only improves the flexibility and scalability of multi-device IoT integration but also maintains reliable data consistency and efficient communication performance.]]>
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