Over the last few years, the number of embedded sensors have been increased in smart
devices (e.g., mobile phones and smart watches) that are supported by several vendors
in which each one has different data models. As a result to the heterogeneity of these
devices, a variety of data are generated by heterogeneous sensors. Therefore, some
researchers have attempted to mitigate the incompatibility between the massive
quantity of the collected data and facilitate meaningful data integration between
machines by using the semantic web technologies. Furthermore, to analyze and
understand a given phenomenon extensively such as monitoring the environment,
getting data from one source is insufficient and needs to get and combine some
additional data from multiple sources. During data fusion process of multiple sources,
some semantic conflicts may be arise and therefor need to be detected and resolved
before presented to the user. Traditional multi-sensor data fusion can deal with the same
type of data effectively. However, the heterogeneous data with different units of
measurement must be compatible to provide a comprehensive and reliable feedback
related to a specific phenomenon.
To address this issue, this study proposes a semantic data fusion framework to provide
the semantic data integration between heterogeneous sensors data. Taking the semantics
of the data into the consideration, the proposed framework should detect and resolve the
semantic conflicts of measurement units that might arise between the heterogeneous
sensors data.
Furthermore, this study has introduced with an application was implemented as a proofof-
concept to demonstrate the visibility of the proposed framework. Consequently,
empirical evaluations were then carried out to evaluate the effectiveness of the proposed
framework through evaluating a semantic data integration potential and query
processing performance with a set of SPARQL queries taken from the benchmark and
real row weather datasets. Furthermore, the evaluation of detection and resolving of
measurement units conflicts was carried out based on temperature measurements and
their variant units. The proposed framework has shown to be efficient compared to the
other framework benchmark in terms of query processing performance within a
semantic data integration. Moreover, the proposed framework has proved its efficiency
especially in terms of detecting and resolving the semantic conflicts of data
measurement units, which were neglected in the benchmark
عنوان الرسالة
الباحث
غيلان محمد الجماعي
سنة الإقرار
تاريخ المناقشة
الملخص
