Proceedings of International Conference on Applied Innovation in IT
2025/12/22, Volume 13, Issue 5, pp.613-619

Towards Intelligent Care: Human Behavior Analysis Using Energy Consumption and Door Operation Patterns in the Internet of Care Things


Svitlana Sokulieva, Ibrahim Kovan and Stefan Twieg


Abstract: The analysis of human behavior is an interdisciplinary science aimed at recognizing, describing, and predicting patterns of human behavior and emotional states. With the development of sensor technologies and data-driven approaches, new opportunities have emerged for observing and modeling everyday human activity. This study is based on a real-world dataset collected over one month from five participants in a residential environment. The data were gathered using environmental sensors, specifically contact sensors and energy consumption sensors, which enabled monitoring of user interactions with their surroundings. A set of statistical and machine learning methods was applied, including K-means clustering, correlation analysis, time-series representation, calculation of mean values, and aggregation of correlations. The results show how contact sensors and energy consumption sensors are related, how daily load is distributed, how periodic the data are, which sensors behave in a similar way within groups and across the system, and how individual behavioral models of each user can be formed. These findings highlight the potential of sensor-based analysis for advancing behavioral research and its practical applications.

Keywords: Human Behavior Analysis, Unsupervised Learning, Clustering, Pearson Correlation, Environmental Sensors, Internet-of-Care-Things (IoCT), Intelligent Algorithm, Anomaly Detection.

DOI: Under indexing

Download: PDF

References:

  1. World Health Organization, ADVOCACY BRIEF: Social isolation and loneliness among older people, Jul. 2021. [Online]. Available: https://iris.who.int/bitstream/handle/10665/343206/9789240030749-eng.pdf?sequence=1.
  2. P. Müller et al., “Making complex technologies accessible through simple controllability: Initial results of a feasibility study,” Applied Sciences, vol. 15, no. 2, p. 1002, 2025, doi: 10.3390/app15021002.
  3. S. Essahraui et al., “Human behavior analysis: a comprehensive survey on techniques, applications, challenges, and future directions,” IEEE Access, vol. 13, pp. 128379–128419, 2025, doi: 10.1109/ACCESS.2025.3589938.
  4. H. Liu, H. Gamboa, and T. Schultz, “Sensor-based human activity and behavior research: where advanced sensing and recognition technologies meet,” Sensors, vol. 23, no. 1, p. 125, 2023, doi: 10.3390/s23010125.
  5. Y. Li, G. Yang, Z. Su, S. Li, and Y. Wang, “Human activity recognition based on multienvironment sensor data,” Information Fusion, vol. 91, pp. 47–63, 2023, doi: 10.1016/j.inffus.2022.10.015.
  6. I. Kovan and S. Twieg, “Forecasting the energy consumption impact of electric vehicles by means of machine learning approaches,” in Proc. Int. Conf., 2022, doi: 10.1201/9781003293989-3.
  7. P. Malik et al., “An analysis of time series analysis and forecasting techniques,” IJARCCE, vol. 9, 2023.
  8. M. N. Martinez and M. J. Bartholomew, “What does it ‘mean’? A review of interpreting and calculating different types of means and standard deviations,” Pharmaceutics, vol. 9, no. 2, p. 14, 2017, doi: 10.3390/pharmaceutics9020014.
  9. A. M. Ikotun, A. E. Ezugwu, L. Abualigah, B. Abuhaija, and J. Heming, “K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data,” Information Sciences, vol. 622, pp. 178–210, 2023, doi: 10.1016/j.ins.2022.11.139.
  10. P. Sedgwick, “Pearson's correlation coefficient,” BMJ, vol. 345, p. e4483, 2012, doi: 10.1136/bmj.e4483.
  11. P. Schober, C. Boer, and L. A. Schwarte, “Correlation coefficients: Appropriate use and interpretation,” Anesthesia & Analgesia, vol. 126, no. 5, pp. 1763–1768, May 2018, doi: 10.1213/ANE.0000000000002864.


    HOME

       - Conference
       - Journal
       - Paper Submission to Conference
       - Paper Submission to Journal
       - Fee Payment
       - For Authors
       - For Reviewers
       - Important Dates
       - Conference Committee
       - Editorial Board
       - Reviewers
       - Last Proceeding


    PROCEEDINGS

       - Volume 13, Issue 5 (ICAIIT 2025)
       - Volume 13, Issue 4 (ICAIIT 2025)
       - Volume 13, Issue 3 (ICAIIT 2025)
       - Volume 13, Issue 2 (ICAIIT 2025)
       - Volume 13, Issue 1 (ICAIIT 2025)
       - Volume 12, Issue 2 (ICAIIT 2024)
       - Volume 12, Issue 1 (ICAIIT 2024)
       - Volume 11, Issue 2 (ICAIIT 2023)
       - Volume 11, Issue 1 (ICAIIT 2023)
       - Volume 10, Issue 1 (ICAIIT 2022)
       - Volume 9, Issue 1 (ICAIIT 2021)
       - Volume 8, Issue 1 (ICAIIT 2020)
       - Volume 7, Issue 1 (ICAIIT 2019)
       - Volume 7, Issue 2 (ICAIIT 2019)
       - Volume 6, Issue 1 (ICAIIT 2018)
       - Volume 5, Issue 1 (ICAIIT 2017)
       - Volume 4, Issue 1 (ICAIIT 2016)
       - Volume 3, Issue 1 (ICAIIT 2015)
       - Volume 2, Issue 1 (ICAIIT 2014)
       - Volume 1, Issue 1 (ICAIIT 2013)


    LAST CONFERENCE

       ICAIIT 2026
         - Photos
         - Reports

    PAST CONFERENCES

    ETHICS IN PUBLICATIONS

    ACCOMODATION

    CONTACT US

 

        

         Proceedings of the International Conference on Applied Innovations in IT by Anhalt University of Applied Sciences is licensed under CC BY-SA 4.0


                                                   This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License


           ISSN 2199-8876
           Publisher: Edition Hochschule Anhalt
           Location: Anhalt University of Applied Sciences
           Email: leiterin.hsb@hs-anhalt.de
           Phone: +49 (0) 3496 67 5611
           Address: Building 01 - Red Building, Top floor, Room 425, Bernburger Str. 55, D-06366 Köthen, Germany

        site traffic counter

Creative Commons License
Except where otherwise noted, all works and proceedings on this site is licensed under Creative Commons Attribution-ShareAlike 4.0 International License.