Routine Pattern Learning and Anomaly Detection Applied to Lone Workers Through Topic Modeling

Ana Cravidão Pereira, Marília Barandas, Hugo Gamboa, Hugo Gamboa

2025

Abstract

Learning routines and identifying anomalous behaviors play a critical role in worker safety. Identifying deviations from normal patterns helps prevent accidents, ensuring enhanced safety in complex environments. Topic modeling is frequently used to discover hidden semantics patterns and is well-suited to the complexity of routines in human behavior. However, its utility in complex time-series analysis and as a baseline for anomaly detection has not been widely explored. This work proposes a novel solution to accurately model complex routines using topic modeling, enabling the identification of anomalies through a statistical approach. A dataset of human movement recordings was collected over up to seven consecutive months, capturing the routines of three lone workers, with each accumulating between 414 and 955 hours of recording time. This dataset served as the basis for a comprehensive analysis of the results, showing strong alignment between visually observed patterns in routines and the outcomes of the proposed method. Additionally, detecting anomalies across models with varying training days confirms that online learning enhances the accuracy and adaptability of routine modeling. Topic modeling allows for in-depth learning of routines, capturing latent patterns undetectable to humans. This capability prevents abnormal events, leading to a proactive approach to predictive risk assessment.

Paper Citation

in Harvard Style

Pereira A., Barandas M. and Gamboa H. (2025). Routine Pattern Learning and Anomaly Detection Applied to Lone Workers Through Topic Modeling. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS; ISBN 978-989-758-731-3, SciTePress, pages 935-942. DOI: 10.5220/0013236600003911

in Bibtex Style

@conference{biosignals25,
author={Ana Pereira and Marília Barandas and Hugo Gamboa},
title={Routine Pattern Learning and Anomaly Detection Applied to Lone Workers Through Topic Modeling},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS},
year={2025},
pages={935-942},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013236600003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS
TI - Routine Pattern Learning and Anomaly Detection Applied to Lone Workers Through Topic Modeling
SN - 978-989-758-731-3
AU - Pereira A.
AU - Barandas M.
AU - Gamboa H.
PY - 2025
SP - 935
EP - 942
DO - 10.5220/0013236600003911
PB - SciTePress