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

Gemma Di Federico*, Carlos Fernandez-Llatas, Zahra Ahmadi, Mohsen Shirali, Andrea Burattin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


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.
Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Process Mining (ICPM 2023)
Publication date2024
ISBN (Print)978-3-031-56106-1
ISBN (Electronic)978-3-031-56107-8
Publication statusPublished - 2024
Event5th International Conference on Process Mining - Rome, Italy
Duration: 23 Oct 202327 Oct 2023
Conference number: 5


Conference5th International Conference on Process Mining


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