Abstract
This work addresses challenges in IoT data quality management. IoT applications in domains like Smart Cities, Smart Healthcare, and Industry 4.0 rely on the Internet for automated services. However, resource limitations and harsh environments of IoT devices raise hardware integrity concerns. IoT data encompasses characteristics like data types, sampling rates, intervals, and specific tasks and states. Since IoT data is not always tied to specific application contexts, managing data quality is crucial to meet diverse application requirements. Asclepius, a data quality framework for IoT infrastructure, is introduced. It comprises software components deployed on IoT devices based on their roles, ensuring interoperability and standardized interfaces. Asclepius serves as a data quality backbone, facilitating reliable data transportation and routing while meeting application requirements. Real device implementation of part of our proposal. The practical incorporation of a segment is present as tangible proof, substantiating its efficacy through real-world device deployment and assessment.
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CITATION STYLE
De Aquino, G. R. C., & De Farias, C. M. (2023). Asclepius: Data quality framework for IoT. In DIVANet 2023 - Proceedings of the International ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications (pp. 69–76). Association for Computing Machinery, Inc. https://doi.org/10.1145/3616392.3623407
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