Göynügür, EmreŞensoy, MuratMel, G. de2019-01-152019-01-152018-01-12978-1-5386-2715-0http://hdl.handle.net/10679/6100https://doi.org/10.1109/BigData.2017.8258269Due to copyright restrictions, the access to the full text of this article is only available via subscription.Monitoring and following health and safety regulations are especially important - but made difficult - in hazardous work environments such as underground mines to prevent work place accidents and illnesses. Even though there are IoT solutions for health and safety, every work place has different characteristics and monitoring is typically done by humans in control rooms. During emergencies, conflicts may arise among prohibitions and obligations, and humans may not be better placed to make decision without any assistance as they do not have a bird's-eye-view of the environment. Motivated by this observations, in this paper, we discuss how health and safety regulations can be implemented using a semantic policy framework. We then show how this framework can be integrated into an in-use smart underground mine solution. We also evaluate the performance of our framework to show that it can cope with the complexity and the amount of data generated by the system.engrestrictedAccessconferenceObject20182990299700042807370212310.1109/BigData.2017.8258269Policy frameworkOBDAPlanningConflict detectionConflict resolutionHealth and safetySemantic web2-s2.0-85047820689