{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T05:06:02Z","timestamp":1779771962129,"version":"3.53.1"},"reference-count":28,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T00:00:00Z","timestamp":1779753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Robot. AI"],"abstract":"<jats:p>\n                    Densely populated enclosed environments, characterized by complex thermal stratification and overlapping breathing zones, represent high-risk clusters for the airborne transmission of respiratory pathogens. To address the dual challenges of physical boundary fidelity and prohibitive computational latency in traditional solvers, this study proposes a physics-validated, data-driven framework for the rapid spatiotemporal prediction of sneeze-induced pollutant dispersion. A CFD-Robotics Twin system was developed, utilizing an anthropomorphic manipulator governed by a Transformer-based Imitation Learning policy to replicate non-linear human sneezing kinematics. To ensure rigorous physical fidelity, the simulated flow fields and particle trajectories were validated through a dual-stage experimental benchmark involving anemometer measurements and robotic-arm-nozzle discharge tests. On this basis, a spatial-preserving U-ConvLSTM architecture was developed. By integrating a convolutional U-Net encoder with ConvLSTM layers and symmetric skip-connections, the model maintains absolute physical coordinates (x,y) and bypasses the topological destruction inherent in conventional flattened architectures. Evaluation via mass error\n                    <jats:inline-formula>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"m1\">\n                        <mml:mrow>\n                          <mml:mo stretchy=\"false\">(<\/mml:mo>\n                          <mml:mrow>\n                            <mml:msub>\n                              <mml:mrow>\n                                <mml:mi>\u03b5<\/mml:mi>\n                              <\/mml:mrow>\n                              <mml:mrow>\n                                <mml:mtext>mass<\/mml:mtext>\n                              <\/mml:mrow>\n                            <\/mml:msub>\n                          <\/mml:mrow>\n                          <mml:mo stretchy=\"false\">)<\/mml:mo>\n                        <\/mml:mrow>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    and Center of Mass distance confirms strict adherence to Eulerian conservation laws. Results demonstrate that the surrogate model achieves a computational acceleration of three orders of magnitude while maintaining high structural similarity (Structural Similarity Index Measure = 0.992). Furthermore, the framework translates abstract concentration fields into practical engineering metrics, including the Dynamic Safety Radius and vertical exposure windows. This research provides a scientifically rigorous tool for real-time risk assessment and the optimization of indoor spatial layouts to mitigate pathogen exposure.\n                  <\/jats:p>","DOI":"10.3389\/frobt.2026.1846010","type":"journal-article","created":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T04:48:06Z","timestamp":1779770886000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatiotemporal prediction of sneeze pollutants in enclosed spaces: a CNN-LSTM approach validated by field measurements and CFD-Robotics arm twin system"],"prefix":"10.3389","volume":"13","author":[{"given":"Mingyu","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Architecture, Taiyuan University of Technology","place":["Taiyuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shujia","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Architecture and Design, Shanxi Vocational University of Engineering Science and Technology","place":["Jinzhong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Architecture, Taiyuan University of Technology","place":["Taiyuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanru","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Architecture, Taiyuan University of Technology","place":["Taiyuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiyi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Architecture, Taiyuan University of Technology","place":["Taiyuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianyue","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Architecture, Taiyuan University of Technology","place":["Taiyuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yawen","family":"Ren","sequence":"additional","affiliation":[{"name":"Institute of Coal Chemistry, Chinese Academy of Sciences","place":["Taiyuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxi","family":"Lu","sequence":"additional","affiliation":[{"name":"Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiahe","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Architecture, Taiyuan University of Technology","place":["Taiyuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,26]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"F1","DOI":"10.1017\/jfm.2020.720","article-title":"Effects of ventilation on the indoor spread of covid-19","volume":"903","author":"Bhagat","year":"2020","journal-title":"J. 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