{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:14:45Z","timestamp":1774628085739,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T00:00:00Z","timestamp":1677628800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science and Higher Education of the Russian Federation","award":["FEFM-2021-0014"],"award-info":[{"award-number":["FEFM-2021-0014"]}]},{"name":"Ministry of Science and Higher Education of the Russian Federation","award":["121111600136-3"],"award-info":[{"award-number":["121111600136-3"]}]},{"name":"Ministry of Science and Higher Education of the Russian Federation","award":["121122300070-9"],"award-info":[{"award-number":["121122300070-9"]}]},{"name":"Institute of Natural and Technical Systems","award":["FEFM-2021-0014"],"award-info":[{"award-number":["FEFM-2021-0014"]}]},{"name":"Institute of Natural and Technical Systems","award":["121111600136-3"],"award-info":[{"award-number":["121111600136-3"]}]},{"name":"Institute of Natural and Technical Systems","award":["121122300070-9"],"award-info":[{"award-number":["121122300070-9"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The use of bivalve mollusks as bioindicators in automated monitoring systems can provide real-time detection of emergency situations associated with the pollution of aquatic environments. The behavioral reactions of Unio pictorum (Linnaeus, 1758) were employed in the development of a comprehensive automated monitoring system for aquatic environments by the authors. The study used experimental data obtained by an automated system from the Chernaya River in the Sevastopol region of the Crimean Peninsula. Four traditional unsupervised machine learning techniques were implemented to detect emergency signals in the activity of bivalves: elliptic envelope, isolation forest (iForest), one-class support vector machine (SVM), and local outlier factor (LOF). The results showed that the use of the elliptic envelope, iForest, and LOF methods with proper hyperparameter tuning can detect anomalies in mollusk activity data without false alarms, with an F1 score of 1. A comparison of anomaly detection times revealed that the iForest method is the most efficient. These findings demonstrate the potential of using bivalve mollusks as bioindicators in automated monitoring systems for the early detection of pollution in aquatic environments.<\/jats:p>","DOI":"10.3390\/s23052687","type":"journal-article","created":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T02:02:56Z","timestamp":1677636176000},"page":"2687","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Anomaly Detection in Biological Early Warning Systems Using Unsupervised Machine Learning"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5816-5615","authenticated-orcid":false,"given":"Aleksandr N.","family":"Grekov","sequence":"first","affiliation":[{"name":"Institute of Natural and Technical Systems, 299011 Sevastopol, Russia"},{"name":"Department of Informatics and Control in Technical Systems, Sevastopol State University, 299053 Sevastopol, Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3105-7283","authenticated-orcid":false,"given":"Aleksey A.","family":"Kabanov","sequence":"additional","affiliation":[{"name":"Department of Informatics and Control in Technical Systems, Sevastopol State University, 299053 Sevastopol, Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4890-3247","authenticated-orcid":false,"given":"Elena V.","family":"Vyshkvarkova","sequence":"additional","affiliation":[{"name":"Institute of Natural and Technical Systems, 299011 Sevastopol, Russia"}]},{"given":"Valeriy V.","family":"Trusevich","sequence":"additional","affiliation":[{"name":"Institute of Natural and Technical Systems, 299011 Sevastopol, Russia"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,1]]},"reference":[{"key":"ref_1","first-page":"635","article-title":"Biological early warning system based on the responses of aquatic organisms to disturbances: A review","volume":"466","author":"Bae","year":"2013","journal-title":"Sci. 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