Process-Aware Internet of Things Model: A Discovery Method Using IoT Data and Process Mining Techniques

The development of suitable systems for managing linked items and data has been made possible by the Internet of Things (IoT), which has completely changed corporate operations. An inventive method called "business process intelligence" combines process mining with process management to enable quick decision-making and real-time analysis. Nevertheless, there are difficulties in converting unstructured Internet of Things data into structured data, as structuring might lead to the loss of crucial information from the original data. In this research, a unique approach to automatically constructing IoT-connected business processes while preserving the original data richness is proposed. In order to transform enormous volumes of unstructured IoT data into data structures appropriate for process mining, the approach uses a model-driven architecture (MDA). The second stage involves semantic enrichment of process mining-generated event logs, which is achieved by annotating event log items with IoT-specific semantic concepts using ontologies.