The advent of the Internet of Things (IoT) has ushered in transformative possibilities for smart cities, with the potential to revolutionize urban living through enhanced connectivity and data-driven decision-making. However, the effective realization of IoT in smart cities hinges upon the seamless interoperability of diverse devices and systems. To address this critical need, the oneM2M standards initiative has emerged as a foundational framework for IoT interoperability. In this research paper, we perform an exploratory analysis of three prominent open-source oneM2M based interoperability systems-Mobius, OM2M, and ACME. We leverage an existing large-scale system provided by our Smart City Living Lab deployed at IIIT Hyderabad, sprawling a 66-acre campus featuring over 370 nodes across eight verticals. We investigate the architectural characteristics of each solution, considering their strengths and limitations in facilitating IoT interoperability. Through this analysis, our paper aims to provide valuable insights for stakeholders seeking to implement IoT interoperability solutions in the context of smart cities. By evaluating the strengths and limitations of Mobius, OM2M, and ACME, we seek to offer guidance for selecting the most suitable solution. Our analysis reveals that the optimal framework choice depends on specific quality constraints: Mobius excels in performance, while ACME offers advantages in ease of setup for smaller-scale implementations.

The increase of IoT devices and the emergence of smart cities have revolutionized urban development, offering numerous benefits while addressing environmental concerns. This has caused an increase in the usage of IoT frameworks, and the need for efficient architecture and standardized ontology is imminent. In this regard, we propose a distributed, multi-layered data platform architecture comprising the Data Monitoring Layer (DML), Data Storage Layer (DSL), Data Enhancement Layer (DEnL), and Data Exchange Layer (DEL). Our architecture achieves interoperability, facilitates data transfer between nodes, enables telemetry data retrieval, and ensures cross-platform and cross-device compatibility. It addresses the challenges of handling increased sensor data and user demands by providing high throughput and scalability support. We investigated Smart City Living Lab at IIIT Hyderabad an existing large-scale system deployed within a 66-acre campus. This system consists of 291 nodes. By studying this deployed system, we were able to gather valuable real-world data, allowing us to analyze the challenges and potential solutions related to data architecture. Our results show improvements of up to 41.23\% in throughput and a decrease in latency by 29.19\% for data insertion from the sensor nodes. The retrieval by the data client gives an increase of over 800\% in both throughput and number of requests through DENL. These metrics are compared to a centralised data platform architecture. We conclude by discussing the implications of our findings and suggesting future work.