Abstract
SI is used to exchange the information from one place to another place in an efficient and meaningful way. The data is generated from various heterogeneous devices, communication protocols, and data formats that are enormous in nature. This is a significant problem for Internet of things (IoT) application developers to make the IoT generated data interoperable. In the existing approaches there is lack of well-defined standards and established tools to solve semantic interoperability (SI) problem in IoT and big data applications. This chapter proposes a collaborative approach to address the SI in IoT and big data for health care applications. In the health care domain, the physicians and patients may interoperate with each other effectively and conveniently. Both IoT and big data are dominant technologies for health care applications. This chapter mainly deals with two use cases, namely (1) IoT in health care systems and (2) big data analytics in health care systems. Gruff and Tableau tools were used for performing experiments and analysis on health care data. The obtained results are convincing and support both patients’ and physicians’ health care data as semantically interoperable. This chapter summarizes, with supporting SI, the tools and developing methodologies in both IoT and big data analytics technologies for health care applications.
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