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A learning approach for query planning on spatio-temporal IoT data
2019
Zenodo
The ever-increasing growth of the Internet of Things (IoT) has attracted a considerable amount of research attention from the Semantic Web community in order to address the challenge of poor interoperability. However, our survey of research work has shown that the goal of providing an intelligent pro- cessing and analysis engine for IoT has still not been fully achieved. Central to this problem is the requirement for a semantic spatio-temporal query processing engine that is able to not only
doi:10.5281/zenodo.2580841
fatcat:or3hunzqyvf4veeuojrohrvc6u