AMORETTO: A Method for Deriving IoT-enriched Event Logs

TL;DR

AMORETTO is a novel method that systematically integrates IoT data into event logs, enabling more comprehensive and context-aware process analytics by classifying and combining IoT and process context information.

Contribution

It introduces the IoT-Pro context classification and a method for deriving IoT-enriched event logs, filling a gap in existing process analytics research.

Findings

Successfully applied to a real-life use case

Generated IoT-enriched logs supported specific analytical questions

Enhanced process insights through integrated IoT data

Abstract

Process analytics aims to gain insights into the behaviour and performance of business processes through the analysis of event logs, which record the execution of processes. With the widespread use of the Internet of Things (IoT), IoT data has become readily available and can provide valuable context information about business processes. As such, process analytics can benefit from incorporating IoT data into event logs to support more comprehensive, context-aware analyses. However, most existing studies focus on enhancing business process models with IoT data, whereas little attention has been paid to incorporating IoT data into event logs for process analytics. Hence, this paper aims to systematically integrate IoT data into event logs to support context-aware process analytics. To this end, we propose AMORETTO - a method for deriving IoT-enriched event logs. Firstly, we provide a classification of context data, referred to as the IoT-Pro context classification, which encompasses two context dimensions: IoT context and process context. Next, we present a method for integrating IoT data with event logs, guided by IoT-Pro, to yield IoT-enriched event logs. To demonstrate the applicability of AMORETTO, we applied it to a real-life use case and examined whether the derived IoT-enriched event log sufficed to address certain specific analytical questions.