An Internet of Things platform for heterogeneous data integration: Methodology and application examples

The Internet of Things (IoT) has revolutionized the industrial sector, yet digital transformation in this domain faces challenges due to the lack of standardized methodologies for IoT platform development. Many existing approaches struggle with issues such as data heterogeneity, lack of interoperability, and limited scalability when applied to large-scale industrial environments. In order to address the aforementioned gap, this work presents an IoT platform specifically designed for the agro-industrial sector, with interoperability as a core feature. Built using open technologies and an interoperable data model based on the OMA NGSI standard within the FIWARE framework, the platform enables seamless communication between heterogeneous devices and systems. Its scalable architecture allows the easy integration of new devices and scenarios. Additionally, the platform encapsulates industrial models (e.g., climate, production) as services and uses ETL processes to manage data heterogeneity, ensuring interoperability across systems. The platform, developed through a successful collaboration between academia and industry, has been validated in three sceneries that are exemplified in this work. To evaluate its scalability and performance, extensive load tests were conducted in a cloud environment, demonstrating its ability to handle high volumes of concurrent requests while maintaining efficient resource consumption.