Abstract: This study presents a quantitative approach to analyzing window opening and closing behaviors using skeletal recognition technology. Video data of five participants performing these actions were captured and processed using the Openpose model, which detects 25 human joints. Focusing on the shoulder, elbow, and wrist, the study analyzed time-series joint coordinates to identify motion patterns and behavioral characteristics. The results revealed consistent relationships among joint movements and enabled accurate distinction between left- and right-hand operations. In addition, behavioral distribution characteristics were examined by visualizing horizontal and vertical skeletal displacements. The results showed that stationary postures are concentrated near a reference origin, whereas window operation actions produce distinct spatial shifts in the coordinate space, indicating that occupant behavior can be interpreted as a sequence of state transitions composed of distinct behavioral phases. The findings confirm that skeletal data can effectively represent occupant behavior without intrusive sensors, providing a non-contact and privacy-preserving monitoring method. This approach contributes to the development of human-centered intelligent building systems that can adapt indoor environments in real time based on occupant actions, thereby improving both thermal comfort and energy efficiency. Future research will expand behavioral categories and explore real-time implementation in smart building applications.

Jewon Oh, Daisuke Sumiyoshi, Takahiro Yamamoto, Takahiro Ueno and Tatsuto Kihara. “Human-Centered Behavioral Analysis of Window Operation Using AI-Based Skeletal Recognition”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.12 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0161222

@article{Oh2025,
title = {Human-Centered Behavioral Analysis of Window Operation Using AI-Based Skeletal Recognition},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0161222},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0161222},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {12},
author = {Jewon Oh and Daisuke Sumiyoshi and Takahiro Yamamoto and Takahiro Ueno and Tatsuto Kihara}
}