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CORRECTION article

Front. Psychol., 12 January 2026

Sec. Environmental Psychology

Volume 16 - 2025 | https://doi.org/10.3389/fpsyg.2025.1729654

Correction: From motion to meaning: understanding students' seating preferences in libraries through PIR-enabled machine learning and explainable AI

  • 1. Department of Architecture, Dokuz Eylul University, Izmir, Türkiye

  • 2. Department of Computer Engineering, Dokuz Eylul University, Izmir, Türkiye

  • 3. UCL Institute for Environmental Design and Engineering, London, United Kingdom

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In the published article, the Conflict of interest statement was erroneously given as:

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The correct conflict of interest statement is below:

The author(s) declared that that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Author GI voluntarily disclosed a collaboration on a different article with reviewer ZND that started during the review of this article. GI at the time of the review was not aware that ZND was one of reviewers of the paper. This had no impact on the peer review process and the final decision.

The original version of this article has been updated.

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Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Summary

Keywords

seat preference, occupancy monitoring, academic library, machine learning, explainable AI, spatial behavior, user comfort, PIR sensors

Citation

Izmir Tunahan G, Tuysuzoglu G and Altamirano H (2026) Correction: From motion to meaning: understanding students' seating preferences in libraries through PIR-enabled machine learning and explainable AI. Front. Psychol. 16:1729654. doi: 10.3389/fpsyg.2025.1729654

Received

21 October 2025

Accepted

11 December 2025

Published

12 January 2026

Approved by

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Volume

16 - 2025

Updates

Copyright

*Correspondence: Gizem Izmir Tunahan, ; Hector Altamirano,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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