rst Информационно-экономические аспекты стандартизации и технического регулирования Informatsionno-ekonomicheskiye aspekty standartizatsii i tekhnicheskogo regulirovaniya 2311-1348 ФГБУ «Институт стандартизации» IQJCRO 83017071 Research Article Информационные системы и процессы information systems and processes МЕЖДУНАРОДНЫЙ ОПЫТ ПРИМЕНЕНИЯ СИСТЕМ ПЫЛЬЦЕВОГО МОНИТОРИНГА INTERNATIONAL EXPERIENCE OF USING POLLEN MONITORING SYSTEMS 83017071 Лебедев Г. С. Lebedev G. S.

Лебедев Г. С., Первый МГМУ им. И.М. Сеченова

Москва, Россия

Lebedev G. S., I.M. Sechenov First Moscow State Medical University

Moscow, Russia

 83017071 Юхновская Ю. Д. Yukhnovskaya Y. D.

Юхновская Ю. Д., Первый МГМУ им. И.М. Сеченова

Москва, Россия

Yukhnovskaya Y. D., I.M. Sechenov First Moscow State Medical University

Moscow, Russia

 83017071 Гостеева Е. А. Gosteeva E. A.

Гостеева Е. А., Первый МГМУ им. И.М. Сеченова

Москва, Россия

Gosteeva E. A., I.M. Sechenov First Moscow State Medical University

Moscow, Russia

 83017071 Родионов А. С. Rodionov A. S.

Родионов А. С., БГУ им Доржи Банзарова

Улан-Удэ, Россия

Rodionov A. S., Buryat State University named after D. Banzarov

Ulan-Ude, Russia

 83017071 Боева О. С. Boeva O. S.

Боева О. С., ФГБНУ «Научно-исследовательский институт фундаментальной и клинической иммунологии»

Новосибирск, Россия

Boeva O. S., Federal State Budgetary Scientific Institution «Research Institute of Fundamental and Clinical Immunology»

Novosibirsk, Russia

 83017071 Ханчук И. В. Khanchuk I. V.

Ханчук И. В., Первый МГМУ им. И.М. Сеченова,

Москва, Россия

Khanchuk I. V., I.M. Sechenov First Moscow State Medical University

Moscow, Russia

 83017071 Яворская А. В. Yavorskaya A. V.

Яворская А. В., ФГБОУ ВО АМУРСКАЯ ГМА

Благовещенск, Россия

Yavorskaya A. V., Federal State Budgetary Educational Institution of Higher Education «Amur State Medical Academy» of the Ministry of Health of the Russian Federation

Blagoveshchensk, Russia

 83017071 Флорен А. М. Floren A. M.

Флорен А. М., СПбГУ

Санкт-Петербург, Россия

Floren A. M., Saint Petersburg State University

St. Petersburg, Russia

 83017071 Сафарова Д. Д. Safarova D. D.

Сафарова Д. Д., СПбГУ

Санкт-Петербург, Россия

Safarova D. D., Saint Petersburg State University

St. Petersburg, Russia

 Первый МГМУ им. И.М. Сеченова Россия I.M. Sechenov First Moscow State Medical University Russian Federation 2025 130 86 99 103 Copyright © Лебедев Г. С., Юхновская Ю. Д., Гостеева Е. А., Родионов А. С., Боева О. С., Ханчук И. В., Яворская А. В., Флорен А. М., Сафарова Д. Д., 2026 2026 Лебедев Г. С., Юхновская Ю. Д., Гостеева Е. А., Родионов А. С., Боева О. С., Ханчук И. В., Яворская А. В., Флорен А. М., Сафарова Д. Д. Lebedev G. S., Yukhnovskaya Y. D., Gosteeva E. A., Rodionov A. S., Boeva O. S., Khanchuk I. V., Yavorskaya A. V., Floren A. M., Safarova D. D. Данная работа распространяется под лицензией Creative Commons Attribution 4.0. https://iea.gostinfo.ru/article/view/103

Целью исследования является повышение осведомленности о проблеме аллергии на пыльцу и важности использования современных технологий на основе искусственного интеллекта для мониторинга и контроля аллергенов в окружающей среде. Анализ и поиск литературы был выполнен с использованием основных зарубежных и отечественных источников в общедоступных научных базах данных: PubMed, Cochrane, Elibrary. В качестве ключевых слов использовались: «Пыльцевой мониторинг», «Обнаружение пыльцы», «Распознавание пыльцы», “AI pollen identification”. Результаты: автоматизированный процесс мониторинга пыльцы включает 4 основных этапа: сбор данных, обнаружение, классификация и распространение результатов (публикация отчетов, в сети Интернет). Описанный метод может быть применен для распознавания образцов пыльцы, не поддающихся микроскопической идентификации. Проведенный литературный анализ подтверждает необходимость разработки автоматизированных систем мониторинга, работающих в реальном времени с минимальным включением человека в процесс диагностики

The aim of the study is to raise awareness about the problem of pollen allergy and the importance of using modern arti cial intelligence-based technologies to monitor and control allergens in the environment.The analysis and literature search were performed using the main foreign and domestic sources in publicly available scienti c databases: PubMed, Cochrane, Elibrary. The keywords used were: “Pollen monitoring”, “Pollen detection“, ”Pollen recognition“, “AI pollen identification”. Results: The automated pollen monitoring process includes 4 main stages: data collection, detection, classi cation and dissemination of results (publication of reports on the Internet). The described method can be used to recognize pollen samples that are not amenable to microscopic identi cation.The literature analysis con rms the need to develop automated monitoring systems operating in real time with minimal human involvement in the diagnostic process.

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Конфликт интересов. Авторы заявляют об отсутствии конфликта интересов.

The authors declare that there are no conflicts of interest present.