Andrea Burattin

Associate Professor
Technical University of Denmark

Identifying Variation in Personal Daily Routine Through Process Mining: A Case Study

G. Di Federico, C. Fernández-Llatas, Z. Ahmadi, M. Shirali, A. Burattin
Paper cover

The study of daily routines has gained substantial attention, especially in healthcare. Understanding the activities and behaviors of individuals, particularly older adults, has the potential to play a crucial role in providing effective care and support, for example, when it comes to spotting deviations from it automatically.

Process mining is a valuable tool for analyzing routine dynamics and identifying variations. However, human behavior is unstructured and characterized by variability, making it difficult to derive a process model representing only the control flow.

In this paper, we employ a multi-dimensional process discovery and conformance checking methodology to a real-world dataset representing a person’s behavior in a smart environment. The derived model combines control flow and statistics on the data. The results, on the real-world data, highlight that the approach can identify variations in the inhabitant’s behavior.

Paper Information and Files

In Proceedings of ICPM Workshop (PODS4H), (2023).

General rights

Copyright and moral rights for the publications made accessible in the public website are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.

If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Latest website update: 18 April 2024.