Abstract
Data interoperability is a crucial requirement in IoT to improve services and enhance business opportunities and innovation. Integrating synergetic applications with heterogeneous data formats is a critical issue that needs to be addressed to achieve interoperability. The use cases indicate IBM ACE is promising in resolving integration issues among on-premises and cloud applications. Further, many efforts are observed to address the interoperability issue apart from the IBM ACE approach. However, they are complex, restricted to few data formats, and use proprietary solutions. To address these above-mentioned issues, this paper proposes the Integration of Synergetic IoT applications with Heterogeneous format data for Interoperability using IBM ACE (ISHII). Further, an intelligence-based data recognition module in the proposed ISHII is trained with standard features defined in RFC 7111, 8259, 8996, JSON-LD of W3C, and Google’s Protobuf. Subsequently, recognized heterogeneous format data are integrated and translated to interoperable format using Data Format Description Language (DFDL) with Extended SQL codes on IBM ACE. Finally, the performance of ISHII has been evaluated with synthetically generated patient monitoring and room ambiance datasets with reference to accuracy, time required for integration, and translation efficiency.
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All data generated or analyzed during this study are included in this published article. Methods to generate the dataset are mentioned in the article. A sample dataset is presented in the article.
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Sandeep, M., Chandavarkar, B.R. Integration of Synergetic IoT Applications with Heterogeneous Format Data for Interoperability Using IBM ACE. SN COMPUT. SCI. 5, 3 (2024). https://doi.org/10.1007/s42979-023-02279-x
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DOI: https://doi.org/10.1007/s42979-023-02279-x