Enhancing Process Mining with IoT data

Process Mining (PM) techniques can be used to automatically discover the process flows of Business Processes (BPs) from event logs. Incorporating process context data in PM could yield more accurate models and help understand better the behaviour of BPs and the issues they may present. Though a fair amount of context data can be collected using IoT devices, existing PM techniques rarely exploit IoT context data. This project focuses on developing PM techniques that will be able to consider real-time data produced by IoT devices and sensors, next to regular event data of BPs. We refer to these techniques as IoT-enhanced Process Mining techniques. More precisely, this research investigates: 1) How to combine IoT context data and BP event logs, 2) How to discover contextualised processes and check their conformance, and 3) How to visualise and improve them.