Extending the SensorThings API Data Model – Improving Interoperability and Use Case Flexibility in IoT
Enrico Gallinucci; Hasan Yasar; Peter Chen; Sotirios Liaskos; Patrick Marcel; Sergio Cesare; Frederik Gailly (Hrsg). ER 2024 : companion proceedings of the 43rd International Conference on Conceptual Modeling: ER Forum, Special Topics, Posters and Demos : Pittsburgh, Pennsylvania, USA, October 28-31, 2024. Aachen: CEUR/RWTH 2024 S. 1 - 14
Erscheinungsjahr: 2024
Publikationstyp: Diverses (Konferenzbeitrag)
Sprache: Englisch
Inhaltszusammenfassung
This study presents an enhancement to the OGC SensorThings API Data Model tailored for Internet of Things (IoT) environments, demonstrated with a Smart Farming application enhancement. The designed data model addresses critical challenges faced in real-world settings like industrial environments, adhering to the FAIR principles of Findability, Accessibility, and, in particular, Interoperability and Reusability. Beyond the practical use case of crop monitoring, we offer a conceptual framework ...This study presents an enhancement to the OGC SensorThings API Data Model tailored for Internet of Things (IoT) environments, demonstrated with a Smart Farming application enhancement. The designed data model addresses critical challenges faced in real-world settings like industrial environments, adhering to the FAIR principles of Findability, Accessibility, and, in particular, Interoperability and Reusability. Beyond the practical use case of crop monitoring, we offer a conceptual framework for future projects across various domains. The resulting architecture demonstrates how modular components improve adaptability and extendibility through standardization and interoperability. This modular approach decouples modules such as device management from data storage, ensuring consistent data handling and supporting the integration and maintenance of diverse and evolving applications. The iterative development and evaluation process underlines the solution’s effectiveness in managing IoT environments in practice. The findings highlight the potential for these extensible modules to be applied in other contexts, promoting a standardized yet flexible approach to IoT data management, supporting effective database design, and deriving best practices and design guidance for future projects. Additionally, our models approach IoT heterogeneity and interoperability, demonstrating clear advantages in modularity and standardized data handling, essential for managing complex, real-world IoT deployments in Smart Farming.» weiterlesen» einklappen