Identification of IoT Medical Devices APIs Through Ontology Mapping Techniques



The Internet of Things (IoT) is being hailed as the next industrial revolution, dealing with billions of heterogeneous devices that are connected over the Internet. In this context, both devices’ integration and their derived data integration are among the most complicated tasks that need to be addressed, especially in the healthcare domain. Despite the critical importance, the current approaches for confronting heterogeneity of IoT medical devices have not been sufficiently effective. For that reason, in this paper a generic mechanism is presented for managing the huge amounts of heterogeneous IoT medical devices that exist in combination with their derived data, by understanding the nature and the meaning of the Application Programming Interfaces (API) methods of these devices that are responsible for gathering data out of them. In order to achieve the latter, the mechanism understands the nature and the meaning of these API methods by translating them into ontologies, while identifying and mapping the syntactic and semantic similarities among them, so as to recognize and use the ones that are responsible for gathering the devices’ data, and finally integrate it into different platforms. The proposed mechanism is evaluated through a specific use case, producing reliable results, thus being considered as a reference value of high quality and accuracy

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