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However, diagnostic precision remains challenged by complex VOC mixtures, low analyte abundance, and significant biological variability. This study introduces an Intelligent Odor Monitoring System (IOMS) guided by infection\u2010associated biomarker identification. Identification of infection\u2010associated markers including ethyl lactate and 3,5\u2010dimethyloctane informed the development of a high\u2010sensitivity sensor array integrated into an individually ventilated cage (IVC) platform. Operating at 1\u00a0Hz, the system generated 3,628,800 longitudinal measurements over a 7\u2010day infection cycle, capturing distinct odor\u2010response dynamics between infected and uninfected groups while exploratory principal component analysis supported stage\u2010associated temporal patterns. Machine\u2010learning models, including KNN, SVM, and LDA, leveraged these temporal dynamics to model the complete infection cycle with the best internal accuracy reaching 99.88% and model generalizability further supported by an independent blinded cohort. Notably, early sensor\u2010response shifts were observed at 7\u20138 hours post\u2010infection (hpi), and robust model discrimination was achieved by 9 hpi, supporting the feasibility of early\u2010stage infection monitoring in this murine model. By fusing biomarker\u2010guided odor sensing with machine learning, the IOMS enables autonomous, continuous surveillance and highlights the potential of longitudinal VOC monitoring for preclinical respiratory infection studies.<\/jats:p>","DOI":"10.1002\/advs.76244","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T10:46:19Z","timestamp":1782211579000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Real\u2010Time and Non\u2010Invasive Detection of Respiratory Viral Infections Using an Intelligent Odor Monitoring System (IOMS)"],"prefix":"10.1002","volume":"13","author":[{"given":"Yajie","family":"Shen","sequence":"first","affiliation":[{"name":"State Key Laboratory of Virology and Biosafety Institute for Vaccine Research College of Life Sciences Wuhan University Wuhan Hubei P. R. 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