A probabilistic model for context-aware proactive decision making

The emergence of the Internet of Things paves the way for enhancing the monitoring capabilities of enterprises by means of extensive use of physical and virtual sensors generating a multitude of data. The generated real-time data streams provide the basis for anticipating future undesired events and thus enable enterprises to decide and act ahead of time, i.e. in a proactive manner. Proactive information systems can benefit from the use of context-awareness in order to provide more reliable recommendations. In this paper we propose a probabilistic model for context-aware proactive event-driven decision making that deals with the uncertainty that is inherent in the contextual elements' values. We validated our approach in an oil and gas industry scenario and we conducted a comparative analysis.

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