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
Abstract
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).
- DOI: 10.1007/978-3-031-56107-8_17
- BibTeX: see at DBLP
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